Structural Determinants of T Wave Alternans in Patients with Cardiomyopathy

Adrian M Suszko

A thesis submitted in conformity with the requirements for the degree of Master of Science Graduate Department of Physiology University of Toronto

Structural Determinants of T Wave Alternans in Patients with Cardiomyopathy

Adrian M Suszko

Master of Science

Graduate Department of Physiology University of Toronto

2012 Abstract

Structural barriers can promote discordant action potential (AP) duration alternans, T wave alternans (TWA) and tachyarrhythmia in animal hearts and simulation studies. We hypothesized that heterogeneous scar (gray zone) and dense midwall scar (midwall core) would promote TWA in patients with cardiomyopathy by slowing conduction and uncoupling transmural APs, respectively. Scar core and gray zone were quantified in 40 cardiomyopathy patients using late gadolinium enhanced cardiac magnetic resonance imaging and related to the results of a clinically validated TWA test. The percentages of gray zone, epicardial core and midwall core were greater in the +TWA group, correlated with TWA magnitude and related to a lower heart rate onset for TWA. These specific scar patterns contribute to the genesis and severity of TWA in cardiomyopathy. Greater knowledge of the substrates that promote TWA in cardiomyopathy patients is valuable in determining those at risk of lethal ventricular arrhythmias.

Acknowledgments

First, I would like to thank my supervisor Dr. Vijay Chauhan for his continuous support and guidance throughout the completion of this MSc thesis. Although I was initially apprehensive, I am now truly delighted that he convinced me to return to academia after more than a 2 year hiatus. His unwavering belief in my potential has imparted me with a sense of purpose and direction. I can only hope that this experience has been as fruitful for him as it was for me.

Second, I wish to thank my incredible committee members Dr. Peter Backx and Dr. Graham Wright for their invaluable insight at each stage of this MSc project. Their objective stance kept me honest and true to the scientific process. Moreover, I greatly appreciate their enthusiastic encouragement to continue in academic pursuits upon the completion of this degree.

Third, I would like to acknowledge our research collaborators. This includes Dr. Andrew Crean who provided clinical CMR support for this study, Dr. Joan Ivanov who verified my statistical approach, and Drs. Arnold Pinter and Andrew Yan who critically evaluated the final project. Additional thanks goes to the research coordinators Jabeen Khan, Ann Hill, Theresa Aves and Antonio Estacio who's tireless recruitment efforts ensured that I had a patient population upon which to test my hypotheses.

Fourth, I would like to thank the eclectic group of cardiac electrophysiology fellows who supervised each of my research studies. They also functioned as my lab mates, each of them enriching my time as a MSc student in their own way. I would especially like to express my gratitude to Dr. Raja Selvaraj, Dr. Danna Spears, Dr. Benedict Glover and Dr. Sing-Chien Yap.

Fifth, I recognise that I could not have accomplished such a feat without the lifelong love and support of my parents. I am also grateful to my brother and friends for their understanding as to why I have been so elusive these past couple years.

Final and most importantly, I would like to thank Ashley Wood, the single most significant person in my life and my inimitable source of inspiration. Without her unremitting love, patience and understanding I certainly would not have reached this pinnacle. Thus to her I owe an immeasurable debt that I hope to one day repay in full. I know it hasn't been easy but thanks for walking with me, every step of the way.

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Table of Contents

Acknowledgments ...... iii

Table of Contents ...... iv

List of Tables ...... vii

List of Figures ...... viii

List of Abbreviations ...... x

List of Variables ...... xii

1 Introduction ...... 1

1.1 Electrophysiology of the Heart Beat ...... 1

1.1.1 Cardiac Ion Channels, Exchangers and Pumps ...... 1

1.1.2 The Cardiac Action Potential ...... 3

1.1.3 Excitation-Contraction Coupling and Ca2+ Cycling ...... 7

1.2 Sudden Cardiac Arrest ...... 9

1.2.1 Ventricular Tachyarrhythmias ...... 10

1.3 T Wave Alternans ...... 12

1.3.1 T Wave Alternans is a Marker of Electrical Instability ...... 12

1.3.2 Physiological Modulation of T Wave Alternans ...... 15

1.3.2.1 Heart Rate ...... 15

1.3.2.2 Autonomic Stimulus ...... 15

1.3.2.3 Myocardial Ischemia ...... 16

1.3.2.4 Antiarrhythmic Medications ...... 16

1.3.3 Action Potential Duration Alternans Underlie T Wave Alternans ...... 17

1.3.4 Mechanisms of Action Potential Duration Alternans ...... 19

1.3.4.1 Action Potential Duration Restitution ...... 19

1.3.4.2 Ca2+ Cycling ...... 21

1.3.5 Action Potential Duration Alternans in the Ventricular Myocardium ...... 23

1.3.6 Mechanisms of Discordant Action Potential Duration Alternans ...... 26

1.3.6.1 Heterogeneity in Action Potential Duration and Action Potential Duration Restitution ...... 26

1.3.6.2 Heterogeneity in Ca2+ Handling Properties ...... 28

1.3.6.3 Conduction Velocity Restitution ...... 28

1.3.7 Role of Structural Barriers in Promoting Discordant Action Potential Duration Alternans ...... 31

1.3.8 Discordant Action Potential Duration Alternans as a Substrate for Arrhythmias ...... 35

1.4 Cardiomyopathy ...... 35

1.4.1 Myocardial Fibrosis in Cardiomyopathy ...... 38

1.4.2 T Wave Alternans in Cardiomyopathy ...... 41

2 Rationale, Hypothesis and Objectives...... 44

2.1 Rationale ...... 44

2.2 Hypothesis ...... 45

2.3 Objectives ...... 45

3 Methods ...... 46

3.1 Patient Population ...... 46

3.2 Cardiac Magnetic Resonance Protocol ...... 46

3.3 Cardiac Magnetic Resonance Image Analysis ...... 47

3.4 T Wave Alternans Protocol ...... 49

3.5 T Wave Alternans Analysis ...... 51

3.5.1 QRS Detection ...... 51

3.5.2 Baseline Correction ...... 54

3.5.3 Beat Alignment ...... 54

3.5.4 Spurious Beat Replacement ...... 55

3.5.5 Spectral Analysis ...... 55

3.5.6 TWA Artifact Detection ...... 57

3.5.7 T Wave Alternans Classification ...... 57

3.5.8 Clinical TWA Analysis ...... 58

3.6 Clinical Outcomes ...... 58

3.7 Statistical Analysis ...... 58

4 Results ...... 61

4.1 Patient Population ...... 61

4.2 Prevalence of +TWA ...... 61

4.3 TWA Algorithm Validation ...... 61

4.4 CMR Assessment ...... 64

4.5 Predictors of +TWA ...... 64

4.6 Relationship between TWAmax and +TWA Predictors ...... 68

4.7 Heart Rate Onset for TWA and +TWA Predictors ...... 68

4.8 Absence of Scar and TWA ...... 68

4.9 Clinical Outcomes ...... 72

5 Discussion ...... 73

5.1 Gray zone, midwall core and epicardial core contribute to T wave alternans in cardiomyopathy patients ...... 73

5.2 Clinical Implications ...... 75

5.3 Limitations ...... 77

5.4 Conclusions ...... 78

5.5 Future Directions ...... 78

References ...... 80

List of Tables

Table 1. The association of core and gray zone with cardiac outcome in various cardiomyopathy populations...... 42

Table 2. Clinical characteristics of the study population...... 62

Table 3. Cardiac magnetic resonance characteristics of the study population...... 65

Table 4. Response of T wave alternans to increasing pacing rate...... 70

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List of Figures

Figure 1. The major ion currents involved in the generation of the ventricular action potential. .. 5

Figure 2. Relation of the cardiac action potential to the body surface electrocardiogram...... 8

Figure 3. Electrical reentry in cardiac tissue...... 11

Figure 4. Clinical examples of electrocardiographic T wave alternans...... 13

Figure 5. The cellular basis of T wave alternans...... 18

Figure 6. Action potential duration restitution as a mechanism of action potential duration alternans...... 20

Figure 7. Comparison of spatially concordant and discordant action potential duration alternans...... 24

Figure 8. Comparison of T wave alternans generated by concordant and discordant action potential duration alternans...... 25

Figure 9. Conduction velocity restitution as a mechanism of discordant action potential duration alternans...... 30

Figure 10. Discordant action potential duration alternans induced by an insulating barrier in the guinea pig model...... 32

Figure 11. Discordant action potential duration alternans induced by diffuse structural heterogeneities in a simulated tissue sheet...... 34

Figure 12. Discordant action potential duration alternans as a mechanism of reentry...... 36

Figure 13. Late gadolinium enhanced cardiac magnetic resonance imaging of myocardial fibrosis...... 39

Figure 14. Scar characterization methods in a representative late gadolinium enhanced cardiac magnetic resonance LV slice...... 48

Figure 15. Method for calculating transmural distribution of core in a representative late gadolinium enhanced cardiac magnetic resonance LV slice...... 50

Figure 16. T wave alternans ECG preprocessing methods...... 52

Figure 17. Spectral analysis of T wave alternans...... 56

Figure 18. HeartWave clinical TWA results output for the precordial leads from a representative +TWA patient during a TWA pacing protocol...... 59

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Figure 19. Comparison of TWA detection between the clinical TWA analysis tool and our software in a representative patient...... 63

Figure 20. Comparison of gray zone between a -TWA and +TWA patient ...... 66

Figure 21. Comparison of midwall core between a -TWA and +TWA patient ...... 67

Figure 22. Core and gray zone characteristics of a patient with large magnitude TWA...... 69

Figure 23. Comparison of scar and TWA onset heart rate ...... 71

List of Abbreviations

AP action potential

APD action potential duration

APDA action potential duration alternans

ATPase adenosine triphosphatase

AV atrioventricular

Ca2+ calcium

CL cycle length

Cl- chloride

CMR cardiac magnetic resonance

CV conduction velocity

DCM dilated cardiomyopathy

DI diastolic interval

ECG electrocardiogram

FWHM full width at half maximum

HCM hypertrophic cardiomyopathy

ICaL L-type calcium current

ICD implantable-cardioverter defibrillator

ICM ischemic cardiomyopathy

IK1 inward rectifier potassium current

IKr rapid delayed rectifier potassium current

IKs slow delayed rectifier potassium current

INa inward sodium current

Ito transient outward current

Ito1 transient outward potassium current

Ito2 transient outward chloride current

K+ potassium

LGE late gadolinium enhancement

LV left ventricle

LVEDV left ventricular end-diastolic volume

LVEF left ventricular ejection fraction

LVESV left ventricular end-systolic volume

Na+ sodium

NCX sodium-calcium exchanger

RV right ventricle

RyR2 ryanodine receptor type 2

SA sinoatrial

SCA sudden cardiac arrest

SCD sudden cardiac death

SERCA2a sarcoplasmic/endoplasmic reticulum calcium adenosine triphosphatase

SI signal intensity

SR sarcoplasmic reticulum

TWA T wave alternans

VF ventricular fibrillation

VT ventricular tachycardia

List of Variables

+TWA T wave alternans positive

-TWA T wave alternans negative k value T wave alternans signal to noise ratio

Coreendo% Endocardial core as a percentage of the left ventricular circumference

Coreepi% Epicardial core as a percentage of the left ventricular circumference

Corefull% Full thickness core as a percentage of the left ventricular circumference

Coremid% Midwall core as a percentage of the left ventricular circumference

Scarcore Absolute size of core

Scargray Absolute size of gray zone

Scartotal Absolute size of total scar

Scarcore% Core size as a percentage of the left ventricular mass

Scargray% Gray zone size as a percentage of the left ventricular mass

Scartotal % Total scar size as a percentage of the left ventricular mass

Valt T wave alternans magnitude

TWAmax Maximum T wave alternans magnitude

TWAonset T wave alternans onset heart rate

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1 Introduction 1.1 Electrophysiology of the Heart Beat

The vertebrate heart is a myogenic muscular organ that is most succinctly and accurately described as an electrically controlled mechanical pump. Its regular rhythmic contraction is required for the continuous distribution of oxygenated blood and other essential nutrients to the entirety of the body. If the organized electrical activity that drives each heart becomes disordered, the heart will ceases to beat effectively, consciousness will be lost after 20 seconds, irreparable brain damage will occur within 3 to 5 minutes and permanent death will follow.1 Thus maintenance of a consistent cardiac cycle is obviously paramount to sustaining human life.

A normal cardiac cycle begins when an electrical impulse is generated by the pacemaker cells of the sinoatrial (SA) node in the upper right atrium.2 Although all types of cardiomyocytes technically possess automaticity,3 the SA pacemaker cells typically control rhythm because they spontaneously depolarize more quickly than any other type, from 60 to 100 times per minute in the human heart.4 The stimulus proceeds from the SA node to the atria via Bachmann’s bundles and the atrial tracts.2 This causes synchronous contraction of the atrial myocardium which forces blood into the ventricles. As the electrical wavefront propagates through the atria, the impulse is simultaneously conducted to the atrioventricular (AV) node in the interatrial septum. The AV node controls ventricular rhythm and delays conduction long enough to allow for ventricular filling. Conduction velocity (CV) increases again when the stimulus reaches the bundle of His where the conduction system is split into three bundle branches that run along the interventricular septum. The right, left posterior and left anterior bundle branches are further divided into thin filaments, known as Purkinje fibres, which are spread throughout the ventricular myocardium to evenly distribute conduction. The stimulation of the ventricular myocardium results in coordinated contraction of the right and left ventricles which pump deoxygenated blood to the lungs and oxygenated blood to the body, respectively. This process repeats upon the generation of the next impulse within the SA node.

1.1.1 Cardiac Ion Channels, Exchangers and Pumps

The uniform contraction of the myocardium is a consequence of the sequential stimulation of countless individual cardiomyocytes.5 The electrical impulses which facilitate contraction are

2 created by small fluctuations in the concentration of ions within each cell. Although the plasma membrane, or sarcolemma, surrounding each myocyte is a hydrophobic milieu that prevents the passage of hydrophilic ions, there are a unique set of proteins embedded in the membrane that permit ion entry and exit. These porous transmembrane proteins include ion channels, exchangers and pumps.

Ion transporting proteins typically exhibit two fundamental properties: selective permeability and gating.6 Selective permeation, which is controlled by a region within the pore known as the selectivity filter, allows for the passage of certain ions and not others. For instance, L-type Ca2+ channels mainly facilitate the passage of Ca2+ ions,7 while cardiac Cl- channels allow for the passage of Cl- and other small cations.8 Gating influences accessibility to the pore, and can be dependent on membrane voltage (voltage gating) or the presence of a specific molecule (ligand gating). Many cardiac channels have multiple gates which can produce distinct closed states. A classic example is the voltage gated Na+ channel which is hypothesized to exist in a “resting” closed state at low membrane voltages prior to activation, in which the “m gate” is shut, and in an “inactive” closed state at high membrane voltages post activation, in which the “h gate" is shut.9

Ion channels permit ions to passively diffuse across the sarcolemma according to their respective electrochemical gradient, a summation of their chemical and electrical gradients.5 The chemical gradient is determined by the concentration of a particular ion in the intracellular and extracellular compartments, and promotes movement of ions from an area of higher concentration to an area of lower concentration. The electrical gradient is determined by the electrical potentials of the intracellular and extracellular compartments, and causes cations to move toward relatively more negative compartments and anions to move toward relatively more positive compartments. If acting in opposition, these two forces will attempt to reach an equilibrium point where the force of moving the ion in one direction equals to that of the force moving the ion in the opposite direction. This equilibrium point is associated with a specific transmembrane potential for each ion, termed the equilibrium potential. For example, K+ ions will no longer be compelled to cross the membrane when their equilibrium potential of approximately -90 mV is reached.10 When active, ion channels can support the rapid movement of ions both into and out of the cardiomyocyte.

Conversely, ion exchangers and ion pumps have the ability to move ions in opposition to their electrochemical gradients. For instance, the Na+/Ca2+ exchanger (NCX) can swap 3Na+ for 1Ca2+ in either direction by using the electrochemical gradient of one ion to transport the other ion against its gradient.11 On the other hand, the plasma membrane Ca2+ adenosine triphosphatase (ATPase) uses energy to expel Ca2+ from the cytosol against its electrochemical gradient.12 Because they are operating against gradients, ion exchangers and pumps are also considerably slower in transport than ion channels. While the L-type Ca2+ channel can allow nearly 3 million Ca2+ ions to pass per second,13 the Na+/Ca2+ exchanger and the plasma membrane Ca2+ ATPase only permit the approximate passage of 500014 and 3015 ions per second, respectively. The primary purpose of ion pumps and exchangers is to restore and maintain ion homoeostasis after rapid alterations in ion concentration by ion channels.

The passage of ions into and out of the myocyte generates current which alters the electrical potential of the plasma membrane.2 The major ions that affect cardiomyocyte membrane potential are K+, Na+, Ca2+ and to a lesser extent Cl-. Under normal physiological conditions, the extracellular Na+, Ca2+ and Cl- concentrations are relatively large compared to that of the intracellular fluid, whereas the K+ concentration is substantially greater within the myocyte. While at rest, a partial permeability to K+ coupled with limited permeability to other ion species encourages K+ to exit the myocyte and drives the membrane potential toward the negative K+ equilibrium potential. On the contrary, opening of Na+ or Ca2+ channels will raise the membrane potential as the positive ions rush into the myocyte.

1.1.2 The Cardiac Action Potential

The cardiac action potential (AP) is the aggregate of all electrical activity generated by the coordinated opening and closing of the ion channels, pumps and exchangers from a single cardiomyocyte during a cardiac cycle.6 Cardiac APs can last for hundreds of milliseconds and are considerably more sophisticated than the brief APs generated by nervous and skeletal tissue.2 There are two main groups of cardiac APs. The pacemaker potentials found in the SA and AV nodes are slowly activating, and are primarily responsible for maintaining and adjusting the cardiac rhythm. Non-pacemaker potentials found in the atria and ventricles are rapidly activating, and are responsible for the physical contraction of the myocardium. Amongst the different types of non-pacemaker cardiomyocytes, variable expression of the constituent ion channels creates

4 subtle yet important differences in the AP amplitude and duration. Atrial APs are the smallest and shortest, Purkinje APs are the largest and longest, while ventricular APs fall somewhere in between. However, even amongst ventricular APs, there can be considerable variation in AP shape depending on the location of the myocyte within the ventricular myocardium.16 Figure 1 illustrates the five phases of the typical ventricular AP and the primary currents involved in its generation.

Phase 4 is the resting membrane potential. It is the flat negative portion of the AP associated with diastole. The duration between successive APs is referred to as the diastolic interval (DI). In the normal human ventricular myocyte, the resting potential is approximately -80 mV.17 This negative potential is primarily maintained by the voltage regulated inward rectifier K+ current

(IK1). While other ion channels are closed at highly negative membrane potentials, the IK1 channels are open. The resultant high K+ permeability coupled with a low permeability to other ion species drives the resting potential toward the K+ equilibrium point of -90 mV.10 There are also several ion pumps and exchangers which assist in preserving the appropriate ion concentration gradients during phase 4. Perhaps most important is the Na+/K+ ATPase which actively transports Na+ and K+ against their electrochemical gradients. It is the primary mechanism by which excess Na+ is removed from the myocyte and creates a small outward current by expelling 3 Na+ ions for every 2 K+ ions brought into the myocyte.18 NCX is also active, generating a small inward current as it extrudes surplus Ca2+ from the cytosol.14

Phase 0 is the activation/depolarization of the myocyte and is associated with systole. It is defined by the steep upstroke of the AP. Activation typically begins with the entry of positive ions via gap junctions which predominately adjoin cardiomyocytes at their longitudinal ends.19 This gap junctional coupling is essential for swift propagation of the AP from one myocyte to another. The influx of positive ions raises the membrane potential to a threshold level between - 70 and -60 mV, which causes voltage gated Na+ channels to rapidly open (activate).20 The large + + inward Na current (INa), generated by Na ions flowing down their electrochemical gradient and into the myocyte, further depolarizes the membrane to approximately 25 mV.21 The positive membrane potential simultaneously triggers the fast inactivation of the INa which causes the channels to close as quickly as they opened. The depolarized state is further supported by the closure of IK1 at positive membrane potentials.

Figure 1. The major ion currents involved in the generation of the ventricular action potential.

A representative ventricular AP illustrating the membrane currents that produce each of the five distinct phases: the upstroke (0), early repolarization (1), the plateau (2), final repolarization (3) and the resting potential (4). The depolarizing INa and ICa currents are shown in yellow boxes. The repolarizing IK1, Ito, IKs and IKr currents are shown in gray boxes. NCX is shown in both a yellow box and gray box since it produces outward current during phase 1 and inward current during phase 4. The black bars below the figure indicate the time periods at which each current is primarily active. Figure adapted with permission from Macmillan Publishers Ltd: Nature Reviews Drug Discovery (Nattel and Carlsson22), copyright © 2006.

Phase 1 is termed early repolarization and is characterized by a small downward deflection or "notch" immediately following depolarization. This brief repolarization event is the product of + two short lived transient outward currents (Ito): the voltage activated transient outward K current - 6 (Ito1) and the calcium activated transient outward Cl current (Ito2). The opening of Ito1 and Ito2 at positive membrane potentials allows K+ and Cl- to flow down their electrochemical gradients out of and into the myocyte, respectively. Although brief, Ito exerts considerable influence on the AP duration (APD) by modifying the cycling behaviour of other ion channels that are active during later phases of the AP. For instance, suppression of Ito1 channel opening has been shown to significantly lengthen APD in the ventricular myocardium.23 NCX also contributes to phase 1, producing a small outward current as it reverses direction in response to the high intracellular Na+ concentration created by activation.

Phase 2 is the positive plateau of the AP near 0 mV. The lack of change in net current is created 2+ + by a balancing of inward Ca currents and outward K currents. ICaL channels open rapidly when the membrane potential rises above approximately -30 mV, but inactivate slowly to promote an 24 2+ extended APD. Importantly, ICaL ensures that there is enough Ca available to facilitate excitation-contraction coupling which is discussed in the following section. Two major voltage- + + dependant K currents combine to counteract ICaL: the rapid delayed rectifier K current (IKr) and + 25 the slow delayed rectifier K current (IKs). IKr channels initiate the repolarization process when they open early in phase 2. IKs channels open more slowly, allowing IKs build to a peak current during the later stages of repolarization. The plateau phase creates an extended period of time in which the myocyte cannot be re-stimulated. This is referred to as the effective refractory period and its existence is essential for the prevention of reentrant arrhythmias.26

Phase 3 is the final repolarization of the myocyte. It is characterized by a down slope in the AP that extends all the way to the level of the resting potential. The increased intracellular Ca2+ 27 + concentrations from phase 2 promote inactivation of ICaL. Because the delayed rectifier K currents are no longer competing with ICaL, the membrane potential quickly drops. This promotes the reopening of the IK1 channels which furthers the repolarization process. NCX once again 2+ become active to assist in reducing intracellular Ca levels. Finally, closure of the IKr and IKs channels returns the myocyte to its initial resting state.

While the AP represents the electrical activity in a single myocyte, the temporal summation of the APs from all cardiomyocytes can be visualized on the body surface using the electrocardiogram (ECG).2 Figure 2 displays an ECG and relates its components to the APs from various regions of the heart. The relatively small P wave is associated with atrial depolarization, whereas the large QRS complex represents ventricular depolarization. The PR interval is the delay from sinus node activation to ventricular depolarization, and is frequently used as a measure of AV node function.28 Atrial repolarization is not evident on the ECG but ventricular repolarization is clearly demarcated by the broad T wave following the QRS. The ST segment, the region between the T wave and QRS complex, is normally isoelectric and is often used as a diagnostic marker. ST elevation is a typical indication of transmural myocardial infarction,29 whereas ST depression is often a sign of subendocardial ischemia.30 Although the majority of repolarization occurs within the JT interval, a U wave may occasionally be visible subsequent to the T wave. The U wave is likely a delayed repolarization waveform but the exact cellular mechanisms responsible for this minor ECG perturbation have yet to be fully elucidated.31 The time between two consecutive QRS complexes is referred to as the RR interval or cycle length (CL). Significant alterations in ventricular AP morphology are often reflected in the ECG. As an example, mutations that prolong the APD such as long QT syndrome, will also produce a noticeable lengthening of the ECG QT interval.32

1.1.3 Excitation-Contraction Coupling and Ca2+ Cycling

Excitation-contraction coupling is the process by which an AP triggers the contraction of the cardiomyocyte.33 Interaction with the cellular contractile machinery is facilitated by a transient increase in the concentration of free cytosolic Ca2+ after depolarization. In fact, measurement of the Ca2+ transient reveals that cytosolic Ca2+ levels can increase by tenfold during systole in the normal ventricular myocyte.34 The readily available cytosolic Ca2+ binds to troponin, a protein complex that normally inhibits interaction between the actin and myosin contractile myofilaments. Ca2+ binding produces a conformational change in troponin which permits myofilament interaction and subsequent myocyte shortening.35 Myocyte relaxation occurs as the Ca2+ transient dissipates and Ca2+ becomes unbound from troponin. Thus excitation-contraction coupling is clearly dependent on cytosolic Ca2+ cycling dynamics.

Figure 2. Relation of the cardiac action potential to the body surface electrocardiogram.

(A) The typical AP recordings from various regions of the heart are referenced to the ECG components that they produce. Atrial depolarization is responsible for the P wave. The QRS complex begins with endocardial depolarization and ends with epicardial depolarization. The T wave is created by the repolarization of all ventricular myocytes but specifically ends with the final repolarization of the endocardial cells. (B) A representative ECG tracing for a single cardiac cycle. Panel A adapted with permission from The American Physiological Society: Physiological Reviews (Nerbonne and Kass36), copyright © 2005.

In the mammalian cardiomyocyte, Ca2+ cycling is a dynamic process that includes both intracellular and extracellular components.2 Although some Ca2+ enters the cell from the extracellular space via ICaL channels, the majority is released into the cytosol from the sarcoplasmic reticulum (SR), a specialized Ca2+ storing organelle, in a process termed Ca2+- 2+ 2+ induced Ca release. The sequence begins when the initial Ca influx through sarcolemmal ICaL channels is detected by nearby SR Ca2+ release channels know as the type 2 ryanodine receptors (RyR2). Because RyR2 is Ca2+ sensitive, a positive feedback response occurs such that an even larger amount of Ca2+ is rapidly released from the SR. Increased cytosolic Ca2+ also simultaneously triggers a negative feedback pathway such that ICaL experiences a long lasting Ca2+ induced inactivation.37 This response is presumed to limit the length of contraction by preventing additional Ca2+ influx once Ca2+-induced Ca2+ release has been triggered. As Ca2+ exits the SR, it is concurrently resequestered into the SR by the sarcoplasmic/endoplasmic reticulum Ca2+ ATPase (SERCA2a). Interestingly, the SR calcium cycling machinery exhibits memory such that Ca2+ release by RyR2 typically equals Ca2+ uptake by SERCA2a.37 The 2+ additional Ca which entered via ICaL is primarily expelled by NCX, as previously discussed.

1.2 Sudden Cardiac Arrest

Sudden cardiac arrest (SCA) is the abrupt and unexpected loss of heart function. During SCA, the normal cardiac cycle is suspended, cardiac contraction ceases and systemic circulation is lost. SCA is considered to be the most devastating manifestation of heart disease because it can progress from onset to death within minutes if not treated by cardiopulmonary resuscitation and defibrillation. In fact, any death within one hour of initial symptoms is typically attributed to SCA and is classified as a sudden cardiac death (SCD).38

SCA is not only lethal but also quite prevalent. SCD is experienced by up to 300,000 Americans39 and 40,000 Canadians40 each year. Unfortunately, the majority of these individuals die out-of-hospital and SCA survival rates have been reported to be as low as 3%.41 Given these statistics it is not surprising that SCD is the leading cause of mortality within the industrialized world, accounting for greater than 50% of cardiac deaths and 6% of all deaths.42 Naturally, identifying and preventing SCD in those at risk has become a primary objective amongst healthcare practitioners. There are various ways to risk stratify for SCD but the majority of individuals at risk still remain unidentified.43 The principal means of preventing SCD is through

10 the use of an implantable cardioverter-defibrillator (ICD), a battery operated implanted device which detects potential lethal arrhythmias and delivers an electrical shock to reset the heart’s rhythm.44

1.2.1 Ventricular Tachyarrhythmias

The etiologies of SCA are complex and varied. It can occur in the structurally normal hearts of individuals with inherited arrhythmias45 but is also commonly associated with structural diseases of the heart.46 However, the specific mechanism underlying SCA in patients with structural heart disease may be common in many cases. Clinical studies suggest that the cause of SCA in nearly 80% of individuals is a ventricular tachyarrhythmia.42 In these patients, the typical pathophysiological cascade involves the development of a ventricular tachycardia (VT) which degenerates into ventricular fibrillation (VF) and finally asystole.38 Occasionally, VF can also spontaneously develop without being preceded by VT.47 Nonetheless, the most common mechanism for the initiation of VT or VF is a process known as reentry.

Reentry, first demonstrated by Mines,48 occurs when a local electrical circuit develops within the myocardium. Figure 3 illustrates the reentry process. The initial requirement for reentry is the presence of a central nonconductive region. This region can be anatomical, such as an area of nonconductive collagenous tissue,49 or functional, such as a region of myocytes that has yet to recovery from a previous stimulus.50 When an electrical wavefront encounters the nonconductive area it is forced to divide, creating two distinct conduction pathways.2 The second requirement of reentry is unidirectional block. Due to heterogeneity in the electrophysiological properties of the myocardium, the recovery time (effective refractory period) of the two pathways may not be equal. Unidirectional block will occur if the propagating stimulus encounters the effective refractory period of myocytes in one pathway but not the other. The final requirement for reentry is delayed conduction. The wavefront which travelled along the unblocked pathway will eventually return to the pathway of unidirectional block in a retrograde manner. If the stimulus propagates slowly enough, it will not encounter the effective refractory period of the initially stimulated tissue, and the reentry circuit will be completed. Once reentry is established, the circuitous conduction can proceed indefinitely unless it is terminated by another stimulus or encounters a new region of block. Thus substrates which produce marked dispersion of refractoriness are also those most likely to cause reentry and SCA.

Figure 3. Electrical reentry in cardiac tissue.

Illustration of normal and reentrant conduction around a central nonconductive region (orange triangle). The green asterisk represents the site of a recording electrode. (A) Under normal conditions, the electrical wavefront (red line) divides upon reaching the nonconductive region and propagates evenly down pathways 1 and 2. The stimuli cancel each other out when they collide in the connecting pathway 3. This process repeats upon the generation of the next stimulus and normal APs are created at the site of the electrode. (B) Under reentrant conditions, one of the branching pathways experiences unidirectional block (gray area). In this case, the wavefront is able to propagate normally down pathway 1 but is unable to enter pathway 2, which has yet to recover from a previous excitation. The stimulus then proceeds from pathway 1 through the connecting branch 3 and retrograde into pathway 2. Conduction delay (wavy blue line) through the region of unidirectional block, caused by incomplete recovery of INa, provides enough time for the tissue in pathway 1 to become reexcitable. Thus the stimulus is able to reenter pathway 1 from pathway 2 and a high frequency counterclockwise reentrant circuit is established. After the initial AP, tachyarrhythmia is viewed at the site of the electrode. Figure adapted with permission from Richard Klabunde: Cardiovascular Physiology Concepts (Klabunde51), copyright © 2007.

1.3 T Wave Alternans

In 1908, shortly after the invention of the ECG, Hering52 noted a visible and regular alternation in the amplitude of the T wave in dogs after the administration of glycolic acid. This abnormal repolarization phenomenon was dubbed T wave alternans (TWA) and has since been defined as the beat to beat alternation in the amplitude, shape or timing of the ECG T wave. The difference in amplitude between short and tall T waves is typically referred to as the TWA magnitude. Importantly, the TWA phenomenon is said to reflect primary fluctuations of the T wave that are not a consequence of other spatial (e.g. QRS alternans) and temporal (e.g. CL alternans) alternating ECG components.53 Clinical examples of TWA are illustrated in Figure 4.

1.3.1 T Wave Alternans is a Marker of Electrical Instability

Upon its initial discovery in humans, the presence of TWA was astutely associated with a poor prognosis.54 Visible TWA has since been reported in a wide variety of clinical conditions that also happen to have a high incidence of arrhythmia such as acute myocardial infarction and ischemia,55 long QT syndrome,56 Brugada syndrome,57 alcoholic cardiomyopathy,58 Prinzmetal’s angina,59 and electrolyte disturbances.60 Further linking TWA and cardiac electrical instability are case reports documenting macroscopic alternans immediately preceding episodes of sustained polymorphic VT.61 Although visible TWA is clearly a cause for concern, it is a fairly rare event which only appears in approximately 0.1% of all individuals.62

Technological advances in the 1980s led to the development of the spectral method for the detection of non visible microvolt level alternans by Adam and colleagues.63 This computer enhanced analysis revealed microscopic TWA to be far more common than macroscopic TWA. Microvolt TWA is detected in over 50% of patients with structural heart disease,64 and has even been observed in normal individuals at rapid heart rates.65 Microvolt level analysis has also reinforced the link between TWA and arrhythmia. Using pig models, Cohen and coworkers63, 66 were able to establish a relationship between TWA and VF susceptibility. They observed that a decrease in the VF threshold correlated with an increase in TWA magnitude. The same association was subsequently seen in dog experiments by Nearing and associates.67 In humans, a 65% increase in the magnitude of microvolt TWA has been observed before the onset of ventricular tachyarrhythmias on electrograms stored by ICDs.68 Together, these studies strongly

Figure 4. Clinical examples of electrocardiographic T wave alternans.

(A) Classical example of macroscopic TWA in which the T wave amplitude alternates on an every other beat basis. (B) TWA immediately preceding polymorphic VT. The alternans are so pronounced in this case that the T waves alternate in polarity. (C) Subtle TWA elicited by exercise in a patient with coronary artery disease. The tall short alternation in the T wave becomes apparent when two successive complexes are magnified and superimposed. Notice that there is very little beat to beat variation of the QRS complex or CL in these examples. Panel A adapted with permission from BMJ Publishing Group Ltd: British Journal of Sports Medicine (Johnson and Ackerman69), copyright © 2009. Panel B adapted with permission from Massachusetts Medical Society: New England Journal of Medicine (Raeder et al.61), copyright © 1992. Panel C adapted with permission from Elsevier : Journal of the American College of Cardiology (Verrier et al.70), copyright © 2011.

14 suggest that microvolt TWA is an easily detectable precursor to life threatening ventricular tachyarrhythmias.

In the mid 1990s, recognizing the potential prognostic value, clinicians began conducting trials to assess the ability of TWA for detecting SCA risk in humans. Rosenbaum and colleagues71 were the first to find a significant link between VT inducibility and TWA in a human population. Follow-up of this cohort revealed TWA testing to be comparable to standard electrophysiological testing for predicting arrhythmia free survival. Based on the results of this study and subsequent work by Cohen and coworkers,72, 73 a clinical TWA test has since been established. An abnormal clinical TWA test is defined as a TWA magnitude ≥1.9 µV occurring at ≤110 bpm while being sustained for at least 1 minute. Using this definition, several large clinical trials have been conducted in a wide range of groups deemed to be at risk of SCA.64, 74-79 A meta- analysis of all trials performed between 1990 and 2004 showed the mean positive and negative predictive values of TWA testing for ventricular tachyarrhythmias to be 19.3% and 97.2%, respectively.80 On a broad scale, the power of TWA testing appears to be its ability to determine those with a low arrhythmia risk. Thus TWA testing has been incorporated into clinical risk stratification guidelines for SCD.81

On the other hand, two large prospective trials have recently brought the prognostic value of TWA into question. The MASTER I trial examined 575 individuals with prior myocardial infarction and reduced ventricular contractile function.82 They found no association between TWA positivity and ventricular tachyarrhythmia risk. The SCD-HeFT study similarly found no relation between lethal arrhythmia risk and TWA in a cohort of 490 individuals with heart failure and reduced ventricular contractile function.78 Although it is not entirely clear why the results of these clinical trials deviate from the majority, a recent study by Hohnloser et al.83 suggests that their reliance on ICD shocks as a surrogate of SCD may account for the lack of TWA predictivity. In this meta-analysis, prospective TWA trials with high ICD usage (2234 patients including MASTER I and SCD-HeFT trials) were compared to those with low ICD usage (3682 patients). This revealed the hazard ratio for predicting SCD with TWA amongst the studies with low ICD usage to be 13.6, whereas the hazard ratio for predicting SCD with TWA amongst the studies with high ICD usage was only 1.6. Thus it may be that ICDs overestimate true tachyarrhythmic events which obfuscates the predictive accuracy of TWA testing.

1.3.2 Physiological Modulation of T Wave Alternans

TWA susceptibility and magnitude is influenced by various physiological factors. Interestingly, physiological interventions that amplify TWA often increase vulnerability to ventricular tachyarrhythmias, whereas physiological interventions that attenuate TWA often reduce arrhythmic vulnerability. Such relationships further highlight the link between TWA and arrhythmogenesis. Commonly known modulators of TWA include heart rate, autonomic stimulus, myocardial ischemia and antiarrhythmic medications.

1.3.2.1 Heart Rate

TWA is perhaps most closely associated with heart rate. In healthy subjects, experimental84 and clinical65 studies demonstrate that TWA is not present at baseline but can be elicited at higher heart rates. In these cases, the alternans is considered to be a normal physiological response. On the other hand, TWA at reduced heart rates is an uncommon occurrence that is associated with ventricular tachyarrhythmia and SCA in humans.71 Once the patient-specific heart threshold for TWA is reached, subsequent elevations in heart rate increase both the stability and magnitude of TWA in clinical studies.85-87 The use of atrial or ventricular pacing to elevate heart rate in these patients suggests that the influence of rate on TWA is independent of autonomic stimulus. TWA can also exhibit a hysteresis effect such that alternans may persist at lower heart rates than were required to induce it.88, 89 This memory effect has been proposed to explain why the majority of SCDs occur at resting heart rates that are typically below the threshold required to elicit TWA.89

1.3.2.2 Autonomic Stimulus

Though TWA is primarily considered to be a heart rate related phenomenon, the autonomic nervous system also plays an active role in modulating TWA magnitude and vulnerability. Both sympathetic and parasympathetic stimuli can independently influence TWA in experimental and clinical situations, as previously reviewed.90

The effects of sympathetic stimulation and blockade on TWA are fairly well studied. In experiments with in vivo dog hearts, excision of the stellate ganglia significantly reduced ischemia induced TWA, while stimulation of the same ganglia returned TWA to pre-stellectomy levels.67 Importantly, a constant heart rate was maintained with atrial pacing to ensure that the effects of the sympathetic nervous system were independent of chronotropic changes. A clinical

16 study comparing exercise and pacing induce TWA demonstrated that although the onset heart for TWA was similar between the two groups, the TWA magnitude at peak heart rate was significantly greater in the exercise group where sympathetic activity was presumed to be greater.85 Conversely, sympathetic blockade with β-blocking agents decrease TWA magnitude in individuals prone to SCD91-93 but has little affect on TWA in individuals without a history of VT.93 Mental stress, which enhances sympathetic activity, also increases TWA magnitude without significantly altering heart rate in individuals at risk of SCD.94, 95 However, the same stress protocol does not alter TWA magnitude in age matched normal individuals.95

Parasympathetic modulation of TWA is less clearly understood. Direct vagus nerve stimulation has been shown to reduce ischemia induced TWA magnitude experimentally.96 This is consistent with the observation that vagal excitation reduces VF susceptibly during ischemia.97 On the other hand, pharmaceutical blockade of the parasympathetic nervous system does not appear to alter TWA magnitude in individuals at risk of SCD.92

1.3.2.3 Myocardial Ischemia

It is generally accepted that acute myocardial ischemia has a profound effect on TWA. Experimental coronary artery occlusion significantly increases TWA on the body surface67, 98, 99 and in intracardiac recordings100 without significantly altering heart rate. In these studies, macroscopic TWA begin shortly after occlusion and are often immediately followed by VT or VF.67, 99 In humans, ischemia caused by angioplasty,98 Prinzmetal's angina59 and classic angina pectoris101 has similarly been observed to augment TWA. In fact, Verrier and colleagues102 demonstrated that a tripling in TWA magnitude occurred during transient ischemic events identified by ST segment depression on ambulatory ECG recordings. Together, these data clearly indicate that TWA can be elicited and magnified by acute ischemic events.

1.3.2.4 Antiarrhythmic Medications

Commonly used antiarrhythmic medications can also alter TWA susceptibility and magnitude but their effects appear to be quite variable depending on the drug and population tested.103 While certain class I antiarrhythmics (Na+ channel blockers) such as procainamide have been shown to decrease TWA magnitude,104 others such as flecainide have been observed to enhance susceptibility to TWA.105 Class II antiarrhythmics (β-blockers) such as metoprolol,91 esmolol92

17 and propanolol93 have been shown to consistently reduce TWA magnitude. The class III antiarrhythmics (K+ channel blockers) amiodarone and sotalol have been shown to decrease the prevalence of TWA in populations at risk of ventricular tachyarrhythmias.91, 106 However, the administration of amiodarone and sotalol has also been observed to produce large macroscopic TWA in select individuals.107, 108 The effects of class IV antiarrhythmics (Ca2+ channel blockers) on TWA are not as well studied in humans but they have been demonstrated to attenuate TWA in dogs during coronary artery occlusion.109 In summary, β-blockers have a compelling negative effect on TWA which is consistent with their well known antiarrhythmic properties. Ion channel blockers similarly appear to have the potential to reduce TWA but their inconsistent effects suggest that further investigation is required.

1.3.3 Action Potential Duration Alternans Underlie T Wave Alternans The relationship between TWA and arrhythmia can only be understood by examining the cellular and tissue level mechanisms which precipitate alternans. The overwhelming majority of evidence suggests that beat to beat alternation in the APD of ventricular myocytes underlies TWA. It has long been known that APD alternans (APDA) could occur in individual cardiomyocytes,110, 111 but the relationship with TWA was not conclusively established until an elegant set of experiments were conducted by Pastore and colleagues.112, 113 Using surface ECGs in conjunction with high resolution optical mapping of the guinea pig ventricular epicardium ex vivo, they observed that heart rate elevation produced epicardial APDA which coincided with TWA on the ECG. Not long after, a similar association between APDA and TWA was seen in excised dog hearts under long QT conditions.114 As can be seen in Figure 5, these beat to beat APD differences are mostly the result of changes in the slope of the AP plateau (phase 2) and in the onset of final repolarization (phase 3). Concurrent TWA and APDA have similarly been observed at elevated heart rates in humans,115 and are easily reconstructed in simulations.116 Furthermore, the maximum voltage difference between the alternating APs is normally 1 to 2 orders of magnitude greater than the resulting TWA in experimental112 and clinical117 settings. This affirms that the presence of microvolt TWA may actually be an indication of significant repolarization instability at the cellular level.

Figure 5. The cellular basis of T wave alternans.

Experimental examples of APDA at the myocyte level and the resulting TWA of the ECG. (A) Simultaneous APDA and TWA recorded from an excised guinea pig heart. Two consecutive beats are superimposed in each panel. No alternans is observed at a baseline heart rate of 150 bpm, but concurrent APDA and TWA are apparent at a rate of 270 bpm. Elevation of heart rate to 285 bpm increases both the APDA and TWA magnitude. (B) APDA recorded from midmyocardial and epicardial cells correspond with TWA on the transmural ECG in a canine long QT wedge preparation. The numbers within each AP indicate the APD in ms. Panel A adapted with permission from Wolters Kluwer Health: Circulation (Pastore et al.112), copyright © 1999. Panel B adapted with permission from Wolters Kluwer Health: Circulation (Shimizu and Antzelevitch114), copyright © 1999.

1.3.4 Mechanisms of Action Potential Duration Alternans

The mechanisms responsible for 2:1 alternation in APD are still not entirely clear but two popular schemas have been used to explain its existence. The restitution hypothesis suggests that alternans is created by an inherent dependence of the APD on the preceding diastolic interval created by incomplete recovery of the repolarizing ion currents. Alternatively, the Ca2+ cycling theory postulates that APDA is a result of ineffective recovery of the intracellular Ca2+ handling machinery.

1.3.4.1 Action Potential Duration Restitution

APD restitution describes the dependence of APD on the previous DI. It was first implicated as a potential mechanism for APDA in the late 1960s.118 The restitution response dictates that a reduction in DI produces a shorter APD, while an increase in DI produces a longer APD. This is considered an adaptive mechanism to preserve diastole and allow for ventricular filling at rapid heart rates.103 The restitution effect is attributed to insufficient recovery of the major voltage 119 sensitive ion currents that are active during repolarization: ICaL, IKr, IKs and Ito. Although all these currents likely play a role in APD restitution, recent simulations by Decker et al.120 suggest that ICaL, IKs and Ito are primarily involved. Experimentally, restitution is measured by plotting APD versus DI while gradually increasing heart rate.121 The resulting “restitution curve” can be theoretically used to determine how APD will adapt to any change in heart rate for the specific subject from which it was constructed.

Nolasco and Dahlen118 applied a cobweb diagram to the restitution curve to elegantly demonstrate how self perpetuating APDA could be generated by APD restitution as shown in Figure 6. While at a contest CL, an alternating sequence can be initiated by a premature stimulus. The early beat, which by definition has a short DI, will also have a short APD owing to restitution. Because CL remains constant, the subsequent DI will be long and restitution will cause the following APD to be long as well. The next DI is short because of the preceding long APD and the process repeats. These long-short-long APD oscillations will either persist or dissipate depending on the slope of the restitution curve for the initial CL. A steep slope (≥1) will create stable alternans, while a shallow slope (<1) will cause the alternans to dampen and return to the original equilibrium point. Indeed, simulated flattening of the restitution curve has been shown to prevent the development of APDA in ventricular myocyte models.122 Furthermore,

Figure 6. Action potential duration restitution as a mechanism of action potential duration alternans.

In the top panel, cobweb diagrams are applied to the restitution curve to demonstrate the effects of a premature stimulus (*) on APD and DI at (A) a steep restitution slope (>1) and (B) a shallow restitution slope (<1). The open circle indicates the initial APD and DI. The dashed lines represent the CL (CL = APD + DI) which is constant before and after the premature stimulus. In the bottom panel, the APs for the (A) steep and (B) shallow scenarios are illustrated. (A) When the restitution slope is steep, the short DI produced by a premature stimulus (*) causes a significant shortening of the associated APD (1). Because the CL remains constant, the next DI is long which generates a long APD (2). The long APD causes the subsequent DI to be short which produces a short APD (3). This process repeats and self sustaining alternation is established. (B) When the restitution slope is shallow, the short DI produced by a premature stimulus (*) has little affect on the following APD. The minor alternations in APD quickly dampen and return to the initial APD and DI. Figure adapted with permission from Elsevier: Journal of Molecular and Cellular Cardiology (Myles et al.123), copyright © 2008.

21 pharmacological agents which flatten the restitution curve have also been shown to reduce arrhythmia risk in experiments with pig hearts.124 Whether or not this antiarrhythmic effect is directly due to the prevention of APDA has not been explored.

Though the restitution hypothesis is theoretically sound and explains the rate dependant nature of TWA, as it is only engaged at the short DIs associated with fast heart rates, it may be overly simplistic and is not well supported experimentally. Pruvot et al.125 and Goldhaber et al.126 used whole hearts and isolated cardiomyocytes, respectively, to demonstrate that alternans could originate at rates where the slope of the restitution curve was <1.When cardiac memory effects are incorporated into ventricular myocyte simulations, an APD restitution slope >1 becomes even less reliable for predicting the appearance of alternans.127 In humans, Narayan and colleagues115 used monophasic action potential recordings to show that APDA and simultaneous TWA arise at heart rates were the APD restitution slope is not steep (<1) and that the presence of a steep slope (≥1) is not predictive of a positive TWA test. Furthermore, the APD restitution slope maxima and number of individuals with a steep restitution slope were not significantly different between individuals with impaired systolic dysfunction and normal subjects. Generally, APD restitution is more readily able to account for APDA at very fast heart rates where the restitution slope is steep, than it is able to explain alternans at slower and more clinically relevant heart rates (≤110 bpm) where the restitution curve is flat.

1.3.4.2 Ca2+ Cycling

Intracellular Ca2+ cycling has been more recently implicated as the primary cause of APDA.125, 128 As previously discussed, myocyte contraction and relaxation is facilitated by the release and reuptake of Ca2+ from the SR by RyR2 and SERCA2a, respectively. Under normal conditions at resting heart rates, the release of Ca2+ from the SR equals the uptake of Ca2+ into the SR.129 The Ca2+ cycling hypothesis states that APDA will occur once heart rate exceeds the ability of the Ca2+ cycling machinery to maintain beat to beat Ca2+ homeostasis.103 Any impairment of Ca2+ handling will theoretically reduce the heart rate at which APDA appears. Thus the heart rate dependant nature of TWA is maintained under this premise.

It is important to note that the relationship between APD and the Ca2+ transient is 130 2+ bidirectional. The AP controls transmembrane Ca fluxes via voltage sensitive ICaL channels and electrogenic NCX channels which in turn influences SR Ca2+ loading and release.

2+ Conversely, cytosolic Ca released from the SR feeds back on the AP via ICaL and NCX which 2+ 2+ also happen to be Ca sensitive. Although other Ca sensitive currents, such as Ito2, can modulate the Ca2+ voltage relationship, their effect is far less pronounced.131 During alternans the Ca2+ transient can either be positively or negatively coupled to the APD. When the large Ca2+ transient is associated with a long APD, known as electromechanical concordance or “positive coupling”, increased NCX activity predominates over decreased ICaL function. Alternatively, when the large Ca2+ transient is associated with the short APD, known as electromechanical discordance or “negative coupling”, the inactivation of ICaL outweighs increased NCX activity.

There is considerable experimental evidence in support of the Ca2+ cycling hypothesis. Chudin et al.132 was the first to demonstrate that the rapid heart rates that elicit both APDA and Ca2+ transient alternans under current clamp conditions are also able to generate Ca2+ transient alternans under AP clamp conditions (where the AP waveform is held constant) without APDA. In intact canine hearts, Wilson and colleagues133 reported a significant correlation between APDA magnitude and Ca2+ alternans magnitude. Introducing heart failure to the canine model significantly lowered the heart rate threshold for both Ca2+ alternans and APDA to equal levels. Most importantly, Ca2+ alternans was consistently observed to occur prior to or simultaneous with APDA in both the normal and heart failure groups. These experiments not only demonstrate that Ca2+ alternans can occur independent of APDA but also implicate that APDA can be driven by Ca2+ alternation in normal hearts and in the disease state.

Moreover, APDA has been specifically associated with abnormal SR Ca2+ loading and release. Protein immunoblot experiments reveal that the regions of ventricular tissue most prone to APDA are those with reduced expression of RyR2 and SERCA2a.134 Pruvot et al.125 used optical mapping with Ca2+ and voltage sensitive dyes to simultaneously record the Ca2+ transient and APD from excised normal guinea pig hearts. They observed that APDA originated and spread from the regions with the slowest time course for cytosolic Ca2+ uptake rather than the regions with the steepest restitution slopes. Conversely, over expression of SERCA2a can suppress APDA at rapid pacing rates in isolated ventricular myocytes.135 These experiments implicate insufficient SR loading via SERCA2a as the primary mechanism of Ca2+ alternans and APDA. On the other hand, Diaz et al.136 showed that pharmacological inhibition of RyR2 can promote Ca2+ alternans and Picht et al.137 observed that beat to beat SR Ca2+ content does not always

23 fluctuate during Ca2+ alternans. These studies alternatively suggest incomplete Ca2+ release via RyR2 as the mechanism of Ca2+ alternans but did not directly demonstrate the effects on APD.

1.3.5 Action Potential Duration Alternans in the Ventricular Myocardium

APDA in a single myocyte cannot obviously account for the arrhythmogenic properties of TWA. Therefore, the behaviour of APDA at the tissue level must be considered to understand the close association between TWA and arrhythmia. Whole heart experiments112, 113 reveal that APDA does not occur uniformly across the myocardium. Normally, when APDA first develop within the myocardium, it is spatially uniform such that all cardiomyocytes alternate in the same long- short-long fashion.138 Although these “concordant alternans” signify an increase in the temporal dispersion of repolarization, they are not necessarily arrhythmogenic.122, 139 However, concordance does typically precede a more malignant form of APDA known as spatially "discordant alternans".112 Discordance occurs when one area of myocardium begins to alternate out of phase from another area such that the APD in one region alternates long-short-long while the APD in another region alternates short-long-short.140 The out of phase regions are separated by "nodal lines" at which there is no alternation in APD. In addition to temporal dispersion of repolarization, discordant APDA produces considerable spatial dispersion of repolarization. The effects of concordant and discordant APDA on APD dispersion are illustrated in Figure 7.

Discordant APDA are said to have the potential to create larger TWA magnitudes than concordant APDA.128, 139 This hypothesis is supported by the results of modelling study previously conducted by our group.116 We simulated APDA in a 257-node heart model and the forward solution was used to obtain the unipolar potentials at 300 points on the body surface. Regional variations of concordant and discordant APDA of 4 ms were modelled and the resulting body surface TWA magnitudes were calculated as displayed in Figure 8. Discordant APDA consistently produced larger maximum TWA magnitudes than concordant APDA, from 31 µV to 87 µV compared to 15 µV to 45 µV. Although this has yet to be verified with experimental data, it does appear that discordance may be more likely to produce large measurable TWA on the body surface than concordance.

Figure 7. Comparison of spatially concordant and discordant action potential duration alternans.

(A) Two successive action potentials from two sites in a simulated two-dimensional cardiac tissue sheet during concordant APDA (left) and discordant APDA (right). At a pacing rate of ~270 bpm the APDA are spatially concordant with APD alternating long-short-long at both sites. At a pacing rate of ~330 bpm the APDA are spatially discordant with APD at site 1 alternating short-long-short and APD at site 2 alternating long-short-long. (B) The spatial distribution of APD across the entire tissue sheet for each beat. During concordance, APD is uniform throughout the sheet. During discordance, the APD at the top of the sheet (site 1) is out of phase with the APD at the bottom of the sheet (site 2). Separating the out of phase regions is a nodal line (white) where there is no APDA. (C) The dispersion of APD across the tissue sheet. Concordance creates no APD dispersion because there is no difference in APD across the entire sheet. Discordance creates marked dispersion of APD (and refractoriness) that is most pronounced near the border of the nodal line (black region). (D) The ECG generated by the tissue sheet. Although there are subtle TWA created by the concordant APDA, they are minute in comparison to the macroscopic TWA generated by the discordant APDA. Figure adapted with permission from Wolters Kluwer Health: Circulation Research (Weiss et al.128), copyright © 2006.

Figure 8. Comparison of T wave alternans generated by concordant and discordant action potential duration alternans.

(A) Simulated intracardiac APDA from a 257-node heart model were used to project unipolar potentials onto 300 points on the body surface. TWA magnitudes were calculated at each point and used to construct body surface isoalternans plots. (B) Isoalternans plots of the body surface generated by concordant APDA of 4 ms localized to the apex, base, anterior wall, posterior wall, LV, RV, endocardium or epicardium of the heart. (C) Isoalternans plots of the body surface generated by discordant APDA of 4 ms between the apex and base (shown in A), anterior and posterior wall, LV and RV, or endocardium and epicardium. Although the spatial pattern of TWA remains fairly consistent between the concordant and discordant APDA models, the discordant TWA magnitudes are roughly twice that of the concordant TWA magnitudes. Figure adapted with permission from Elsevier: Heart Rhythm (Selvaraj et al.116), copyright © 2009.

1.3.6 Mechanisms of Discordant Action Potential Duration Alternans

Though it is not entirely clear why regions of myocardium with concordant APDA will spontaneously switch phase and become discordant, three basic mechanisms of discordance have been proposed.123 First, intrinsic heterogeneities in APD and APD restitution may create enough dispersion of repolarization to create discordance. Second, heterogeneity in Ca2+ handling may produce spatially discordant APDA in a similar fashion. Third, dynamic modulation of repolarization by CV restitution can promote discordance in the absence of tissue heterogeneity. In addition, a timely trigger such as an increase in heart rate or an ectopic beat is typically required to initiate the cascade of events leading to discordance. It is also important to note that these mechanisms are not necessarily mutually exclusive and may work in unison to facilitate spatially discordant APDA. Unfortunately, the evidence supporting these mechanisms is only theoretical and experimental, as these scenarios have yet to be studied in the human ventricular myocardium.

1.3.6.1 Heterogeneity in Action Potential Duration and Action Potential Duration Restitution

Differences in APD and APD restitution are created by variable distribution of ion channels in cardiomyocytes from different ventricular regions.141 These heterogeneities are not random from myocyte to myocyte but are typically aligned in gradients throughout the ventricles. For example, in the human ventricles, APD gradients are arranged from left ventricle (LV) to right ventricle (RV), apex to base and endocardium to epicardium.142 Because electrical propagation is not instantaneous to all areas, these gradients are likely present to provide uniform recovery across the ventricles. The existence of such gradients can understandably produce regional variation in the magnitude of APDA. However, these gradients have also been suggested to promote changes in the phase of alternans.

By definition, myocytes with differences in baseline APD and APD restitution properties will be expected to react differently in response to the same DI. If these differences are great enough, they may result in discordance at elevated heart rates. In the original guinea pig model of alternans, all that was required to elicit spatially discordant APDA was the presence of concordant APDA and an increase in pacing rate.112 In this study, discordance was consistently observed to occur between the apex and the base of the LV epicardium, which happened to

27 correspond with the underlying APD restitution gradient.143 Moreover, this occurred irrespective of the pacing site suggesting the pattern of discordance did not rely on the direction of conduction but was inherent to the myocardium. Transmural heterogeneity in APD restitution properties has similarly been implicated in the genesis of discordant APDA in the in vivo canine ventricle.144 In these experiments, discordance arose between the epicardial regions with a long baseline APD and steep restitution, and midmyocardial sites with a short baseline APD and shallow restitution. More recently, it has been suggested that temporal variations in APD restitution may combine with spatial variations in APD restitution to promote discordant APDA.145 Just as the APD restitution curve can vary between regions, the APD restitution curves within the same myocyte may be markedly different between the alternating beats during APDA.146 In this case, a critically timed premature stimulus can cause a switch in the phase of alternans in regions where there is only small beat to beat variation in APD restitution, while not affecting the phase of regions where there is large beat to beat variation in APD restitution.145

Although these experiments demonstrate that stable discordant APDA can be created by APD restitution heterogeneity alone, they typically require pacing at extremely rapid heart rates. Unfortunately, alternans at high heart rates are not clinically relevant because individuals at risk of SCA typically develop TWA at rates below 110 bpm.73, 86 Normally, intrinsic variation in repolarization properties is attenuated by electrotonic coupling.147, 148 Coupling occurs because the repolarizing ion currents of one myocyte are able to directly influence neighbouring myocytes via gap junctions. Therefore, any tendency for myocytes to alternate APD in opposing fashion will be resisted by the coupling effect. In contrast, intercellular uncoupling allows myocytes to act independently and readily reveals underlying heterogeneity in APD and APD restitution.149 Pastore and Rosenbaum113 introduced an insulating scar to the guinea pig model of alternans and observed that the presence of the structural barrier lowered the heart rate threshold for discordance. Importantly, the scar was positioned such that it divided the underlying apex to base APD restitution gradient. In a simulation study where the conditions of a structural barrier were duplicated, the mechanism of discordance was shown to be directly related to uncoupling of tissue with dissimilar APD restitution properties.150 Reduced coupling from abnormal gap junction arrangement and function has also been suggested to facilitate discordance. Drugs known to enhance gap junctional conductance have been shown to suppress ischemia induced discordant APDA.151 Thus, it appears that conditions which unmask underlying repolarization

28 heterogeneity through either intercellular uncoupling or reduced coupling can promote discordance.

1.3.6.2 Heterogeneity in Ca2+ Handling Properties

Ca2+ cycling properties are similarly found to be distributed heterogeneously across the myocardium. Experimental examination of the LV has revealed both apicobasal152 and transmural153 gradients in intracellular Ca2+ handling components. Interestingly, these are the same gradients as those associated with APD which suggest that these heterogeneities may be interrelated. However, if Ca2+ cycling is primarily responsible for concordant APDA, it is reasonable to expect that heterogeneity in Ca2+ handling properties between myocytes may also be primarily responsible for the genesis of discordance. In canine and guinea pig ventricles, spatial variation in Ca2+ handling ability has been linked to regional susceptibility to APDA.134, 153 These regional variations in Ca2+ cycling properties may promote spatially discordant APDA in a similar manner to discordance via spatial variation in APD and APD restitution.

Simulations by Sato et al.154 alternatively suggest that differential coupling between Ca2+ and APD may facilitate spatially discordant APDA. Theoretically, if some regions of myocardium were predisposed to “negative coupling” while others were predisposed to “positive coupling” 2+ between the Ca transient and APD, due to variable expression of NCX and ICaL, then these regions would more readily be able to alternate out of phase. Unlike the other major repolarizing ion species, intercellular diffusion of Ca2+ is limited155 and intercellular coupling will likely have little effect on maintaining synchronization in Ca2+ handling between cells. Therefore, if Ca2+ handling drives APDA, it may be quite simple for Ca2+ cycling to become regionally dyssynchronous and for discordance to develop. This has yet to be fully explored in an experimental setting.

1.3.6.3 Conduction Velocity Restitution

Theoretical studies have shown that tissue heterogeneity is not necessarily required to cause discordance.122, 139 A simple classical mechanism, known as CV restitution, can produce discordant APDA in homogenous tissue. CV restitution, like APD restitution, is the adaptation of CV in response to the previous DI. CV changes little at longer DIs, but at very short DIs CV can 156 be markedly reduced due to the incomplete recovery of INa from inactivation. Therefore,

29 unlike the APD restitution curve, the CV restitution curve is normally quite flat until it suddenly drops off at very short DIs. In further contrast to APD, CV properties are distributed fairly uniformly throughout the ventricle under normal conditions.157

Computer modelling studies demonstrate that engagement of CV restitution at very fast heart rates or after a premature beat will cause concordant APDA to become discordant between sites closest to and farthest from the pacing stimulus.122, 139 Figure 9A illustrates this concept. In a simulated tissue cable with normal CV restitution properties, a small increase in pacing rate during concordant APDA produces a DI after a long APD that is short enough to engage CV restitution.139 The resulting slowed conduction causes DI to increase with distance from the pacing site. Because of APD restitution, the longer DIs will also have subsequently longer APDs. This process self amplifies over the following beats until the previously "short" APDs farthest from stimulus become longer than the previously "long" APDs that preceded them, whereas as there is no phase change at the sites closest too stimulus. In this way, discordance is established between the top and the bottom of the tissue cable. Alternatively, engagement of CV restitution at slower heart rates by a critically timed ectopic can result in the immediate development of discordant APDA through a similar process as shown in Figure 9B.138 In either scenario, CV restitution creates an inhomogeneity in DI which causes myocytes from different regions to operate on different portions of their APD restitution curves. This mechanism is supported by two-dimension tissue models122, 139 and observation of discordant APDA within canine hearts in vivo.144

Additionally, alterations in CV can either promote or discourage the development of discordance. Qu et al.122 used a homogenous two-dimensional tissue model to demonstrate that discordance by means of CV restitution could be intensified or attenuated by changing the shape of the CV restitution curve. In this study, broadening of the curve (CV slowing begins at longer DIs) produced spatially discordant APDA at reduced heart rates, while narrowing of the curve (CV slowing begins at shorter DIs) prevented discordance all together. These results are experimentally supported by the occurrence of discordant alternans at baseline heart rates during ischemia,158 where CV is known to be considerably slowed.159 Pharmacological agents that enhance gap junctional conductance are also known to prevent discordance.151 Aside from attenuating APD heterogeneities as previously discussed, improved coupling also increase CV160 which may alternatively explain the decreased susceptibility to discordance. CV slowing caused

Figure 9. Conduction velocity restitution as a mechanism of discordant action potential duration alternans.

(A) Discordant APDA induced by CV restitution in a one-dimensional tissue cable. APs at 75 positions from the top to the bottom of the cable are displayed. Stimulus was applied at a rate of ~195 bpm at the top of the cable. Concordant APDA are initially present (before break) but transition into discordant APDA over time (after break). Discordance occurs because the DI after the long APD is so short that it engages CV restitution at the top of the cable. The slowed conduction increases DI as the impulse travels away from the site of stimulus which lengthens the subsequent APD via APD restitution. This process repeats until the sites farthest from stimulus become discordant from the sites closest to stimulus. (B) Diagrammatic illustration of CV restitution producing discordance in cardiac tissue. Activation (arrows) normally proceeds from site 1 to site 2 without conduction slowing. However, an early beat (*) at site 1 after a long APD will engage CV restitution (wavy line). The delay in conduction causes a long DI at site 2 even though the previous APD was long. The next APD is also long because of APD restitution and discordance is established. Panel A adapted with permission from John Wiley and Sons: Journal of Cardiovascular Electrophysiology (Watanabe et al.139), copyright © 2001. Panel B adapted with permission from Springer: Electrical Diseases of the Heart (Oshodi et al.119), copyright © 2008.

31 by structural heterogeneity, rather than electrical remodelling, has also been implicated as a mechanism of discordance in tissue models.161 In summary, CV restitution may be a highly potent mechanism of discordant APDA in diseased myocardium where CV is pathologically slowed due to either electrical or structural remodelling.

1.3.7 Role of Structural Barriers in Promoting Discordant Action Potential Duration Alternans

As briefly alluded to in the preceding sections, structural barriers have the capacity to facilitate spatially discordant APDA in animal experiments and simulations.113, 150, 161 In these studies, both the location and composition of the barrier appear to be important factors in determining the discordance promoting potential. Furthermore, the very mechanism of discordance can differ depending on the nature of the barrier and the substrate that surrounds it.

Pastore and Rosenbaum113 were the first to examine the effects of a structural barrier on APDA. This experiment is illustrated in Figure 10A and Figure 10B. A dense insulating scar was introduced to the isolated epicardium of an explanted guinea pig heart. Importantly, the structural barrier was specifically placed perpendicular to the intrinsic apex to base APD gradient. The presence of the barrier lowered the heart rate threshold for discordance by nearly 70 bpm. This occurred regardless of the pacing site and without significant alterations in the beat to beat activation sequence. The authors also noted that the heart rate threshold for TWA was similarly decreased, although the exact data was not provided. They proposed that the observed reduction in the discordance and TWA thresholds was due to the decoupling of tissue with inherently different APD properties. However, the limitations of the animal model did not allow this to be directly demonstrated.

Krogh-Madsen and Christini150 reproduced the experiments of Pastore and Rosenbaum113 in a simulated two-dimensional tissue sheet to determine if uncoupling was the actual mechanism of + discordance. K conductances (Ito and IKs) were regionally adjusted in order to replicate the apex to base APD gradient found in the guinea pig heart. The structural barrier was modelled as a rectangular piece of unexcitable tissue and positioned in the middle of the sheet such that it divided the APD gradient. Discordant APDA was observed to occur when the pacing rate was elevated to 250 bpm, but did not occur in tissue sheets where a barrier was not included. The precise mechanism of discordance is illustrated in Figure 10C. The initial stimulus at 250 bpm

Figure 10. Discordant action potential duration alternans induced by an insulating barrier in the guinea pig model.

(A) A dense scar was placed perpendicular to the intrinsic APD gradient of a Langendorff perfused guinea pig heart. APs within the 1.5 x 1.5 cm grid were mapped using voltage sensitive dies and ECGs were recorded from the effluent surrounding the heart. Stimuli was applied at the top right of the mapping region (square pulse symbol). (B) Optical mapping of activation (DEPOL), APD and repolarization (REPOL) from two successive beats in the absence (left) and presence (right) of a structural barrier. When paced at ~285 bpm, discordant APDA developed in the presence of the structural barrier but not in control. Although activation is quite uniform in both scenarios, beat to beat repolarization and APD are significantly altered by the barrier. Note that discordance primarily develops on opposing sides of the barrier. The discordant APDA also produces macroscopic TWA on the ECG. (C) A simulation replicating the conditions of the guinea pig experiments which illustrates the precise sequence of events that leads to discordance. The panels display the membrane voltages across the tissue sheet at the indicated time after the initial stimulus. On the first beat, repolarization is delayed on the left side of the barrier (150-250 ms) where the intrinsic APD is longest. On the second beat, APD restitution causes the left side of the panel to now have a shorter repolarization time than the right side (330-390 ms) and discordance is established. Panel A adapted with permission from Wolters Kluwer Health: Circulation Research (Pastore and Rosenbaum113), copyright © 2000. Panel B adapted with permission from Elsevier: Biophysical Journal (Krogh-Madsen and Christini150), copyright © 2007.

33 propagates evenly up the sheet but recovery occurs early on the right side of the barrier because APD is intrinsically shortest there. When the next action potential is initiated, the DI on the left side of the sheet is short since recovery has just finished, while the DI on the right side is long since recovery has been complete for over 30 ms. Because of APD restitution, the left side of the sheet, which previously had a long APD, now has a short APD and the right side of the sheet, which previously had a short APD, now has a long APD. In this way, APD begins to alternate out of phases on opposite sides of the barrier. In the absence of a barrier, this was not observed to occur because electrotonic coupling created greater homogeneity in APD. Together, these experiments revealed cellular uncoupling by a barrier as a potent mechanism of discordance.

Alternatively, small nonuniformly distributed structural barriers can encourage discordant APDA in the absence of electrical heterogeneity. Engelman et al.161 modelled diffuse structural heterogeneities similar to patchy myocardial fibrosis in a simulated two-dimensional ventricular tissue sheet with homogenous electrical properties as shown in Figure 11. Discordance was observed to occur at lower pacing rates in the tissue sheets with structural heterogeneities than in control tissue. At faster rates, APDA also became discordant in control but there were considerably more out of phase regions present in the tissue with structural heterogeneities. The early onset of discordant APDA was facilitated by tortuous "zigzag" conduction through the region of the discontinuities. Increased tortuosity produced greater variability in CV which created local conduction delays that promoted discordance in a manner similar to the engagement of CV restitution. At slower pacing rates the increased tortuosity had little effect on the activation pattern but as rate increased so did the spatial and temporal variation in activation and thus DI. The spatial variations in DI gave rise to spatial variation in APD which in turn lead to discordant APDA. This study demonstrates that patchy fibrosis has the potential to promote discordance without intrinsic variation in APD and APD restitution properties.

Although structural barriers can clearly facilitate discordant APDA in simulations and animal models, it has yet to be determined if this is also true in the human heart. However, patients with structural heart diseases are more likely to be TWA positive162 and have greater TWA magnitudes71 than healthy individuals. The presence of TWA in these individuals is also a significant predictor of arrhythmia risk,64 suggesting that arrhythmogenic discordant APDA may be particularly prevalent within this population. It is possible that these individuals have a

Figure 11. Discordant action potential duration alternans induced by diffuse structural heterogeneities in a simulated tissue sheet.

(A) Unexcitable diffuse structural heterogeneities (white voids) were modelled in the center of a 14 x 14 mm tissue sheet with homogenous electrical properties. Stimulus was applied near the top of the sheet (square pulse symbol). The membrane voltage 30 ms after an initial stimulus is displayed. (B) The upper panel illustrates tortuosity (a measure of complexity of the local conduction pathways) within the structurally heterogeneous region. The lower panel relates CV to tortuosity. Although median CV was relatively similar, CV variability significantly increased with tortuosity. (C) Three successive beats during discordant APDA. There is large beat to beat variability in activation (upper panels) within and below the region of the structural discontinuities. The spatial variation in activation creates variation in DI that results in multiple regions with discordant APDA (lower panels). Note that the temporal activation pattern is fairly homogenous before it enters the region of the structural discontinuities. Figure adapted with permission from Wolters Kluwer Health: Circulation Arrhythmia and Electrophysiology (Engelman et al.161), copyright © 2010.

35 predisposition to TWA and discordant APDA due to the presence of structural barriers in the form of myocardial scar.

1.3.8 Discordant Action Potential Duration Alternans as a Substrate for Arrhythmias

The seminal studies by Pastore et al.112, 113 revealed discordance to be a novel mechanism by which repolarization alternans could initiate tachyarrhythmia. They showed that discordant APDA produced marked spatial dispersion of APD, and hence dispersion of refractoriness, which facilitated conduction block and reentry in the guinea pig model. Block typically occurred at the boundary of the nodal lines, where the repolarization gradient was observed to be steepest. Figure 12 illustrates how conduction block and reentry can develop from an ectopic beat or heart rate increase in the presence of discordance. In this scenario, an early impulse which begins in a region with short APD will proceed to the nodal line and be blocked as it attempts to enter the region with long APD that has yet to recover. Conduction will be forced to proceed laterally to the block until the region of long APD is able to repolarize. Finally, when the wavefront is able to enter the region with long APD, it will proceed back toward the area of block and reentry will be completed. In this way, discordance magnifies small inherent physiological heterogeneities in APD to create pathophysiological heterogeneities in APD.140

In the aforementioned experiments112, 113 and subsequent simulations122, 150 of APDA, discordance is always seen to precede VF or VT. However, the development of VF versus VT largely depends upon the physical substrate. In the presence of a structural barrier, such as myocardial scar, nodal lines “lock” themselves to the anatomical anomaly.113, 150, 161 This results in monomorphic VT more often than VF because the reentrant circuit has a permanent anchor to fix itself upon.113, 150 In contrast, discordance that occurs in structurally homogenous tissue almost always results in VF.112

1.4 Cardiomyopathy The cardiomyopathies are a diverse group of structural heart diseases that involve an adverse remodelling of the myocardium that often leads to heart failure.163 The deterioration in cardiac function is due to either impaired ventricular contraction, known as systolic dysfunction, inadequate ventricular filling, known as diastolic dysfunction, or a combination of both. In addition to being vulnerable to heart failure, cardiomyopathy patients are also at high risk of

Figure 12. Discordant action potential duration alternans as a mechanism of reentry.

(A) APs at myocardial sites 1 and 2 during discordant APDA. Activation (arrows) proceeds normally from region 1, where APD alternates long-short- long, to region 2, where APD alternates short-long-short, until it is interrupted by a premature beat (asterisk) that produces VF. The gray bars indicate the dispersion of repolarization between the two sites. (B) The spatial distribution of APD created by the fourth sinus beat, immediately preceding the ectopic stimulus. The premature beat (asterisk) that occurs in region 1 after the short APD blocks when it propagates across the nodal line (white) and into region 2 where the APD is long. However, the stimulus continues to propagate laterally to the region of block until region 2 has recovered. The stimulus then returns to the site of block in a retrograde manner and reentry is initiated. Panel A adapted with permission from Springer: Electrical Diseases of the Heart (Oshodi et al.119), copyright © 2008. Panel B adapted with permission from Wolters Kluwer Health: Circulation Research (Weiss et al.128), copyright © 2006.

SCD.38 The three most common cardiomyopathic etiologies are ischemic cardiomyopathy (ICM), dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM).

ICM affects approximately 1% of all adults, making it by far the most common form of cardiomyopathy.164 ICM is characterized by reduced LV contractile function due to coronary artery disease and almost always involves prior myocardial infarction. The observed systolic dysfunction is primarily a result of insufficient myocardial perfusion.165 Within ICM populations, SCA accounts for up to 50% of all deaths166 with an annual incidence rate reported to be as high as 6%.167 Due to its prevalence and association with a heightened arrhythmia risk, it is unsurprising that ICM causes more SCDs per year than any other underlying substrate.38 However, not all individuals with ICM are at equal risk of SCA. Clinical studies suggest that the degree of systolic dysfunction in ICM helps to stratify risk. In a clinical setting, systolic function is most commonly assessed using the LV ejection fraction (LVEF), which is the percentage of blood that is expelled from the LV in a single contraction. Healthy individuals typically possess an LVEF in the range of 55% to 70%, while systolic dysfunction is defined by an LVEF less than 50%.168 A recent multicentre trial involving 4122 ICM patients, revealed that individuals with an LVEF between 30% and 40% were at an increased of SCD compared to those with an LVEF >40%, while those with an LVEF <30% were at even greater risk.169

Nonischemic DCM refers to systolic dysfunction due to an often unexplainable (idiopathic) enlargement of the LV.170 Although the diameter of the LV is significantly increased in DCM, the wall thickness remains relatively unchanged. Thus the stretched myocardium has less elastic recoil and ventricular pumping function is reduced. DCM is the second most common type of cardiomyopathy with an estimated prevalence of 0.4 per 1000 in the general population.171 Nevertheless, individuals with DCM represent approximately 10% of the total SCD burden38 with a relative annual risk near 3%.172 The degree of systolic dysfunction in DCM is not as conclusively linked with SCA risk as it is in ICM. However, the MACAS trial found an LVEF <30% to be the only significant predictor of SCD amongst 343 DCM patients.173

The third most common form of cardiomyopathy is HCM, a frequently asymptomatic genetic disorder that is estimated to affects 0.02% of individuals.171 HCM involves abnormal myocardial thickening and myofibril disarray, which predominantly affects the ventricular septum and LV wall.163 Unlike ICM and DCM, the reduced ventricular function is initially the result of diastolic

38 dysfunction but as the disease progresses it may lead to reduced systolic function as well. Diastolic dysfunction occurs because hypertrophy hinders LV filling by decreasing LV cavity size and increasing myocardial stiffness. HCM patients have a lesser but appreciable risk of SCA compared to individuals with ICM or DCM. SCD accounts for the majority of deaths in HCM but the general mortality rate due to SCA is less than 1%.174 However, HCM is the leading cause of SCD in children and young adults with an annual incidence of 4% to 6%.175 Because HCM patients normally have preserved contractile function, LVEF is less relevant for identifying those at risk of SCD.

1.4.1 Myocardial Fibrosis in Cardiomyopathy

Structural remodelling, which is common to all types of cardiomyopathy, often involves the development of myocardial fibrosis. Fibrosis, or scarring, typically entails collagen deposition and fibroblast proliferation.176 In general, scar can manifest as either interstitial fibrosis, where collagen deposition occurs without the loss of myocytes, or replacement fibrosis, where collagen supplants necrotic myocytes.177

In cardiomyopathy patients, fibrosis can be visualized with high resolution using late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) imaging. LGE CMR involves the administration of a gadolinium contrast agent and a specially devised inversion recovery magnetic resonance imaging sequence.178 Since gadolinium is unable to cross intact cellular membranes, regions of fibrosis support a greater volume of distribution due to larger extracellular space and reduced myocyte membrane integrity.179, 180 Furthermore, decreased capillary density in fibrotic tissue prolongs the washout of gadolinium contrast agents.179 Because the presence of gadolinium amplifies CMR signal intensity (SI), the abnormal contrast handling characteristics of the fibrotic myocardium allow it to be readily distinguished from normal myocardium. Histological evaluation reveals that dense replacement fibrosis appears white, interstitial fibrosis or diffuse replacement fibrosis appears grey, and normal myocardium appears black on LGE CMR (Figure 13A).181, 182 The high intensity white regions and intermediate intensity grey regions are customarily referred to as the scar “core” and “gray zone”, respectively.183, 184

There is currently no gold standard for quantifying LGE CMR based scar. The two most common approaches for measuring core and gray zone are the full width at half maximum

Figure 13. Late gadolinium enhanced cardiac magnetic resonance imaging of myocardial fibrosis.

(A) Comparison of histology (left) to high resolution LGE CMR (right) in a short axis slice from the base of an infracted rat heart. Masson trichrome staining causes regions of collagen containing fibrosis to appear blue in the histological slice, while LGE causes fibrosis to appear white on the corresponding CMR image. The red insert depicts a region of dense replacement fibrosis that was classified as “core” on lower resolution LGE CMR image. The yellow insert depicts a region of diffuse interstitial fibrosis that was classified as “grey zone” on lower resolution LGE CMR image. (B) LGE patterns specifically associated with ICM, HCM and DCM. The ICM patient displays classical LGE enhancement of the subendocardium caused by a prior myocardial infarction. The HCM patient displays multiple LGE foci, including a region of less intense LGE near the inferior RV insertion point (bottom). The DCM patient displays characteristic LGE in the midwall of the ventricular septum. Panel A adapted with permission from Wolters Kluwer Health: Circulation Cardiovascular Imaging (Schelbert et al.181), copyright © 2010.

(FWHM) and standard deviation SI thresholding techniques. FWHM classifies core as regions of SI ≥50% of the maximum scar SI and gray zone as areas greater than the maximum SI from a region of normal myocardium but less <50% of the maximum scar SI.183 The standard deviation technique defines core and gray zone according to a prespecified number of standard deviations above the mean SI from a region of normal myocardium. For example, Yan et al.185 defined core as regions with SI >3 standard deviations above the normal myocardium and gray zone as regions with SI between 2 to 3 standard deviations above the normal myocardium. On the other hand, some studies simply use a trained observer to visually asses and delineate the scar regions.186, 187 Furthermore, not all studies make the distinction between core and gray zone.188, 189 In these cases, the method used to define the scar region is often equivalent to the total scar (core + gray zone) in studies that identify both core and gray zone.185 No matter the quantification method, core should generally be comprised of dense collagenous nonconductive tissue, whereas gray zone should contain enough connected bundles of viable myocytes to permit conduction.181, 182

In humans, LGE CMR and histological assessment have revealed that the scar consistency and distribution can be quite variable depending on the severity and type of cardiomyopathy (Figure 13B). The vast majority of ICM patients have scarring due to infarction in the region of the coronary arteries.190 The fibrosis typically begins at the subendocardium and extends outward toward the epicardium. The transmural extent of the infarction is dependent on the duration of the ischemic event.191 Examination of explanted hearts from patient with ICM reveals their scar to be primarily comprised of concentrated replacement fibrosis surrounded by diffuse interstitial fibrosis intermingled with smaller pockets of replacement fibrosis.192 Approximately 30% of DCM patients have been found to have ventricular midwall fibrosis, which is a linear scarring of the septum that begins in the midwall and extends toward the endocardium and epicardium.190 Necropsy results reveals scar in DCM patients to be a combination of both replacement and interstitial fibrosis.193 Up to 80% of HCM patients exhibit scar in clinical studies.194 Aside from fibrosis often being observed at the RV insertion points, scarring in HCM patients occurs at irregular locations throughout the LV myocardium.195 Histological data suggests that the majority of scar in HCM involves focally increased regions of interstitial fibrosis and not complete replacement fibrosis.196

Clinical studies using LGE CMR have independently linked delayed enhancement to increased arrhythmia risk and SCD in ICM,183-185, 197 DCM187, 189 and HCM186, 188, 198 populations as shown in Table 1. In ICM, the extent of gray zone scar has specifically been associated with greater likelihood and frequency of ventricular tachyarrhythmias,183, 184 cardiovascular events197 and cardiac mortality.185 Unlike ICM, LGE CMR evaluations of DCM and HCM have not examined the prognostic utility of scar core separately from gray zone. However, there are some studies that have evaluated the relation between total scar and arrhythmia. In DCM, the mere presence of midwall fibrosis is predictive of cardiovascular events189 and cardiac mortality.187 In HCM populations, the extent of total scar is associated with greater VT inducibility186 and arrhythmic events.188, 198

1.4.2 T Wave Alternans in Cardiomyopathy

Visible TWA199 and abnormal microvolt TWA64 are present in 10% and 66% of patients with cardiomyopathy, respectively. It is not likely a coincidence that TWA is so commonly found amongst a group of individuals who are also predisposed to SCD. In fact, clinical testing has revealed TWA to be highly predictive of arrhythmia risk in cardiomyopathy patients, perhaps more so than in any other population. In a large prospective study of a mixed cardiomyopathy population with an LVEF <40%, TWA was found to have a negative predictive value of 97.5% and hazard ratio of 6.5 at 2 years for total mortality.64 More recently studies have begun to explore the relation between TWA and SCD in specific cardiomyopathy groups.

TWA testing is considered to be best suited for use in patients with ICM and an LVEF <40%.200 The recent Alternans Before Cardioverter Defibrillator study revealed TWA to have a negative predictive value of 95% and a hazard ratio of 2.1 for sustained arrhythmias.79 However, it is worth mentioning that the positive predictive value of TWA testing in ICM patients soon after myocardial infarction has been found to be particularly low.201 This may be due to inaccurate assessment of TWA during the post-infarct period (<1 month) where structural and electrical remodelling can occur.53 TWA testing in DCM populations with an LVEF <40% is equally well supported. The ALPHA trial examined 446 individuals and found the hazard ratio and negative predictive value of TWA for arrhythmic events to be 3.2 and 98%, respectively.202 Within HCM populations, TWA testing is occasionally utilized but there is less evidenced of its predictive ability for SCD. An early trial consisting of 23 Japanese patients found TWA to be predictive of

Table 1. The association of core and gray zone with cardiac outcome in various cardiomyopathy populations.

Study Population Scar Quantification Cardiac Outcome Method Core Gray Zone Does not Size predictive Yan et al.185 167 ICM Standard deviation* predict cardiac of cardiac mortality mortality Does not Size predictive Schmidt et 47 ICM FWHM predict VT of VT al.183 inducibility inducibility Does not Size predictive Roes et al.184 91 ICM FWHM† predict ICD of ICD shocks shocks Does not Size predictive Heidary et predict of 70 ICM FWHM al.197 cardiovascular cardiovascular events events Presence of scar and total scar Assomull et size predictive of all cause 101 DCM Visual al.187 mortality and cardiovascular hospitalization Presence of scar predictive of cardiovascular events and total Lehrke et al.189 184 DCM Standard deviation‡ scar size predictive of cardiovascular events amongst +LGE patients Total scar size predictive of Kwon et al.188 68 HCM Standard deviation‡ sustained and nonsustained VT combined Size predictive O'Hanlon et of cardiac 217 HCM FWHM Not assessed al.198 mortality and arrhythmia Total scar size predictive of VT Fluecther et 76 HCM Visual inducibility and increased risk al.186 factors for SCD *Core and gray zone defined as regions >3 and between 2-3 standard deviations from mean normal signal intensity, respectively. †Gray zone defined as regions between 35-50% of maximum scar signal intensity.

‡Total scar defined as regions >2 standard deviations from mean normal signal intensity.

43 sustained VT,203 while a more recent study found non sustained VT to be associated with TWA in a cohort of 88 individuals.204

2 Rationale, Hypothesis and Objectives 2.1 Rationale

Clinical and experimental evidence suggests that arrhythmogenic APDA may depend on the presence of structural nonuniformities in the ventricular myocardium. For instance, patients with structural heart disease develop TWA at lower heart rates162 and have greater TWA magnitudes71 than healthy individuals. TWA magnitudes in these patients appear to reflect the extent205, 206 and location of the structural damage as assessed by echocardiography.207 APD restitution208 and CV restitution209 properties, which have been suggested to contribute to the development of spatially discordant APDA,122, 139 are also significantly altered by structural heart disease in humans. Most importantly, experimental preparations have shown that structural barriers can directly give rise to discordance at reduced heart rates.113, 150, 161

Discordant APDA can create larger TWA magnitudes than concordant APDA.128, 139 Unfortunately, there are currently no experimental studies comparing variation in the magnitude and phase of APDA to TWA due to the technical difficulties associated with mapping repolarization alternans in vivo. However, using the forward solution to project simulated intracardiac APDA onto the body surface, we have previously demonstrated that TWA magnitude is directly related to the underlying APDA magnitude.116 Moreover, our prior simulation revealed that discordant APDA produce TWA magnitudes up to 6 times greater than concordant APDA of the same magnitude. This suggests that conditions which facilitate APDA discordance will also be those most likely to generate large measurable TWA in cardiomyopathy patients.

In the hearts of cardiomyopathic individuals, structural barriers occur in the form of localized fibrosis. Scar composition can vary such that some regions exist as a dense insulating core completely comprised of connective tissue, while other regions exist as a partially conductive gray zone that is a mixture of collagen and viable myocytes.181, 182 The amount and distribution of core and gray zone can be quite variable among patients depending on the severity and etiology of their heart disease. Diffuse structural heterogeneities, such as gray zone, can facilitate the development of discordant APDA at decreased heart rates by slowing conduction in simulated ventricular tissue.161 Alternatively, an insulating barrier, such as core, lowers the heart rate threshold for APDA discordance by uncoupling tissue with different AP properties in animal

45 models.113, 150 However, the effect of structural barriers on TWA in patients with cardiomyopathy has not been investigated. It may be that certain scar characterizations are more likely to promote discordant APDA which in turn produce large magnitude TWA in humans.

2.2 Hypothesis

We hypothesized that TWA in cardiomyopathy patients would be related to scar types that have greater potential to generate discordant APDA. More specifically, we proposed that a clinically positive TWA test, larger TWA magnitudes and a lower heart rate onset for TWA would be associated with:

1) greater amounts of gray zone which create tortuous pathways that delay conduction.

2) greater amounts of midwall core which transmurally uncouple endocardial and epicardial regions with disparate APD and APD restitution properties.

2.3 Objectives

Our objective was to prospectively evaluate TWA in a combined ICM, DCM, and HCM population, and relate this to the extent and transmural distribution of core and gray zone within the LV as quantified by LGE CMR.

3 Methods 3.1 Patient Population

The study population consisted of 43 consecutive patients with ICM (LVEF ≤40%, presence of coronary artery disease or prior myocardial infarction), DCM (LVEF ≤40%, no coronary artery disease) or HCM, who were scheduled for ICD placement or a clinical electrophysiological study. ICDs were implanted for either primary or secondary prevention of sudden cardiac death. Patients with recent myocardial infarction (<1 year), persistent atrial fibrillation, unstable angina, pacemaker dependency, or contraindications to LGE CMR imaging were excluded. All patients gave written informed consent and the study was approved by the Research Ethics Board of the University Health Network.

3.2 Cardiac Magnetic Resonance Protocol

LV structure and function was assessed using CMR, which was performed prior to electrophysiology study or ICD implantation using a 1.5-T (Avanto, Siemens) or 3-T (Verio, Siemens) scanner equipped with fast VQ gradient coils (slew rate up to 200 T/m/s) and a 32 channel phased array coil. Base to apex short-axis cine steady-state free precession images covering the entire cardiac cycle were obtained with breath-holding and ECG gating. Slice thickness and interslice gap varied from 6-10 mm and 0-2 mm, respectively, between patients. Other technical parameters were as follows: repetition time, 3.5 ms; echo time, 1.3 ms; flip angle (α), 45°; matrix, 224×128 pixels, and field of view, 36×36 cm.

LGE images were acquired 10-15 minutes after bolus injection of 0.2 mmol/kg gadobutrol (Gadovist, Bayer Schering Pharma) using an inversion recovery gradient-recalled echo pulse sequence. Images were obtained at short-axis locations with slice thickness and interslice gap identical to those of the cine sequence at a single instance near the end of diastole. Optimal inversion time was individually adjusted to null the normal myocardium. Technical parameters were as follows: repetition time, 7.2 ms; echo time, 3.2 ms; α, 15°, matrix, 256×192 pixels; inversion time, 180-300 ms.

3.3 Cardiac Magnetic Resonance Image Analysis

CMR analysis was blinded to TWA results and other clinical data. Cine images were analyzed with QMASS MR (version 4.2, Medis Medical Imaging Systems Inc) by Dr. Andrew Crean. LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), LVEF and LV end-diastolic mass were calculated by standard methods.210 For each short axis slice sequence, the end- diastolic and end-systolic images were identified as those that displayed the maximum and minimum LV cavity sizes, respectively. LV endocardial borders were manually traced, excluding trabeculae and papillary muscle, on each end-diastolic and end-systolic image. The end-diastolic and end-systolic LV cavity volumes were individually summed to obtain the LVEDV and LVESV. LVEF was calculated as the difference in LVEDV and LVESV divided by LVEDV. LV epicardial contours were manually traced, excluding epicardial fat, on the end-diastolic images. The LV end-diastolic myocardial volumes were then summed and multiplied by the average density of myocardium (1.05 g/mL) to obtain the total LV mass.

LGE images were analyzed with custom software developed in MATLAB (Version 7.7.0, MathWorks Inc.). As illustrated in Figure 14, scar volume and heterogeneity were quantified using a previously described FWHM SI thresholding technique.183 For each slice, the LV endocardial and epicardial borders were manually traced as previously described. Because it is often difficult to distinguish endocardial enhancement from blood pool and epicardial enhancement from pericardial fat, the LGE images were compared to their corresponding cine images to ensure accurate assessment of the LV contours. Once the LV borders were delineated, the maximum SI within the scar region was automatically determined. A region of remote (normal) myocardium was manually identified and the maximum SI of this region was determined. Scar core was defined as myocardium with SI ≥50% of the maximum scar SI. Scar gray zone was defined as myocardium with SI > the maximum remote SI but <50% of the maximal scar SI. Single isolated pixels of core or gray zone were considered to be noise and were manually excluded. LV slices without apparent delayed enhancement did not undergo SI thresholding and their scar volumes were set to zero. The mass of total scar, core and gray zone

(Scartotal = Scarcore + Scargray) were calculated by summing the measured volumes in each LV slice and multiplying by the average density of myocardium (1.05 g/mL). The scar masses were also computed as a proportion of the total LV mass (Scartotal% = Scarcore% + Scargray%).

Figure 14. Scar characterization methods in a representative late gadolinium enhanced cardiac magnetic resonance LV slice.

(A) LV endocardial and epicardial contours (blue lines) are traced to define the LV myocardial region. Papillary muscle and trabeculae are left as a part of the bloodpool. The maximum SI (green X) within the scar region is identified. A region of remote (normal) myocardium is contoured (green diamond) and the maximum remote SI is identified. (B) Scar core (red) is defined as pixels with SI ≥50% of the maximal SI. Scar gray zone (yellow) is defined as pixels with SI > the maximum remote SI but <50% of the maximum scar SI. (C) The total myocardial and scar volumes are calculated by summing the individual slice volumes. Panel C adapted with permission from Elsevier: Journal of the American College of Cardiology (Heidary et al.197), copyright © 2010.

The scar annotated images were used to evaluate the transmural distribution of core as shown in Figure 15. For each LV slice, 360 evenly spaced radial lines were generated, extending outward from the center of the LV. Each radial line was categorized by the location of the core through which it passed. A line was classified as full thickness if it intersected core adjacent to both the endocardial and epicardial borders, endocardial if it intersected core only adjacent to the endocardial border, epicardial if it intersected core only adjacent to the epicardial border, or midwall if it intersected core adjacent to neither border. The proportion of full thickness, endocardial, epicardial, and midwall core for each LV slice was determined by dividing the number of lines in each category by 360. These slice proportions were used to create a volume- weighted average for the entire LV according to the following equation (where n is the total number of slices and X represents epicardial [epi], endocardial [endo], midwall [mid] or full thickness [full] core):

3.4 T Wave Alternans Protocol

TWA evaluation was performed during EPS or ICD follow-up at least one month after implantation. Beta-blocking agents were not routinely held prior to evaluation, which is currently considered to be acceptable practice for TWA assessment.211 AV sequential pacing (AV delay 160 ms) was performed at 100, 110, and 120 bpm for 3 minutes at each rate using the ICD leads at follow-up or quadripolar pacing catheters (Avail, Biosense Webster) placed in the high right atrium and RV apex at the time of EPS. Throughout pacing, 12-lead ECG signals were recorded at a sampling rate of 1 kHz with 12 bit resolution on a clinical electrophysiology workstation (Cardiolab, GE Medical Systems) at EPS, or a digital Holter monitor (CardioMem CM 3000- 12BT, Getemed Inc.) in patients with an ICD. The analog bandwidths used by the Holter and electrophysiology workstation were 0.05 to 120 Hz and 0.05 to 500 Hz, respectively. During EPS, TWA was simultaneously assessed using the clinical HeartWave system and High-Res electrodes (Cambridge Heart Inc.). Because TWA analysis is particularly sensitive to noise, leads were only placed after the skin was shaved, abraded and cleaned.

Figure 15. Method for calculating transmural distribution of core in a representative late gadolinium enhanced cardiac magnetic resonance LV slice.

(A) The centre of the LV is defined (black X) and 360 evenly spaced radial lines (blue) are generated from this point. (B) Each radial line is classified by the location of core that it intersects. Lines passing through core that is adjacent to both the endocardial and epicardial borders are defined as full thickness (white). Lines passing through core only adjacent to the epicardial border are defined as epicardial (green). Lines passing through core only adjacent to the endocardial border are defined as endocardial (yellow). Lines passing through core which is not adjacent to either border are defined as midwall (red). For each LV slice, the proportion of core in each transmural category is then calculated by dividing the number of respective lines by 360.

3.5 T Wave Alternans Analysis

All ECG signal processing was completed with in-house developed software written in MATLAB (version 7.7.0). Each pacing study was individually analyzed for TWA utilizing the spectral method first described by Smith and colleagues.66, 71 Before alternans could be quantified a series of preprocessing steps were implemented including beat detection, baseline correction, beat alignment and spurious beat replacement.

3.5.1 QRS Detection

QRS detection was automatically carried out on a single lead of the entire recording using an adaptation of the Pan-Tompkins real-time QRS Detection algorithm.212-214 This process involved an initial filtering of the signal followed by the application of a series of detection rules. Typically, precordial lead V2 was chosen for QRS detection due to its large amplitude QRS complexes.

The first stage of QRS detection required filtering of the raw ECG waveform as shown in Figure 16A. A fourth-order bidirectional Butterworth bandpass filter with a bandwidth of 5 to 15 Hz was applied to the initial signal. This pass band was chosen to attenuate noise while capturing the majority of the QRS complex energy. A five point derivative was then used to obtain QRS slope data. The absolute value of the derivative waveform was subsequently taken to produce an entirely positive signal. Moving window integration was then applied to smooth the positive signal by removing minor deflections. An averaging window of 80 ms, which is the width of a typical QRS, was chosen to avoid merging of QRS and T wave slope information.215 These filtering steps produced a final waveform with isolated large amplitude peaks corresponding to the high frequency QRS complexes and smaller peaks corresponding to the T wave.

The second stage of QRS detection involved classification of each peak in the filtered waveform as a QRS complex or noise. This entailed the application of a series of detection rules that utilized peak height and peak location information from the integrated waveform, as well as slope information from the derivative waveform. For peak height, an adaptive peak detection threshold was created by using the mean of the maximum amplitudes of the eight most recently

Figure 16. T wave alternans ECG preprocessing methods.

(A) Signal processing stages involved in the creation of the QRS detection waveform. (i) The unaltered ECG. (ii) Output of the bandpass filter. (iii) Differentiation of the filtered ECG. (iv) Absolute value of the filtered derivative. (v) Result of moving window integration. QRS detection rules are applied to the final waveform as described in the text. (B) Baseline correction of a representative ECG segment. The top panel depicts the uncorrected ECG (black) and the cubic spline interpolation (blue) of the isoelectric PR segment anchor points (red x). (ii) The lower panel shows the corrected ECG after subtraction of the spline. (C) Illustration of QRS end (J point) and T end marking on a single beat. All 12 ECG leads are overlaid in the same window. The automatically determined QRS onset (blue) is displayed, while the QRS end (red) and T end (green) are manually identified. Multiple beats are checked to ensure accuracy of these fiducial points.

53 detected QRS peaks and the mean of the maximum amplitudes of the eight most recently detected noise peaks:

At the onset of analysis, the peak threshold was initialized by filling the QRS peak buffer with the largest peaks in the first eight consecutive one second intervals, and the noise peak buffer with eight zero values.

The detection rules outlined by Tompkins and associates212, 213 are as follows. First, all peaks within 200 ms of a larger peak were ignored because two QRS complexes cannot occur within such an interval under normal most circumstances. Second, if a peak occurred <360 ms after a previous QRS detection, the derivative waveforms at the two peak locations were compared. If the maximum slope in the region of the detected peak was <50% of the maximum slope of the previous QRS, then the new peak was assumed to be a T wave and classified as noise. Third, if a peak did not satisfy the first two rules and it was larger than the peak detection threshold then it was classified as a QRS, otherwise it was classified as noise. Finally, if no QRS had been detected within 1.5 times the average CL and there was a peak >50% of the detection threshold that occurred ≥360 ms after the last QRS detection, that peak was classified as a QRS. The average CL used in this step was determined by taking the mean of the eight prior CLs.

Once QRS detection was completed, QRS onsets locations were automatically determined by searching for the isoelectric PR segment. To remove noise, the raw waveform was first filtered using a fourth-order bidirectional Butterworth bandpass filter with a pass band of 1 to 60 Hz. Starting at the location of the QRS detection, a 20 ms moving window was incremented backward one sample point at a time. When the moving window reached a region where the difference between the maximum and minimum voltages were <75 µV, the QRS onset was determined to have been found and the fiducial point was set at the middle of the window. If this criterion was not satisfied within 150 ms prior to the QRS detection, the onset point was left at the 150 ms mark for subsequent manual correction.

Visual analysis was used to confirm accurate QRS detection and onset placement. The selected ECG lead was plotted with markers corresponding to the detected QRS onsets above the CL

54 graph to aid in the detection of abnormal onsets. Missed QRS complexes or inaccurate QRS onsets were manually added or adjusted, respectively.

3.5.2 Baseline Correction

Baseline wander, created by respiration or patient movement, was removed to prevent potential false positive or false negative TWA detections. The first and last beat of a pacing study was manually identified within the continuous ECG recording. Baseline wander for this segment was corrected in each of the 12 ECG leads using a cubic spline interpolation of the isoelectric points.216 Although there are a variety of methods for removing baseline artifacts, the cubic spline algorithm was chosen because it has little effect on the low frequency components of the signal and therefore should not alter the true TWA signal.217, 218 Anchor points were automatically set 20 ms prior to each QRS onset and visually confirmed to ensure that they fell within the isoelectric PR segment and not on the P wave. To avoid distortion of the ECG ends, PR segment anchors were also placed before the five beats at the beginning and end of the evaluation segment. A baseline wander waveform was created for each lead via cubic spline interpolation of the isoelectric anchor points. These waveforms were then subtracted from the corresponding lead to produce the final baseline corrected ECG (Figure 16B).

3.5.3 Beat Alignment

An iterative template matching scheme as outlined by Smith et al.66 was used to align QRS complexes and their associated T waves in the baseline corrected ECG segment. The average QRS interval was determined by manually demarcating the QRS offset (J point) on the superimposed QRS complexes of all 12 leads as shown in Figure 16C. With this average QRS interval, a corresponding QRS offset was created for each QRS onset. These fiducial points were then used to create an average QRS complex that was compared to each individual QRS for alignment. In this process, the average QRS template was placed 100 ms prior to a candidate QRS onset and incremented one sample point at a time until at it was 100 ms beyond the QRS onset. The QRS onset and offset points for the candidate beat were set at the position which maximized the normalized cross-correlation with the template. The QRS template was then recalculated with the newly derived fiducial points, excluding noisy or ectopic beats whose best correlation coefficient was <0.5. Cross-correlations were recalculated for each beat using the new template to determine the final QRS onset and offset points.

3.5.4 Spurious Beat Replacement

Noisy or ectopic beats were automatically identified within the analysis segment by morphology and CL criteria similar to those used by the clinical HeartWave system (Cambridge Heart Inc.). T end points were generated for each beat in a similar fashion to QRS end points as described in the previous section and shown in Figure 16C. An average beat template, covering the entire QT interval, was computed excluding the beats with previously detected noisy or ectopic QRS complexes. Morphological comparison of each candidate beat to the average beat was computed using the Pearson correlation. Beats with a correlation coefficient <0.9 were flagged, as were beats with a CL <15% of the mean CL. In case the premature beats encroached on the previous T wave, beats prior to a short CL were also flagged. All potentially spurious beats were viewed and manually confirmed. Bad beats were replaced by the average beat template to prevent potential phase changes in the alternans signal.71

3.5.5 Spectral Analysis

TWA was evaluated in each lead using a 128-beat window that was incrementally shifted by 16 beats from the beginning to the end of the preprocessed evaluation segment. The relatively large window and small incrementing factor provide adequate robustness to noise and temporal resolution, respectively.71 Figure 17 illustrates the spectral analysis of a single 128-beat window as described by Cohen and colleagues.66, 71-73 Power spectra were created for each set of corresponding sample points in the aligned JT intervals by computing the squared magnitude of the fast Fourier transform for each series. These power spectra were then summed to create an aggregate power spectrum encapsulating the entire T wave. The final spectrum depicted all frequencies at which there were beat to beat fluctuations in the JT segment. Importantly, a frequency peak at 0.5 cycles per beat signifies a fluctuation in the T wave on an every other beat basis, indicating the presence of alternans. The TWA magnitude (Valt) was calculated relative to the mean noise band directly preceding the alternans frequency from 0.44 to 0.49 cycles per beat:

To provide a level of statistical confidence, the alternans signal to noise ratio (k value) was calculated as the number of standard deviations of the alternans peak above the mean noise band:

Figure 17. Spectral analysis of T wave alternans.

(A) A representative portion of a 128 beat ECG segment. The filled black circles highlight corresponding points on each JT interval as determined by beat alignment. (B) The time series created from the amplitudes of the corresponding JT points from all 128 consecutive beats. The up down oscillations in amplitude are indicative of alternans. (C) The power spectrum produced by calculating the squared magnitude of the fast Fourier transform of the 128 point series. A large respiration peak is visible near 0.2 cycles per beat and a smaller alternans peak is visible at 0.5 cycles per beat. The alternans magnitude is calculated relative to the noise band from 0.44 to 0.49 cycles per beat. Summing the power spectra from each JT point series produces an aggregate spectrum that encapsulates all frequencies across the JT interval for the entire 128 beat segment. Figure adapted with permission from Elsevier: Cardiac Electrophysiology From Cell to Bedside (Cohen219), copyright © 2000.

3.5.6 TWA Artifact Detection

Each 128-beat windows was examined for potential artifacts that could produce false positive TWA. Artificial alternans can be created by multiple factors but are most commonly a result of ectopic beats, a respiratory frequency at one forth the heart rate, or CL alternans.73 First, TWA analysis was considered to be unreliable in the presence of ≥15% spurious beats. Second, respiratory frequency typically occurs between 0.2 and 0.33 cycles per beat, however, a sustained frequency at 0.25 cycles per beat can produce a harmonic peak at 0.5 cycles per beat. Therefore, alternans could not be reliably measured in segments where the frequency peak at 0.25 cycles per beat was greater than twice the frequency peak at 0.5 cycles per beat. Third, sustained CL alternans can generate artificial TWA. CL alternans was assessed by applying the spectral method to the set of the 128 consecutive CLs within the window. TWA in the presence of CL alternans >2 ms with a k ≥3 were considered artifactual. Windows with any of these potential confounders were excluded from analysis.

3.5.7 T Wave Alternans Classification

Each patient was classified as TWA positive (+TWA) or TWA negative (-TWA) by applying a set of Valt, k value and heart rate criteria to the artifact free 128-beat segments. An abnormal or

+TWA test was defined according to the clinical definition as a Valt ≥1.9 µV with a k ≥3 at a heart rate ≤110 bpm, occurring in more than one ECG lead for the same 128-beat window.72, 73 A TWA test that was not positive was considered to be negative. The maximum

TWA magnitude (TWAmax) for each patient was defined as the maximum Valt with a k ≥3 at a heart rate ≤110 bpm, occurring in more than one ECG lead for the same 128-beat window.

TWAmax was considered 0 for any window with a k value <3. For each patient, the heart rate onset for TWA (TWAonset) was defined as the slowest paced rate (≤100, 110, or ≥120 bpm) where the Valt was greater than 0 µV with a k ≥3 occurring in more than one ECG lead for the same 128-beat window. In those patients with k <3 for all 128-beat windows across all pacing rates, TWAonset was classified as ≥120bpm.

3.5.8 Clinical TWA Analysis

The clinical TWA HeartWave system (Cambridge Heart Inc.) similarly applies the spectral method to consecutive 128 beat windows using 16 beat increments. Although the analytical methods are nearly identical to our algorithm, the clinical system also uses specialized noise reducing High-Res (Cambridge Heart Inc.) electrodes that reportedly improve TWA detection.73 Results outputted by the clinical TWA system are displayed in Figure 18. Each patient is classified as +TWA, -TWA or indeterminate. Detailed plots of the Valt, k value and noise versus time are also outputted for each precordial lead. Because the maximum TWA magnitude is not directly provided, the clinical TWAmax was estimated from the graphs by identifying the largest

Valt with a k ≥3 that occurred in an artifact free segment of more than one precordial lead. The clinical TWAonset was similarly obtained from the graphs by identifying the lowest hear rate at which a Valt >0 with a k ≥3 occurred in an artifact free segment of more than one precordial lead.

3.6 Clinical Outcomes

Clinical outcomes were evaluated prospectively in the patients without a history of sustained ventricular tachyarrhythmia. These patients were followed every 3 to 6 months after EPS or ICD implantation for appropriate ICD therapy, sustained ventricular tachyarrhythmias (>30 seconds), or death. Ventricular tachyarrhythmia programming was standardized for all patients with a prophylactic ICD.

3.7 Statistical Analysis

Continuous variables are expressed as mean and standard deviation or median and interquartile range (25th-75th percentiles) where appropriate. Student's t test or the Mann-Whitney U-test was used for unpaired group comparison. Student's paired t test and the Wilcoxon signed-rank test were used for paired comparison between groups. The Jonckheere-Terpstra test was used to compare variables between the ordered TWAonset groups. Mann-Whitney U-tests with Holm-

Bonferroni correction were applied post-hoc to determine which TWAonset groups differed. Categorical variables are presented as frequency or percentage and were compared by χ2 or Fisher's exact test for unpaired groups and McNemar's test for paired groups. Correlation between TWAmax and CMR variables was assessed using Spearman's rank correlation

Figure 18. HeartWave clinical TWA results output for the precordial leads from a representative +TWA patient during a TWA pacing protocol.

The upper graph display both beat to beat and smoothed heart rate versus time. The lower graphs display changes in the TWA magnitude (solid line) over time for each precordial lead. Gray shaded areas denote regions with a k value ≥3. Solid horizontal bars indicate artifact free data. The dashed line represents the noise level. For this patient, the clinical TWAonset is estimated to be 100 bpm, occurring prior to the 1 minute mark where leads V1-V3 are all artifact free with a k value ≥3. The clinical TWAmax is estimated to be 12 µV, occurring just after the 5 min mark in lead V2 where k ≥3 and the data is artifact free (horizontal bar visible in leads V4 and V5).

60 coefficient. Variables that could relate to +TWA as determined by univariate analysis were included in a multivariate stepwise logistic regression model. Variables entered the multivariate model if P<0.1 and exited the model if P>0.05. A two-tailed P<0.05 was considered statistically significant. Potential colinearity between multivariate variables was assessed using Pearson's correlation. All statistical analysis was performed using SPSS (version 19.0.0, SPSS Inc.). Statistical analysis and approach was reviewed by Dr Joan Ivanov.

4 Results 4.1 Patient Population

Clinical characteristics of the study population are presented in Table 2. The pacing protocol could not be completed in three patients due to frequent ectopy. The remaining population included 40 patients (31 male, age 53±14 years, LVEF 39±17 %) with ICM (n=13 [33%], LVEF 30±7%), DCM (n=12 [30%], LVEF 27±9%) and HCM (n=15 [38%], LVEF 56±13%). Three patients (8%) received an ICD for secondary preventive therapy and 31 patients (78%) received a prophylactic ICD. The remaining 6 patients (15%) did not undergo ICD implantation. Seven patients (18%) underwent TWA testing during clinical EPS and 33 patients (83%) were tested during ICD follow-up, 74 (52-109) days after implantation.

4.2 Prevalence of +TWA

A total of 120 pacing studies were performed in the 40 patients. Six pacing studies were excluded due to excessive ectopy throughout. All patients had at least one analyzable study at a pacing rate 110 bpm. From the pacing studies, 27 patients (68%) were found to be +TWA with a median TWAmax of 6.1 (3.8-12.6) µV. The -TWA group had a median TWAmax of 0.0 (0.0-0.0)

µV, as only 3 of the -TWA patients (33%) had a non-zero TWAmax. No significant differences were observed in any of the clinical parameters between the +TWA and -TWA groups.

4.3 TWA Algorithm Validation

Out TWA results were compared to those generated by the clinical HeartWave system (Cambridge Heart Inc.) amongst the 9 patients who underwent TWA testing during EPS. The clinical tool classified 7 (78%) of the patients as +TWA, while our method found all patients to be +TWA. Review of the graphic output revealed that the two clinically -TWA patients had a

Valt >0 µV but <1.9 µV (k ≥3) at a heart rate of 100 bpm. Our analysis found both of these patients to have a Valt just above the 1.9 µV (k ≥3) threshold (2.1 µV and 3.7 µV) at approximately the same times as the subthreshold detections by the clinical system. The TWAmax obtained from the clinical tool was significantly greater than the TWAmax calculated by our method (7.1 ± 3.5 µV vs. 5.7 ± 2.6 µV, P=0.03). The TWAonset for all patients using either method was 100 bpm. Typically, there was good agreement in tracking of Valt changes over time as demonstrated in Figure 19. It appears that our system may be more sensitive to TWA

Table 2. Clinical characteristics of the study population.

All patients -TWA +TWA (n = 40) (n = 13) (n = 27) P

Age, y 53±14 56±16 51±13 0.33 Male, n (%) 31 (78) 9 (69) 22 (81) 0.44 Hypertension, n (%) 7 (18) 3 (23) 4 (15) 0.66 Diabetes, n (%) 8 (20) 3 (23) 5 (19) 1.00 Cardiomyopathy, n (%) 0.12 Ischemic 13 (33) 7 (54) 6 (22) Dilated 12 (30) 2 (15) 10 (37) Hypertrophic 15 (38) 4 (31) 11 (41) Medication, n (%) β-blocker 34 (85) 13 (100) 21 (78) 0.15 Class III antiarrhythmic 6 (15) 3 (23) 3 (11) 0.37 ACE inhibitor/ATII antagonist 27 (68) 8 (62) 19 (70) 0.72 Calcium channel blocker 4 (10) 0 (0) 4 (15) 0.28 Lipid lowering 21 (53) 9 (69) 12 (44) 0.19 Diuretic 19 (48) 5 (38) 14 (52) 0.51 Antiplatelet 18 (45) 8 (62) 10 (37) 0.19 ICD indication* 0.54 Primary prevention 31 (91) 11 (85) 20 (95) Secondary prevention 3 (9) 2 (15) 1 (5)

*Amongst patients with an ICD (n=34)

Figure 19. Comparison of TWA detection between the clinical TWA analysis tool and our software in a representative patient.

(A) Plot illustrating heart rate over the course of an entire TWA pacing protocol. (B) Plot of TWA magnitude (Valt, solid black line) versus time in ECG lead V4 of a representative patient as outputted by the HeartWave clinical TWA system (Cambridge Heart Inc.). Grey shaded areas indicate regions with k ≥3. (c) Valt plot created by our algorithm from ECG lead V4 of the same patient. Red shaded areas denote regions with k ≥3. In both Valt graphs, transient alternans appear at 100 bpm but does not become sustained above the 1.9 µV threshold until the pacing rate is increased to 110 bpm. Alternans decreases and finally subsides when the pacing rate is increased to 120 bpm.

64 under certain circumstance, perhaps due to the manual verification of each automated stage, but normally underestimates TWAmax, possibly due to the use of normal non noise cancelling electrodes.

4.4 CMR Assessment

CMR images were acquired within 102 (67-184) days of TWA testing. Table 3 summarizes the CMR findings for the study population. No significant differences in LVEF, LVEDV, LVESV or LV mass were seen between the +TWA and -TWA groups.

Scartotal (45 [29-56] g vs. 16 [0-37] g, P=0.007) and Scargray (26 [15-36] g vs. 8 [0-16] g,

P<0.001) were significantly larger in the +TWA versus -TWA group. Scarcore, however, was not significantly different between the two groups. When calculated as a proportion of the myocardial mass, Scartotal% (29 [22-40] % vs. 19 [0-27] %, P=0.009) and Scargray% (17 [14-25] % vs. 8 [0-11] %, P<0.001) remained significantly larger in the +TWA group while there was still no difference in Scarcore%. Figure 20 compares core and gray zone between a +TWA and -

TWA patient with ischemic cardiomyopathy. Although the two patients had similar Scarcore%

(12% vs. 14%), Scargray % was considerably greater in the +TWA patient (24% vs. 12%).

The +TWA group also had significantly greater Coreepi% (4 [3-10] % vs. 1 [0-3] %, P=0.002) and Coremid% (7 [4-10] % vs. 3 [0-6] %, P=0.018) than the -TWA group. There was no significant difference in the proportion of endocardial and full thickness core between +TWA and -TWA. Figure 21 compares the distribution of core between a +TWA and -TWA patient with hypertrophic cardiomyopathy. While both patients had nearly identical total myocardial scar

(Scarcore% [7% vs. 8%], Scargray% [19% vs. 18%]), the +TWA patient had substantially greater

Coremid% (10% vs. 4%) than the -TWA patient.

4.5 Predictors of +TWA

In order to determine whether LV structure predicted +TWA, univariate analysis was performed on the variables listed in Table 3, with the exception of absolute scar mass. In the univariate analysis, Scartotal% (P=0.015), Scargray% (P=0.002), Coremid% (P=0.028), and Coreepi% (P=0.020) percentages were significant predictors of +TWA. A non-significant association was observed between LVEDV (P=0.097) and +TWA. For multivariate logistic regression analysis,

Scargray%, LVEDV, Coreepi% and Coremid% were included. Scartotal% was not included because

Table 3. Cardiac magnetic resonance characteristics of the study population.

All patients -TWA +TWA (n = 40) (n = 13) (n = 27) P

LVEDV, mL 241±103 202±67 260±112 0.09 LVESV, mL 158±97 126±68 173±107 0.16 LVEF, % 39±17 40±19 38±17 0.82 LV mass, g 145±53 131±48 151±55 0.28 Scar size, g Total (core + gray zone) 36 (15-49) 16 (0-37) 45 (29-56) 0.007 Core 14 (5-21) 7 (0-21) 15 (9-22) 0.15 Gray zone 20 (8-32) 8 (0-14) 26 (15-36) <0.001 Scar size, % of LV mass Total (core + gray zone) 26 (19-36) 19 (0-27) 29 (22-40) 0.009 Core 10 (4-16) 8 (0-16) 10 (6-16) 0.31 Gray zone 15 (9-19) 8 (0-11) 17 (14-25) <0.001 Core distribution, % of LV circumference Endocardial 6 (1-27) 7 (0-34) 5 (1-21) 0.72 Epicardial 3 (1-7) 1 (0-3) 4 (3-10) 0.002 Midwall 5 (3-10) 3 (0-6) 7 (4-10) 0.02 Full thickness 1 (0-2) 0 (0-2) 1 (0-2) 0.26

Figure 20. Comparison of gray zone between a -TWA and +TWA patient

Annotation of core (red) and gray zone (yellow) on late gadolinium enhanced cardiac magnetic resonance images from the LV base, mid and apex of a -TWA and +TWA patient. Although both patients have ischemic cardiomyopathy (LVEF 38% vs. 26%) with similar core (14% vs. 12%), the +TWA patient has greater gray zone (12% vs. 24%) which is most evident in the mid to apical LV.

Figure 21. Comparison of midwall core between a -TWA and +TWA patient

Annotation of core (red) and gray zone (yellow) on late gadolinium enhanced cardiac magnetic resonance images from the LV base, mid and apex of a -TWA and +TWA patient. Although both patients have hypertrophic cardiomyopathy (LVEF 48% vs. 63%) and similar core (8% vs. 7%) and gray zone (18% vs. 19%), the +TWA patient has greater midwall core (10% vs. 4%) which is most evident in the basal to mid LV.

of strong colinearity with Scargray% (r=0.79, P<0.001). In this model Scargray% was the only significant predictor of +TWA (odds ratio, 1.22/10%; 95% confidence interval, 1.08 to 1.39; P=0.002) with a c-statistic of 0.89.

4.6 Relationship between TWAmax and +TWA Predictors

Scartotal% (r=0.34, P=0.03), Scargray% (r=0.53, P<0.001), Coremid% (r=0.40, P=0.01) and

Coreepi% (r=0.54, P<0.001) positively correlated with TWAmax. LVEDV did not significantly correlate with TWAmax (r=0.26, P=0.107). Figure 22 illustrates scar distribution in a representative patient with hypertrophic cardiomyopathy (LVEF 62%) and large TWAmax (17.0

µV). This patient had greater Scargray%, Coremid%, and Coreepi% than the median values for the +TWA group (30% vs. 17%, 10% vs. 7%, and 15% vs. 4%, respectively).

4.7 Heart Rate Onset for TWA and +TWA Predictors

With increasing pacing rate, the proportion of pacing studies with Valt >0 and a k ≥3 significantly increased as did Valt (Table 4). Amongst the 40 patients, TWAonset occurred at ≤100 bpm in 20 patients (50%), at 110 bpm in 10 patients (25%) and at ≥120 bpm in 10 patients (25%). Figure 23 presents box plots comparing Scartotal%, Scargray%, Coremid%, and Coreepi% between the TWAonset groups. Scartotal% (P=0.001), Scargray% (P<0.001) and Coreepi% (P=0.001) were significantly different between the groups while Coremid % (P=0.14) was similar. Post-hoc analysis revealed that there was significantly more Scartotal%, Scargray% and Coreepi% in patients with TWAonset

100 bpm than in patients with TWAonset ≥120 bpm (P=0.003, P<0.001 and P=0.004, respectively). Scargray% was also found to be significantly greater in individuals with a TWAonset of 110 bpm compared to those with a TWA onset ≥120 bpm (P=0.004). There were no differences in Scartotal%, Scargray%, Coremid%, or Coreepi% between the 100 bpm and 110 bpm

TWAonset groups.

4.8 Absence of Scar and TWA

No discernable scar on LGE CMR was present in 5 patients, all with non-ischemic cardiomyopathy. A lack of scar was significantly associated with -TWA compared to +TWA (n=4 of 13 [31%] vs. n=1 of 27 [4%], P=0.03). The patients without scar also had a significantly later TWAonset compared to patients without scar (120 [110-120] bpm vs. 100 [100-110] bpm,

Figure 22. Core and gray zone characteristics of a patient with large magnitude TWA.

Annotation of core (red) and gray zone (yellow) on late gadolinium enhanced cardiac magnetic resonance images from the LV base, mid and apex of a patient with hypertrophic cardiomyopathy (LVEF 62%) and a TWA magnitude of 17.0 µV. Compared to the median values of the +TWA group, this patient has greater gray zone (30% vs. 17%), epicardial core (15% vs. 4%), and midwall core (10% vs. 7%).

Table 4. Response of T wave alternans to increasing pacing rate.

100 bpm 110 bpm ≥120 bpm (n = 40) (n = 38) (n = 36) P*

TWA present†, n (%) 20 (50) 25 (66) 26 (72) 0.006

Valt, µV 0.7 (0.0-5.1) 3.1 (0.0-7.1) 4.1 (0.0-9.9) 0.001

*Comparison between pacing studies at 100 and 120 bpm.

†TWA present if Valt >0 (k ≥3) in more than one ECG lead.

Figure 23. Comparison of scar and TWA onset heart rate

Box plots illustrating differences in scar between patients who manifest TWA at low (≤100 bpm, n=20), intermediate (110 bpm, n=10) and high (≥120 bpm, n=10) pacing rates. Patients with a lower heart rate onset for TWA have larger proportions of total scar (A), gray zone (B) and epicardial core (C). (D) Midwall core percentage does not separate patients by heart rate onset for TWA. An open circle signifies an outlier value which is between 1.5 to 3 times than the interquartile range. An asterisk signifies an extreme value which is more than 3 times the interquartile range.

P=0.03). There was a trend towards a lower TWAmax in patients with no scar compared to those with scar (0.0 [0.0-6.3] µV vs. 4.2 [1.9-9.1] µV, P=0.066).

4.9 Clinical Outcomes

Clinical follow-up was available for the 37 patients (93%) without a prior history of sustained ventricular tachyarrhythmia. Mean follow-up duration was 403±206 days. There were no deaths in the study population. No clinical events were experienced by the -TWA group. However, one +TWA patient (ICM, LVEF 29%) received appropriate ICD therapy for ventricular tachycardia.

This patient had a TWAmax of 3.8 µV with Scargray% and Coremid% greater than the median values of the +TWA group (18% vs. 17% and 10% vs. 7%, respectively).

5 Discussion 5.1 Gray zone, midwall core and epicardial core contribute to T wave alternans in cardiomyopathy patients

The major finding of our study is that increased scar gray zone is associated with a +TWA test, greater TWA magnitude, and a lower heart rate onset for TWA in cardiomyopathy patients. Greater total scar, midwall core and epicardial core also related significantly to TWA, albeit to a lesser extent. Other clinical and CMR variables of LV structure and function were not associated with heart rate onset, magnitude or prevalence of TWA.

Our study is the first to evaluate the relation between TWA and scar as defined by LGE CMR in humans. Prior clinical studies have suggested that higher magnitude TWA at slow heart rates may reflect increased myocardial damage in DCM205, HCM206 and ICM207 patients. Furthermore, echocardiography has revealed that TWA spatially reflects regions with wall motion abnormalities and presumable scarring in patients with ICM.207 However, these studies did not quantify the spatial distribution of core and gray zone with the precision afforded by CMR. In computational150, 161 and experimental113 studies using tissue sheets, a structural barrier facilitates the development of higher magnitude concordant APDA as well as spatially discordant APDA at lower heart rates, which in turn produce the largest TWA magnitude.116 Our findings extend these observations to humans, and support the relevance of structural barriers to the pathogenesis of TWA in cardiomyopathic patients.

We observed that a lack of apparent myocardial scar was related to -TWA, a lower TWAmax and a higher TWAonset. Conversely, greater Scartotal% was associated with +TWA, positively correlated with TWAmax and lowered the TWAonset. These results are consistent with the aforementioned clinical works relating TWA to increased total structural damage in cardiomyopathy.205-207 However, our study reveals that the composition and distribution of scar is of even greater importance to TWA genesis than the total amount of scarring.

Through precise tissue characterization we found gray zone to be the most significant determinant of TWA. Increased Scargray% was associated with an earlier TWAonset, positively correlated with TWAmax and was the only independent predictor of +TWA. Histological examination of infarcted pig and rat hearts shows that the gray zone, as identified by LGE CMR,

74 is a disorganized mixture of collagen and viable myocytes.181, 182 Engelman et al.161 simulated this type of diffuse heterogeneous scar in an electrically homogenous tissue sheet and observed that the highly tortuous conduction pathways created large variation in CV which altered the temporal activation sequence and subsequently decreased the onset heart rate for APDA discordance. Of particular importance was the presence of regions with slowed conduction. In electrically uniform tissue models, engagement of CV restitution causes spatially concordant APDA to become discordant by slowing conduction after a short diastolic interval which paradoxically increases the diastolic interval at sites far from stimulus.139 Patchy fibrosis has similarly been observed to delay conduction in the hearts of individuals with ICM, DCM and HCM.209 Together these studies suggest that abnormal CV restitution created by structural remodelling in the gray zone of our patients may facilitate the early onset of discordant APDA and consequently large TWA.

Extensive electrical remodelling of myocytes also occurs throughout the gray zone. Gap junction organization and connexin43 expression is altered in the diffusely fibrosed regions of hearts with ischemic and nonischemic cardiomyopathy.220 Gap junctional remodelling enhances anisotropy and reduces intercellular coupling which slows conduction.221, 222 Slowing of CV at reduced heart rates is associated with broadened CV restitution which promotes APDA discordance at reduced heart rates.122, 139 Additionally, the increased number of fibroblasts in the gray zone may lead to greater fibroblast-myocyte interaction. Simulations demonstrate that fibroblast-myocyte coupling can promote APDA discordance at slow heart rates via two mechanisms: by slowing CV and broadening CV restitution in adjacent myocytes or by heterogeneous fibroblast distribution which promotes regional variation in electromechanical coupling (APD-Ca2+).223 Thus electrical remodelling in the gray zone may further initiate and/or augment TWA through various mechanisms.

A modest relation was observed between midwall core and TWA. Greater Coremid% was significantly associated with +TWA and weakly correlated with TWAmax. Core, as distinguished by LGE CMR in animal models, is an area of dense nonconductive fibrosis.181, 182 Experiments with guinea pig hearts show that dense scar placed perpendicular to an APD gradient can cause APDA discordance and TWA at reduced heart rates.113 Electrotonic coupling normally acts to homogenize intrinsic differences in the repolarization properties of myocytes across the ventricular myocardium.224 However, a loss of coupling due to the presence of a non conductive

75 barrier allows myocytes to express intrinsic differences in APD and APD restitution; thereby promoting concordant APDA to act independently on opposing sides of the barrier.150 Transmural APD gradients exist in the human LV, such that APD decreases from endocardium to epicardium.142 Therefore, midwall core in our patients may promote TWA by uncoupling transmural regions with distinct APD restitution properties.

Although not initially hypothesized, epicardial core was found to be more closely linked to TWA than midwall core. Increased Coreepi% was associated with +TWA, decreased TWAonset and moderately correlated with TWAmax. These results may similarly be explained by intercellular uncoupling. Apex-to-base APD gradients have been observed in the human ventricular epicardium.225 Because intra-epicardial APD gradients are substantially larger than transmural APD gradients,143 uncoupling of epicardial tissue may expose greater difference in APD restitution than uncoupling of transmural tissue. Experimental work also suggests that APD is more randomly distributed across the endocardium and forms no consistent gradient,226 which may account for the lack of relation between TWA and endocardial core in our study. Thus, uncoupling of the epicardium may produce larger disparity in APD restitution properties that more readily promotes APDA discordance and large TWA, than uncoupling of other ventricular regions.

There are several possibilities why gray zone was the scar type most closely associated with TWA in our study. First, gray zone has the ability to promote discordant APDA via multiple mechanisms (i.e. structural and electrical remodelling). Second, gray zone can provoke APDA discordance without being restricted to a specific area of the ventricular myocardium (i.e. a location that specifically separates regions with different APD). Third, gray zone occurred more frequently than any other scar type in our study (Table 3), giving it a greater probability of inducing discordant APDA.

5.2 Clinical Implications

TWA64, 71, 79, 162, 202-205 and myocardial scar183-189, 197, 198 have independently been associated with arrhythmogenesis in patients with cardiomyopathy. However, the proarrhythmic effects of TWA and fibrosis are not necessarily mutually exclusive. Our results paired with prior experimental and clinical observations suggest that fibrosis and alternans may work in concert to provide the substrate for development of lethal ventricular arrhythmias in cardiomyopathy patients.

Clinical studies have found gray zone183, 185 and midwall scar187 to be independent predictors of VT and mortality in patients with cardiomyopathy, but the mechanism by which these scar characterizations initiate ventricular tachyarrhythmias is unclear. As previously discussed, the close relation that we observed between TWA and certain scar types may be due to the presence of underlying spatially discordant APDA. Discordance creates steep gradients of repolarization that can lead to unidirectional block and reentry.112 Furthermore, in experiments by Pastore and colleagues,112, 113 discordant alternans were always observed to precede the initiation of VT or VF.

Schmidt and coworkers183 provided the first direct evidence for the arrhythmogenic potential of gray zone, as defined by LGE CMR, by showing a greater propensity for VT inducibility with this substrate in patients with ICM. The results of our study suggest that the genesis of VT with premature ventricular stimulation may be via TWA in the gray zone. Indeed, Pastore and Rosenbaum113 demonstrated that a premature stimulus delivered in the presence of APDA discordance induced by a structural barrier results in VT more often than VF because the scar acts as an anchor for the reentrant circuit. Thus it is conceivable that ischemic cardiomyopathy patients with greater gray zone will be more likely to develop VT via TWA in response to critically timed premature ventricular beats.

No study has yet explored the arrhythmogenic potential of gray zone in DCM or HCM patients. Nonetheless, the total extent of scar has been associated with greater VT inducibility186 and arrhythmic events188, 198 in HCM. In DCM, the mere presence of fibrosis is predictive of cardiovascular events189 and cardiac mortality.187 We did not perform subgroup analysis of the various cardiomyopathy types due to the limited sample size, but preliminary analysis of the scar composition in our DCM and HCM patient showed a preponderance of gray zone (64%) versus core scar (36%). If the scar in these prior clinical studies with DCM and HCM patients was also primarily composed of gray zone this may explain the arrhythmogenic association with total scar.

Our results also suggest a novel approach to improving the prognostic utility of TWA testing. Although TWA is a valuable non-invasive risk stratification tool, clinical trials have not shown consistent predictive accuracy for SCD.82 It is possible that not all +TWA patients have underlying arrhythmogenic discordant APDA, and in some a +TWA test may simply reflect the

77 presence of less arrhythmogenic concordant APDA. Using LGE MRI to identify the subset of +TWA patients with scar patterns that promote APDA discordance may improve the specificity and positive predictive accuracy of TWA testing. In our study population, there was no SCD or documented VF, but one patient developed VT during follow up. This individual had +TWA and relatively large amounts of gray zone and midwall core. Therefore, patients with +TWA and large amounts of APDA discordance promoting scar, such as gray zone, midwall core and epicardial core, may be at higher risk of SCD.

5.3 Limitations

Our study population was heterogeneous and separate analysis based on the etiology of cardiomyopathy was not possible due to the limited sample size. However, LGE has been shown to correlate with collagen deposition in excised hearts from individuals with ICM,227 DCM187 and HCM.196 Furthermore, experimental histology data reveals that the intensity of LGE reflects the degree of collagen deposition such that bright LGE (core) identifies dense fibrosis that would be nonconductive, whereas intermediate LGE (gray zone) identifies fibrosis intermingled with viable myocytes that can permit conduction.182 Therefore, although each form of cardiomyopathy may have distinct scar distributions and compositions, the electropathological effects of core and gray zone should remain consistent between our patients (i.e. core is nonconductive and gray zone is partially conductive). Second, we measured TWA during AV pacing rather than using traditional exercise or atrial pacing protocols in order to sample heart rates up to 120 bpm without AV Wenckebach. Although AV pacing does not replicate the natural ventricular activation pattern, it has been shown to produce concordant TWA results with similar rate behaviour and fewer indeterminate studies.228 Third, SI thresholding techniques for identifying core and gray zone on LGE CMR have not yet been standardized. The full width at half maximum method was chosen due to its close correlation with pathological data in ischemic cardiomyopathy229 and reliability in defining core scar in nonischemic cardiomyopathy compared to visual assessment.230 However, over estimation of gray zone due to partial volume effects is a possibility and inherent to all thresholding techniques.183 Fourth, large clinical trials suggest that continuing beta-blockers during TWA assessment does not significantly alter +TWA/-TWA results.231 However, beta blockade has been shown to diminish the TWA magnitude in smaller cohorts.91, 92 Although we did not observe a significant difference in +TWA between the patients on and off beta-blockers, it is possible that the TWAmax values were

78 depressed due to the use of beta-blocking agents in some patients. Although no difference in +TWA was observed, ion channel blocking drugs may have similarly altered TWA magnitude. Final, TWA is an aggregate of APDA from both ventricles, but we only quantified scar in the LV. Consequently, myocardial damage in the right ventricle may have contributed to the TWA signal, but it is not reflected in our scar measurements.

5.4 Conclusions

In patients with cardiomyopathy, greater gray zone, epicardial core and midwall core are associated with a +TWA test, larger TWA magnitudes and lower heart rate onset for TWA. These results provide evidence of a structure function relationship between scar and TWA in humans. Furthermore, the existence of gray zone, epicardial core or midwall core in the presence of TWA may reflect underlying discordant APDA; thereby identifying a more arrhythmogenic substrate. With greater understanding of the substrates that promote arrhythmogenic TWA we may be able to improve risk assessment for SCD in patients with cardiomyopathy.

5.5 Future Directions

Cardiomyopathy patients undergoing ICD implantation for primary prevention of SCD will be recruited in order to evaluate the prognostic utility of a new composite risk metric which utilizes both TWA and LGE CMR scar analysis. The hypothesis being tested is that potentially arrhythmogenic discordant APDA is identified when TWA is recorded with certain LGE CMR scar patterns, thereby identifying individuals with a higher risk of ventricular arrhythmias or death. Patients will be followed for 2 years to evaluate clinical events. The expanded cohort will also permit subgroup analysis of ICM, DCM and HCM to determine the relationship between scar and TWA in each type of cardiomyopathy.

Our study also highlights the absence of in vivo human data directly correlating APD alternans to TWA with high spatial resolution. A technically challenging but important clinical study would involve measuring intracardiac APD using multiple monophasic action potential catheters while simultaneously recording ECGs from cardiomyopathy patients during a TWA pacing protocol. In this way, variations in APDA magnitudes and phase may be directly related to TWA magnitudes on the body surface. Furthermore, LGE CMR performed prior to the electrophysiology study

79 could be used to guide catheter placement to core scar or gray zone in order to more directly study the relationship between scar composition and discordant APDA.

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