POTENTIAL UTILITY OF CHANGES IN ENTROPY AS AN ADJUNCT TO THE DIAGNOSIS OF REVERSIBLE MYOCARDIAL ISCHAEMIA

Master Degree of Medical Science

By

JINLIN ZHAO

In

Health Science at the University of Adelaide

And

Cardiology Unit at the Queen Elizabeth Hospital

August 2007

1 TABLE OF CONTENTS

TABLE OF CONTENTS………………………………………………….2 ABSTRACT OF THESIS…………………………………………………5 LIST OF ABBREVIATIONS……………………………………………..8 STATEMENT………………………………………………………….....10 ACKNOWLEDGEMENT…………………………………………….....11 CHAPTER 1 Introduction 1.1 Ischemic Heart Disease (IHD)……………………………………...... 13 1.1.1 Pathophysiology………………………………………………13 1.1.2 Causes of IHD………………………………………………...15 1.1.3 Epidemiology of IHD………………………………………....16 1.1.4 Treatment of IHD…………………………………………...... 18 1.1.4.1 Management of acute anginal episodes……………...18 1.1.4.2 Prophylactic treatment for IHD……………………...18 1.1.4.3 Agents potentially improving outcomes…………...... 20 1.1.4.4 Revascularization ……………………………………21 1.1.4.4.1 Percutaneous coronary intervation………….21 1.1.4.4.2 Coronary artery bypass grafting…………….22 1.2 Electrophysiology of : Cellular Physiology……22 1.2.1 Cellular membrane potentials…………………………………22 1.2.2 Cardiac cell potentials………………………………………...25 1.2.3 “Current injury” in myocardial …………………...... 28 1.3 Diagnosis of IHD………………………………………………………30 1.3.1 Clinical history/clinical examination…………………………30 1.3.2 Electrocardiography…………………………………………..31 2 1.3.2.1 Electrocardiography detection of acute myocardial infarction and/or ischemia………………………………...... 31 1.3.2.2 Electrocardiography detection of intermittent “spontaneous” ischemia……………………………………...33 1.4 Provocative Tests for Myocardial Ischemia…………………………...34 1.4.1 Classification………………………………………………….34 1.4.2 Exercise tolerance testing (ETT)……………………………...36 1.4.2.1 Introduction…………………………………………..36 1.4.2.2 Physiology of ETT…………………………………...36 1.4.2.3 Assessment of ETT…………………………………..39 1.4.2.4 Predictive value of ETT ……………………………..42 1.4.3 Myocardial perfusion imaging (MPI)………………………...44 1.4.3.1 Introduction…………………………………………..44 1.4.3.2 Forms of stress MPI………………………………….49 1.4.3.2.1 Exercise MPI………………………………..49 1.4.3.2.2 Pharmacological stress MPI………………...49 1.4.3.2.3 pacing stress…………………...50 1.4.4 Stress echocardiography………………………………………51 1.4.4.1 Introduction…………………………………………..51 1.4.4.2 Contrast echocardiography…………………………..52 1.4.5 Magnetic resonance imaging (MRI)………………………….53 CHAPTER 2 Electrocardiography and Detection of Myocardial Ischemia: Recent Developments 2.1 Introduction: Electrocardiography: Continued Investigations …...... 55 2.2 Automated ST-segment Analysis……………………………………...57 2.3 Analysis……………………………………………………….60 2.4 QRS Complex Studies……………………………………………...... 60 3 2.4.1 Introduction: general concept of QRS complex…………...... 60 2.4.2 Late potentials of QRS complex……………………………...61 2.5 Signal-Averaged Electrocardiography Techniques……………………61 2.6 High-frequency QRS Complex Studies………………………………..62 2.6.1 Introduction…………………………………………………...62 2.6.2 Studies on high-frequency QRS complex…………………….63 2.7 Entropy Method: A Modified High-frequency QRS and/or ST-segment Method for the Current Investigation……………………………………...67 CHAPTER 3 Detection and Localization of Reversible Myocardial Ischemia during Coronary Angioplasty: Entropy-based Techniques 3.1 Introduction……………………………………………………………71 3.2 Methodology…………………………………………………………...72 3.3 Results…………………………………………………………………79 3.4 Discussion……………………………………………………………...90 CHAPTER 4 Utility of Entropy-based Technology to Detect, Localize, and Quantitate Pacing-induced Myocardial Ischemia 4.1 Introduction……………………………………………………………94 4.2 Methodology…………………………………………………………...95 4.3 Results………………………………………………………………..101 4.4 Discussion…………………………………………………………….115 CHAPTER 5 Conclusions, Limitations, and Further Perspectives BIBLIOGRAPHY

4 Thesis Abstract

Background The 12-lead electrocardiogram (ECG) is a pivotal clinical investigation for evaluations of disorders of myocardial electrophysiology and function. Myocardial ischemia is generally diagnosed on the basis of clinical history, combined with ST segment shifts and T wave changes on resting 12-lead ECG. The ECG is also used as a monitoring tool for assessment of resolution of transmural ischemia following emergency treatment. Because this technology is easy, noninvasive, and inexpensive, it represents a convenient central investigative modality. On the other hand, the 12-lead ECG exhibits very low predictive accuracy for the diagnosis of ischemia in the absence of concurrent symptoms. Even if ECG monitoring is combined with treadmill exercise, the sensitivity and positive predictive accuracy for detection of myocardial ischemia are only around 50% - 75%. Therefore, information from the ECG, combined with exercise test, does not usually have a large influence on clinical decision- making. A number of imaging techniques may be combined with pacing-induced tachycardia or pharmacological stress in order to improve the diagnostic accuracy of such provocative tests for ischemia beyond the level provided by continuous ECG monitoring alone. These include echocardiography, nuclear imaging with single photon emission computed tomography (SPECT) or positron emission tomography (PET) and magnetic resonance imaging. All add to the diagnostic accuracy of the provocative tests performed, but involve considerably incremental costs. The question therefore arises: is it possible to refine continuous ECG analysis during

5 provocative testing in such a way that the diagnostic accuracy of the procedure can be improved? The majority of clinical studies has examined the accuracy or otherwise of the diagnosis of myocardial ischemia utilizing fluctuation of the ST segments during either “spontaneous” ischemia or during provocative manoeuvres (e.g. exercise). As previously stated, the diagnostic accuracy of such analyses tends to be mediocre; when subjected to utility evaluation under Bayesian considerations, they often add little to history/physical examination. However, a number of potential refinements of 12-lead ECG analysis have been proposed, in order to improve both detection and as well as localization and quantitation of ischemia. These include evaluation of a variety of the component waveforms of both the QRS complex and the ST segment of the ECG.

Current experiments The currently described series of investigations arose from preliminary findings that myocardial ischemia in a canine model was associated with transient fluctuations in QRS entropy. Both evaluations performed related to the hypothesis that reversible myocardial ischemia causes transient increases in entropy within QRS complexes and ST segments of the human 12-lead ECG. A series of preliminary experiments suggested that such changes did indeed occur, mainly within the ST segment. The first series of experiments performed compared conventional continuous ST segment analysis within the 12-lead ECG is vs. continuous evaluation of entropy-derived parameters for the localization of ischemia induced by balloon inflation during non-emergency coronary angioplasty. In a series of 103 patients, localization of ischemia was similarly accurate for the entropy-based method and the ST segment assessment method. Ischemic 6 zones were correctly localized by these approaches in 88% and 80% of cases, respectively (p not significant). There was poor concordance between the extent of ST elevation and changes in ST segment entropy. In a small subset of patients with complete and/or ST depression on resting ECG (n=22), entropy-based localization of ischemia was possible in 55% of cases compared with 41% via ST segment assessment (difference not significant). Post hoc analysis revealed that entropy fluctuations arose throughout the ST segment rather than predominantly at the J-point. The second series of experiments was carried out on patients undergoing pacing-induced provocation of possible myocardial ischemia, with scanning via myocardial perfusion imaging (SPECT) examination. As with the first series, 12-lead ECG recording and ST trend monitoring were performed during the pacing procedure. The ST segment deviation and the entropy- based analyses were used for localization of possible ischemia. Data analyses were correlated with myocardial perfusion imaging results. A total 43 patients were studied. Categorization of ischemia via ST segment assessment had only 30% concordance with myocardial perfusion imaging results, while entropy-based analyses had 58% concordance. Therefore neither “conventional” (i.e. ECG-based ST segment analysis) nor novel entropy-based analyses are currently of clinical utility for detection of tachycardia-induced ischemia.

7 List of Abbreviations

ACEi Angiotensin Converting Enzyme inhibitor ACS AMI Acute Myocardial Ischemia APD Action Potential Duration ATP Adenosine TriPhosphate AV Atrial-Ventricle CABG Coronary Artery Bypass Grafting CAD CRP C – Reactive Protein CX Circumflex DBP Diastolic Blood Pressure ECG Electrocardiography ECHO Echocardiography EF Ejection Fraction ETT Exercise Tolerance Testing GTN Glyceryltrinitrate H2O2 Hydrogen Peroxide IHD Ischemia Heart Disease LAD Left Anterior Descending LDL Low Density Lipoprotein LV Left Ventricle MBq Mega Becquerel’s METS Metabolic Equivalents MI Myocardial Infarction MPI Myocardial Perfusion Imaging MRI Magnetic Resonance Imaging 8 PCI Percutaneous Coronary Intervention PCWP Pulmonary Capillary Wedge Pressure PET Positron Emission Tomography RAZs Reduced Amplitude Zones RCA Right Coronary Artery RMS Root Mean Square SAECG Signal-Averaged Electrocardiography SBP Systolic Blood Pressure SPECT Single Photon Emission Computed Tomography UA Unstable

9

Statement

This work contains no material which has been accepted for the award of any other degree or diploma in any university or tertiary institution and , to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference has been made in the text.

I give consent to this copy of my thesis, when deposited in the University Library, being made available for loan and photocopying, subject to the provisions of the Copyright Act 1968.

Jinlin Zhao (February, 2007)

10

Acknowledgements

I would never have had confidence to complete the thesis without support from Professor John Horowitz, my principal supervisor. He spent hours and hours to encourage, instruct, explain, and correct the writing. When I began this project, I had no real research experience and was concerned about methodology. He was so patient and directed me through the study, giving full encouragement. I have learned so much from him. I am so glad to have him as my supervisor. I also would like to thank Dr Angela Kucia. She was the only person with knowledge and experience on GE Marquette ST trend analysis. She spent her own time to teach me how to analyze ST data. She always gave me some suggestion to handle difficult problems. Without her generous assistance, I would not have been able to complete the work. Thanks also to my colleague Dr Antonia Claasz who was responsible for blinded analysis of the entropy data. We spent many times with Professor Horowitz and consumed many cups of “coffee” in the interests of better data analysis. To all staff in the coronary care unit, cardiac catheter laboratory and cardiology department at the Queen Elizabeth Hospital; thanks for your help and support.

11

CHAPTER ONE

INTRODUCTION

12 CHAPTER ONE

Introduction

1.1 Ischemic Heart Disease (IHD)

1.1.1 Pathophysiology of IHD

Ischemic Heart Disease (IHD), a consequence of coronary artery disease (CAD), is a condition that is characterized by inadequate myocardial blood flow relative to the metabolic needs of the myocardium. The lumen of one or more coronary arteries is narrowed or obstructed due to the deposition of cholesterol plaques resulting in haemodynamically significant “fixed” obstruction of blood flow and in impairment of the supply of oxygen and nutrients to the heart musculature, which is essential for proper functioning of the heart.

One form of myocardial ischemia (acute ischemia: ) is engendered by the rupture of tissue of atheromatous plaques, associated with platelet aggregation and thrombus formation 1 2 3. This process may eventually result in a portion of the heart being suddenly deprived of its blood supply, leading to the death of that area of heart tissue (myocardial infarction).

Ischemia is not only associated with a reduced delivery of oxygen and metabolic substrates, but also with a reduced ability to “wash out” products of metabolism. Myocardial ischemia is a condition in which by definition oxygen demand is greater than oxygen supply within the myocardium 4. In other words, there is an imbalance between myocardial oxygen supply and demand 5. Generally, this causes several potential outcomes: (1) prolonged ischemia without cellular necrosis may lead to “stunned myocardium” 13 emerging on reperfusion; (2) severe and prolonged ischemia may induce myocardial infarction; (3) prolonged but less severe ischemia may be reversible without sequelae 6 7.

Myocardial infarction accounts for over half of all deaths related to coronary disease. The incidence of coronary disease is associated with certain characteristic risk factors, such as advancing age, family history of ischemic heart disease, male gender, hypertension, dyslipidemia, cigarette smoking, obesity, sedentary lifestyle, diabetes mellitus and various other genetic predisposing factors 8.

Coronary atherosclerosis is also associated with chronic inflammation, representing the response of the arterial wall to the stress imposed by various risk factors, and probably especially oxidized lipoproteins 9. Acute myocardial ischemia (AMI), including acute myocardial infarction may also arise in part as a result of inflammation, reflecting erosion of the fibrous caps as part of an inflammation process 10 11 12. The evidence in favor of inflammation as a basis for the development of acute coronary syndromes comes primarily from studies linking C-reactive protein (CRP) levels with coronary risk 13 14.

Myocardial ischemia causes biochemical, physiological, and energetic and metabolic changes in the body. When myocardial ischemia occurs, disturbed haemostatic responses include biochemical and energetic changes such as cellular acidosis, failure of calcium sequestration, and increase of inorganic phosphate levels (ATP depletion) that rapidly abolish the contractile activity 15. During prolonged myocardial ischemia and subsequent restoration of the coronary flow, intrasarcomeric actin and 14 myosin continue to interact during diastole leading to impaired muscle relaxation because of failure of calcium sequestration into the sarcoplasmic reticulum 16.

Myocardial ischemia also causes electrophysiological changes especially including a so-called “injury current”, which affects the action potential of cell membranes resulting in prolonged action potentials and prolonged depolarization 17; these are reviewed more extensively in section 1.2.

1.1.2 Causes of ischemic heart disease

The development of ischemia is dependent on an imbalance between myocardial oxygen supply and demand. Thus myocardial ischemia can occur both as a result of increased myocardial oxygen demand, and/or reduced myocardial oxygen supply 4. Myocardial oxygen demand is related to heart rate, contractility, systolic wall pressure and volume, and to extent of diastolic myocardial relaxation. It also varies with the predominant mode of substrate utilization in myocardial metabolism, glucose metabolism being more “oxygen-efficient” than long chain fatty acid utilization 18. In the presence of fixed coronary obstruction, an increase of myocardial oxygen requirements caused by exercise-induced tachycardia, leads to a “demand ischemia”. Most episodes of chronic stable angina reflect these changes.

In other situations, the ischemic imbalance is caused primarily by acute reduction of oxygen supply secondary to increased coronary vascular tone (i.e., ), or platelet aggregation and/or thrombosis, all of which may induce marked reduction or cessation of coronary flow 4. This condition is termed “supply ischemia”, and is responsible for myocardial 15 infarction (MI) and most episodes of unstable angina (UA). However, in many circumstances, ischemia may result from a variable mixture of an increase in oxygen demand and a reduction in supply. The “mixed pattern” angina is an example of this circumstance, being engendered by a combination of tachycardia and increased coronary vaso-motor tone.

Atherosclerotic stenoses in epicardial coronary arteries may be considered as non-linear resistors in series with the downstream arterioles in the coronary circulation. There is extensive physiological regulation of total coronary vascular resistance via fluctuations of tone of the small coronary arteries (i.e. “vasodilator reserve”). The mechanism(s) of this coronary auto- regulation may include both the vasodilator properties of locally released metabolites and autacoids, but may also include the effective “oxygen sensor” role of compounds such as hydrogen peroxide (H2O2) 19.

Thus, when myocardial oxygen consumption is low during resting conditions, the corresponding coronary blood flow is also low irrespective of the presence or absence of a stenosis in a large coronary artery. When a patient who has typical angina begins to exercise, myocardial oxygen consumption increases and local metabolic arteriolar vasodilatation begins simultaneously but the regional increase in coronary blood flow is insufficient to avert nett ischemia 20.

1.1.3 Epidemiology of Ischemic Heart Disease

Ischemic heart disease in its various forms is a leading cause of death and disability worldwide. The incidence of ischemic heart disease is increasing

16 rapidly in many developing countries from their previous low level recently because their traditional life-style have been changed 21.

On the other hand, in many developed countries the age-adjusted incidence is decreasing and mortality has declined 21. These changes reflect improved control of coronary risk factors, and particularly a decline in cigarette consumption 22. However, these changes in the age-adjusted incidence do not reflect life-long incidence, or disease prevalence.

The prevalence of myocardial ischemia in the general population is difficult to ascertain since the actual numbers of ischemic episodes and patients with myocardial ischemia would have to include those with “silent” or minimally symptomatic ischemia 23, many of whom are undiagnosed.

Atherosclerotic coronary heart disease causes approximately 500,000 deaths in the United States each year, i.e., about 1 in 5 deaths overall. The American Heart Association currently estimates (Heart disease and stroke statistics – 2005 update) that approximately 13.5 million United States citizens have either had a myocardial infarction and/or suffer from angina pectoris. The prevalence of ischemic heart disease is highest in the lower socio-economic strata of society. The annual cost burden imposed by coronary disease is estimated an around $140 billion in the United States. Similar considerations apply in most Western European countries, with higher incidence rates in Eastern Europe and some Asian countries such as China and India 24 25 26 22. The major determinants of coronary risk factors are identified by the Framingham investigators, among others 27 and include smoking, hyperlipidemia, hypertension, diabetes, family history of heart disease, and male gender. However, many other possible risk factors for 17 heart disease have also been identified 26; overall, the relationship between coronary risk and events remains incompletely understood.

1.1.4 Treatment of Ischemic Heart Disease

1.1.4.1 Management of Acute Angina Episodes

The only treatment widely validated for this circumstance is glyceryltrinitrate (GTN; nitroglycerine), which accelerates resolution of symptoms when administrated sublingually. The utility of GTN is limited by variability of dose response characteristics and adverse effects due to systemic vasodilatation e.g. headaches, dizziness. Sublingually administrated GTN also has a limited additional role in prophylaxis of angina. Narcotics such as morphine also relieve angina symptoms but they are generally not required.

1.1.4.2 Prophylactic Medication

Prophylactic anti-ischemic agents may be grouped into 4 classes: i: Long-acting Nitrates. The pathogenesis of coronary artery disease is atherosclerosis, which is associated among other things with decreased nitric oxide release from vascular endothelium. Nitric oxide plays an important role to induce vasodilatation and inhibit platelet aggregation. Organic nitrates act as an exogenous nitric oxide source which can be supplied directly to the blood vessel wall, resulting in vasodilatation both systemically and in the coronary circulation. Furthermore, the vasodilator effects of nitrates result in decreased venous return and therefore may decrease cardiac work via

18 preload reduction. Thus, nitrates may decrease oxygen demand as well as increasing oxygen supply. Nitrates also decrease platelet aggregation and consequent thrombosis formation 28 29, which is of most relevance in acute coronary syndromes. ii. β - adrenoceptor antagonists. These agents act as competitive inhibitors of circulating catecholamine effects on β-adrenoceptors. They therefore reduce heart rate and blood pressure (especially during exercise), resulting in diminution of oxygen demand. There is good evidence that some β-adrenoceptor antagonists improve outcomes in patients with systolic , or after substantial myocardial infarction 30 31. iii. L- channel Calcium antagonists. Calcium antagonists have been divided into two groups: dihydropyridines such as nifedipine, amlodipine, felodipine and non-dihydropyridines such as diltiazem and verapamil. The dihydropyridine groups have greater selectivity for vascular smooth muscle rather than myocardium, and are predominant vasodilators 32. The non-dihydropyridine group tends to decrease heart rate, which may contribute to their greater anti-ischemic effects 33 34. iv. “Metabolic” agents. There is an increasingly well understood group of anti-anginal agents which act primarily by altering the metabolism of the heart to make its more efficient 35. Agents of this type, such as perhexiline are currently in limited clinical use.

19 1.1.4.3 Other Agents Potentially Improving Outcomes in Patients with Myocardial Ischemia

Apart from the various anti-ischemic agents (discussed above), a number of other classes of drugs are of potential value in patients with ischemic heart disease. Such agents include: i. Anti-aggregatory agents: These agents include oral aspirin, clopidogrel and intravenous glycoprotein IIb/IIIa antagonists. These agents inhibit platelet activation and reduce the release of prothrombotic and pro-inflammatory products, thus preventing further blood aggregation and thrombus progression. ii. Lipid-lowering drugs: Elevations of serum cholesterol, and/or triglyceride, and/or low-density lipoprotein (LDL) levels are strongly associated with coronary atheroma. In particular, statins such as pravastatin, simvastatin, and atorvastatin can be used to treat hyperlipidaemia and in most cases achieve normal or “low normal” total cholesterol and LDL levels. A number of studies have suggested that approximately 1% reduction in serum cholesterol level is associated with an intermediate duration reduction in coronary events and mortality of around 2-3% 36 37. It remains to be seen whether non-statin lipid-lowering drugs also affect mortality, and whether the beneficial effects of statins reflect purely their reduction of atheromatous burden: statins also exert a number of “pleiotropic” effects, such as suppression of inflammation and stimulation of nitric oxide release 38.

20 iii. Angiotensin converting enzyme inhibitors (ACEi) ACE is a widely distributed dipeptidase which among other effects, converts angiotensin I to II (activating process), and bradykinin to heptapeptide (inactivating process). ACEi’s exert anti-hypertensive effects, presumably partially via decreasing angiotensin II levels and increasing bradykinin levels. However, recent studies have revealed that some ACEi’s exert cardio-protective effects in patients with known or potential myocardial ischemia. The mechanisms whereby some ACE inhibitors (e.g. ramipril, perindopril) 39 40 but not all (e.g. trandolapril) 41 have these beneficial effects, are currently uncertain.

1.1.4.4 Treatments of Coronary Revascularization

1.1.4.4.1 Percutaneous Coronary Intervention (PCI)

One of the most common treatments for myocardial ischemia is PCI. The procedure involves dilatation of stenosed and/or occluded coronary arteries by using special designed “balloons” plus or minus stents. The purpose is to remove any physiologically relevant nett large coronary obstruction. PCI currently carries very high anatomically based procedural success rates, both for isolated coronary stenoses and for acute coronary occlusions 42, for example in associated with acute myocardial infarction. Therefore, its use is increasing rapidly, despite potential economic constraints and concerns about late restenosis and/or stent thrombosis 43. Importantly, in the context of this thesis, PCI is widely perceived to be the treatment of choice for patients with stable angina pectoris who continue to have symptoms on medical therapy and have suitable coronary anatomy (i.e. small numbers of stenoses, no chronically occluded vessels). However, the long-term

21 advantages of PCI over medical therapy in stable angina are minimal in most cases 44.

1.1.4.4.2 Coronary Artery Bypass Grafting (CABG)

This surgical procedure uses vein and/or arterial segments to “bypass’ diseased segments within coronary arteries. CABG is an effective long-term treatment for patients with angina pectoris as regards symptomatic relief. While CABG has not shown any survival benefits over medical therapy for most patients, in view of the previously demonstrated prognostic advantages of CABG in patients with extensive ischemia, CABG tends to be utilized in patients with multiple stenoses, especially, if the left main coronary artery is involved 45.

1.2 Electrophysiology of Myocardial Ischemia: Cellular

1.2.1 Cellular Membrane Physiology

Myocardial ischemia causes increases in extracellular potassium concentration, depletion of ATP, and prolonged depolarization. These cellular changes generate “injury currents” between ischemic and normal cells leading to electrophysiological changes 17 46 47

From the point of view of this thesis, it is important to consider myocardial ischemia as a process which disturbs electrical homeostasis within the ventricular myocardium, with regional variability according to extent and site of ischemia.

22 Normally, the resting membrane potential is maintained as a consequence of different trans-membrane ionic gradients and of different relative membrane permeability. The movements of various ions through cell membrane create currents, which may either be by-product of the transport process or important biological event themselves. Any events occurring, which induce concentration changes of these ions, also affect excitability of cell membrane and voltage fluctuation.

The serial components of a single cardiac action potential have been defined conventionally as rapid depolarization (phase 0); immediate fast repolarization (phase 1); a plateau maintained depolarization or very slow repolarization (phase 2); final repolarization (phase 3); and diastolic or resting potential (phase 4), as depicted in figure 1.1.

23 Figure 1.1: 4 phases of the action potential in a cardiac cell without “spontaneous” depolarization and corresponding ECG changes. Phases 0: the rapid depolarization due to opening of the fast Na+ channel. Phase 1: early partial repolarization due to the efflux of K+ and closing of the fast Na+ channels. Phase 2: plateau phase due to a balance of movement between inward currents and outward currents. Phase 3: final repolarization primarily due to opening of the slow delayed rectifier K+ channels resulting in net outward positive currents and causing the cell repolarization. Phase 4: restoration of the resting membrane potential due to efflux of K+ slightly exceeding the influx of K+ through same channels.

Note: Phase 0 and 1 correspond approximately to the R and S waves on an electrocardiogram (ECG). Phase 2 corresponds to the ST segment on the ECG. Phase 3 corresponds to the T wave on the ECG.

24 Excitability is the property of membranes to respond out of proportion to a stimulus causing depolarization (action potential) 48. This important characteristic is easily demonstrated by contrasting it with the passive response of membrane resting potentials. An excitation response must be a result of major changes in the membrane properties. Cardiac and muscle cells are able to change the permeability of their surface membranes by the opening and closing of ion channels, and in this way to generate a depolarization - repolarization phase during the cardiac cycle known as an action potential (see previous page). This action potential also serves to transmit electrical impulses along cells or between cells.

1.2.2 Cardiac Cells Potentials

Action potentials of myocardial cells generally start from the sino-atrial node, then spread rapidly through the atria, through the atrio-ventricular node (AV node), and then rapidly via His-Purkinje fibers to all parts of the ventricles. The initial depolarization in atrial and ventricular myocardium, and in the His-Purkinje system is primarily due to Na+ influx through cell membranes via rapidly opening Na+ channels 49 50. When a balance is achieved between residual sodium currents, developing L-channel calcium currents (activated on partial depolarization), and developing outward potassium currents, the nett depolarization phase is completed. The subsequent plateau phase is produced by a balance between calcium ion (Ca2+) influx, more slowly opening Ca2+ channels and potassium ion efflux through membrane K+ channels. Finally, the repolarization phase is predominantly related to potassium ion efflux via a range of potassium channels. A schematic of some of the major transmembrane ion channels is shown in Fig 1.2.

25 Each region of the heart has its own characteristic action potential. The SA and AV node have slow conduction velocities and potentials. The action potential in atrial and ventricular myocytes is quite sensitive to vagal activity via acetylcholine release. The His-Purkinje cells have the most rapid depolarization rate and the highest condition velocity 51. These cells also have the longest action potentials. The electrical activity of the heart depends upon the distribution of ions in muscle fiber cells. The distributions of ions rely on trans-membrane permeability of ions, trans-membrane potential difference that net amount of ions diffuse across the membrane.

Action potentials reflect the underlying electrical activities of cardiac cells. The activity of the sodium-potassium ATPase system maintains a high concentration of intracellular potassium with reciprocal extracellular concentrations at rest. The currents may be classified as inward and outward currents: the inward currents depolarize cell membranes. See figure 1.2. The cell membrane is eventually repolarized when a range of outward currents are activated. The primary outward currents utilize potassium (K+) and chloride (Cl+) fluxes 52 53. Large numbers of different potassium channels have currently been described and cloned, including delayed rectifier, K- ATP and voltage activated K+ channels 48 53.

The physiology of the outward currents is fundamental to cellular repolarization, which corresponds to the ECG components conventionally studied for ECG diagnosis of ischemia 52. Therefore, pathology of potassium channels is relevant to ECG evidence of ischemia.

26

Figure 1.2 Schematic diagrams of major transmembrane ion channels and ion fluxes within sarcoplasmic reticulum. Inward currents include: Sodium channels (I Na a, b) and various Calcium channels (I Ca b, T, L). The various K+ channels (I K ATP, I, r, s) reduce nett outward currents while there are also a variety of exchange currents, such as the Na+/Ca+, Na+/K+ exchange channels 48.

27 1.2.3 “Injury Currents” in Myocardial Ischemia

Myocardial ischemia causes local increases in extracellular potassium concentration in ischemic zones 47. The resultant increase in concentration of extracellular potassium ions (K+) induces conditions which are fundamentally different to the normal cellular-physiological environment. (i.e. concentration of K+ far greater inside of muscle cells and concentration of Na+ higher outside of cells). Thus, the affected muscle cells become partially depolarized during diastole causing a shortening of the action potential (figure 1.3).

Furthermore, ischemia with insufficient blood flow results in insufficient oxygen supply to . Reduced availability of oxygen at the cellular level results in impaired aerobic myocardial metabolism, resulting in a decrease in ATP production. This energetic depletion in turn impairs myocardial contraction and relaxation.

The ECG changes associated with ischemia include ST segment fluctuations 54, which are partially related to increased extracellular potassium concentrations (figure 1.3). In general, if the ST segment shifts downward, this suggests injury currents primarily within the subendocardium 55, while if the ST segment shifts upward, this suggests more extensive injury currents (“transmural ischemia”) 55. The usually accepted threshold for diagnosis of myocardial ischemia is that the ST segment deviation is greater than 0.1mV (or 1mm) from the isoelectric region.

28 Figure 1.3. Simulation data: Relationship between changes in action potential and underlying extracellular K+ concentration changes that have been correlated with actual experimental ECG. The horizontal axes represent time (milliseconds) and the vertical axes represent voltage changes on simulation of K+ concentration from M-cell and epicardium regions, and surface ECG, also from experiment ECG. Hypokalemia prolongs the QT interval and flattens the T wave. On the other hand, hyperkalcemia shortens the QT interval and increases the amplitude of the T wave. Dashed lines indicate that Ikr (fast component of the delayed rectifier potassium current) channel was also affected during changes of extracellular potassium concentration 53.

29 1.3 Diagnosis of Ischemic Heart Disease

1.3.1 Clinical History/Physical Examination

The diagnostic process regarding myocardial ischemia depends in part on whether patients develop symptoms. Myocardial ischemia may be largely or entirely asymptomatic 23. This tends to be particularly the case in diabetic subjects and the elderly, although theoretically the classic example of painless ischemia should be that occurring in a recently transplanted heart.

In all cases, the probability of presence of fixed coronary disease may be assessed by obtaining data on conventional coronary risk factors (e.g. male gender, advanced age, cigarette smoking, hyperlipidaemia, hypertension, diabetes) 8. These a priori probabilities interface with other diagnostic processes, modulating the predictive accuracy of all “diagnostic” tests (for example, see section 1.4) according to Bayesian considerations.

The presence of symptoms such as intermittent chest pain therefore provides variable assistance in the diagnosis of angina pectoris (reversible ischemia) and/or acute myocardial infarction (evolving ischemic cell death). Many patients have symptoms which are not clearly diagnostic of ischemia, and conversely symptoms of chest wall, pulmonary, pericardial or even upper abdominal origin may be difficult to differentiate from myocardial ischemia. In general, the reliable diagnosis of myocardial ischemia from history alone has proved particularly difficult in females 56, although the basis for this remains controversial.

Physical examination alone provides little or no diagnostic information in the majority of cases of reversible myocardial ischemia. This is despite the 30 fact that ischemia is predictably associated with regional impairment of myocardial relaxation 19, and therefore potentially with signs of elevation of left ventricular filling pressures. Impediments to diagnosis of ischemia or physical examination include the episodic nature of ischemic symptoms and the lack of specificity of diastolic dysfunction as a manifestation of ischemia.

Thus in summary, patients’ clinical history details are often useful, but are not sufficiently reliable to diagnose the majority of cases of non- catastrophic myocardial ischemia. Furthermore, there is current evidence that early detection of asymptomatic ischemia improves outcomes. This has led to wide developments of diagnostic tests, varying greatly in complexity and incremental utility over clinical data.

1.3.2 Electrocardiography (ECG)

1.3.2.1 ECG Detection of Acute Myocardial Infarction or Ischemia

The resting ECG is a potentially sensitive tool for detecting current or recent myocardial ischemia. Performance of a resting ECG is a key component of proper assessment of any patients with a suspected acute coronary syndrome (ACS). Extensive myocardial ischemia can generally be diagnosed in a range of abnormalities of ECG: deviation of ST segments, and abnormalities of T waves.

Myocardial ischemia commonly causes depression of the ST segment, often with associated T wave inversion. This primarily reflects changes in extracellular potassium concentration which modify repolarization primarily via IKr and IKs channel conductance 57 (also see section 1.2).

31 ST elevation implies transmural ischemia but only potentially extensive subsequent infarction. For example, elevation of ST segments can appear and disappear within a few minutes and leave no permanent sequelae, as occurs in some cases of coronary spasm 58 or during elective coronary angioplasty. This is called transient transmural ischemia.

However, the ECG is essentially defective in several ways as a diagnostic test for both myocardial ischemia and evolving infarction. Firstly, it often fails to detect “smaller” degrees of myocardial ischemia or infarction. Secondly, the diagnostic accuracy of the ECG depends on the region of the heart involved with diminished negative predictive accuracy, for example, in the case of posterior wall ischemia 59. Finally, the detection of transient anomalies in an ECG (as occur with ischemia) is affected by whether or not the “resting” ECG is normal or not. Unfortunately, many patients at risk of recurrent (as distinct from de novo myocardial ischemia) have abnormalities on the resting ECG. In particular, the presence of ST segment depression and/or complete left or right bundle branch block on the resting ECG limits the accuracy of ECG detection of ischemia 60 61 62.

Thus, in many cases, a “negative” ECG does not markedly diminish the probability of presence of concurrent ischemia. This is discussed further in section 1.4.6. Holter monitoring or twenty-four-hour ambulatory ECG monitoring may be used to detect episodes of myocardial ischemia, both symptomatic and silent. However, the limitation of Holter monitoring in the diagnosis of myocardial ischemia is the lack of predictability of either ischemic symptoms or stress leading to ischemia within a specific 24-hour period.

32 1.3.2.2 ECG Detection of Intermittent “Spontaneous” Ischemia

The utility of ECG for diagnosis of prolonged myocardial ischemia has been discussed in section 1.3.2.1. However, some patients exhibit numerous transient episodes of myocardial ischemia, not all of which are symptomatic 63 64. The detection of such episodes of ischemia may be achieved with continuous ECG monitoring, whether the patient is ambulant or on an in- patient basis, for example within a coronary care unit.

There are a number of potential technical limitations to such approaches. Specifically, as “conventional” measures of ischemia rely upon quantitation of ST segment shifts, the frequency response characteristics of the equipment utilized must be adequate for detection of minor charges 65. Secondly, artifacts may be a problem, particularly for ambulant patients’ ECG. Thirdly, the detection of ischemia is optimized by the use of a full 12- lead ECG: however, the majority of systems for ambulatory ECG detection utilize only limited lead systems, usually one or three leads. In additional, women and/or in young age (<65 years) are more difficult to be presented ST abnormalities for myocardial ischemia on ECG 66 56.

Despite these difficulties, there is a considerable literature documenting the utility of in-hospital continuous ECG monitoring for detection of ischemic episodes 65. The technology utilized in Chapters 3 and 4 of this thesis (the GE Marquette system for ST segment/T wave analysis) has been the subject of previous publications examining determinants of ischemia 67 68. As regards the detection of ischemia on ambulatory ECG monitoring, this remains a somewhat controversial basis for therapeutics, despite extensive

33 trials utilizing validated “technologies” 69. This particular technology is not of direct relevance to the work performed in this thesis.

1.4 Provocative Tests for Myocardial Ischemia

1.4.1 Classification

Episodes of myocardial ischemia are classically precipitated by increases in myocardial oxygen demand and/or episodic reductions in regional coronary flow. By definition, provocative tests seek to induce myocardial ischemia, which is then detected by various means. The various available tests are summarized in table 1.1.

34 Table 1.1: Classification of provocative tests for myocardial ischemia

1. Means of induction of ischemia

1. Exercise (1) Bicycle (2) Treadmill 2. Production of tachycardia by non-exercise means (1) Catecholamine infusion (2) Temporary pacing 3. Production of coronary “steal” (1) Dipyridamole (2) Adenosine 4. Induction of coronary spasm (1) Acetylcholine (2) Ergonovine

2. Means of detection of induced ischemia

1. ECG (various methods) 2. Echocardiography (various methods) 3. Magnetic resonance imaging 4. Myocardial perfusion imaging (various methods) 5. Positron tomography imaging 6. Direct visualization of coronary flow/diameter

The various combinations are discussed below.

35 1.4.2 Exercise Tolerance Testing (ETT)

1.4.2.1 Introduction of ETT

ETT is a widely, commonly used cardiovascular test for evaluation of possible myocardial ischemia in patients. It is a well established, safe, relatively inexpensive, and widespread clinical generally procedure. It is performed by using either treadmill or bicycle ergometer with simultaneous blood pressure monitoring. Bicycle exercise is cheaper and more convenient than treadmill, but it is not as suitable for patients who may be not familiar with regular bicycle - riding. Treadmill exercise represents an easy way to reach maximal heart rate and oxygen consumption level in most patients.

Indications for termination of ETT can be either development of symptoms and/or observed signs/abnormalities. Symptoms include chest pain or discomfort, dyspnoea, dizziness, cyanosis or pallor, general or leg fatigue. Observed signs include decreased systolic blood pressure, serious , progressive ST and/or QRS changes, or development of bundle branch block. In general, the blood pressure increases as cardiac workload increases.

There are large numbers of protocols designed for treadmill electrocardiography testing. The standard Bruce protocol is widely used clinically 70. A “modified” Bruce protocol is designed for elderly individuals and includes 3 minutes warm up with normal speed no any incline, then increases incline at a low grade without increasing speed.

36 Other protocols which are commonly used clinically for treadmill exercise have been designed by Ellestad 71, and Weld 72. Their respective merits are beyond the scope of this thesis; however, the key issue is that none of them has been shown to be “optimal” regarding the precipitation of detectable ischemia in an unselected population.

Cardiac workload achieved on the treadmill is generally expressed in metabolic equivalents (METs) theoretically. This is calculated based on oxygen consumption relative to individual’s body weight. The oxygen consumption can be expressed as ml per kilogram per minute. It depends on each physical condition and body weight. One MET equals 3.5 ml per kilogram per minute oxygen consumption and equals the average number of resting oxygen consumption. Oxygen consumption rises more rapidly with the Bruce or Ellestad protocols than most other protocols. Presumptive oxygen consumption can also be calculated by products of heart rate and systolic blood pressure (the so-called “double product”) in clinical exercise. However, many factors may affect the heart rate responses to exercise. Age, gender, position, some medications such as beta-blockers, and calcium antagonists, physical conditions, and coronary artery disease may all affect maximally heart rates and level of oxygen consumption attained.

1.4.2.2 Physiology of ETT

The normal cardiovascular system can be stressed by exercise (dynamic exercise), or pacing techniques or some drugs (isometric exercise). The stress causes physiological changes in body system. Assuming exercise is used, there are normal physiological responses. A stress exercise test can be

37 subdivided into pre-exercise, exercise, and post-exercise stages according to physiological responses to exercise.

In the pre-exercise stage, cardiac output is increased by an augmentation in stroke volume. The increase in cardiac output in the later phases of exercise is due primarily to an increase in ventricular rate.

As exercise progresses, blood flow through muscle is increased in parallel with oxygen demand. Systolic blood pressure (SBP) and pulse pressure increase, while diastolic blood pressure maintains approximately constant. Overall, cardiac output increases and peripheral resistance decreases. Meanwhile norpinephrine is released from sympathetic postganglionic nerve endings throughout exercise. The increasing level of norpinephrine in the blood stream may contribute to increases in myocardial contractility during exercise. The pulmonary arterial pressure, pulmonary capillary wedge pressure, and the right atrial pressure may increase as well due to increased blood flow. During the exercise period, oxygen demand and consumption increase dramatically. In a normal cardiovascular system, these hemodynamic changes will return to baseline level within few minutes after termination of exercise.

In the post-exercise phase, the vagal system is dominant and hemodynamics return to baseline over a few minutes.

Due to decreased beta-adrenergic responsiveness, elderly patients may exhibit limited maximum heart rate and cardiac output responses to exercise. The issue that arises from this limitation is whether the exercise test is a valid way of assessing possible induction of ischemia in the elderly. 38 In fact, most studies of treadmill exercise have been performed predominantly in middle-aged (36-53 yrs) male patients 73 74 75. With the recent ageing of the population being screened for cardiac disease, and in particular ischemia, this lack of detailed information about elderly subjects is unfortunate. The lack or limitation of definitive information on treadmill exercise in the elderly may have contributed to the development of other diagnostic techniques for use in this population.

Conventionally, any patient who reaches 80% of the expected maximal heart rate without symptoms and signs of ischemia developed is deemed to have had a negative result. Conversely, a patient who develops typical chest pain with progressive exercise during testing, together with ECG changes, is termed to have had a “positive” test.

1.4.2.3 Assessment of ETT

The most common manifestation of exercise-induced myocardial ischemia is ST segment depression on the standard surface ECG 76 71. Myocardial ischemia generates electrical gradients between normal and ischemic zones, which are expressed as ST shifts downward. The standard criterion is ST segment depression greater than 1.0 mm, with horizontal or down-sloping ST segment depression quantities 80ms after the J point. Up-sloping ST depression may also occur. However, down-sloping ST depression is more specific for presence of coronary artery disease compared to horizontal or up-sloping ST segment changes 71 77.

Furthermore, the diagnosis of ischemia on the basis of ST segment fluctuations during exercise is seen to involve “grey area”: probability of a

39 “true positive” test is influenced by concomitant symptoms, extent of ST depression, number of leads involved, ST segment morphology and associated haemodynamic changes. The additional Bayesian implications of the test are considered on page 42. An example of positive exercise tolerance test is shown in figure 1.4.

40

Figure 1.4: ST segment data summary of a single patient undergoing exercise testing. Note development of ST depression in leads V2-V6. Particularly, V4, V5, and V6 (correlated with lateral region) leads.

41 Changes in the ECG during ETT in male and female patients with coronary artery disease may provide different clinical information 78 79.

The value of ETT is conventionally categorized via sensitivity, specificity, and predictive value. ST segment depression is not specific for coronary disease. In most studies, exercise-induced ST segment depression associated with CAD has a sensitivity around about 50-70% and a specificity around about 70-90% 80. There are many false positive ST segment depression responses associated, for example, with anemia, , coronary artery spasm, severe hypertension, left , Wolff- Parkinson-White syndrome, electrolyte abnormalities, bundle branch block, drug-induced (digoxin treatment), glucose ingestion, and spontaneous ST depression 71. These potential bases for “false positive” tests will influence the decision whether or not to perform ETT and the interpretation of results if ETT is performed.

1.4.2.4 Predictive Value of ETT

As we discussed above, ETT may be a useful method for diagnosis of induced ischemia. However, many studies have been performed to evaluate the value and limitations from ETT in this regard. These studies have shown that ETT has only approximately 60% - 70% sensitivity and 60% - 80% specificity for the diagnosis of coronary artery disease 81 82 73 76.

Overall, most results showed that the diagnostic value of ETT was low in asymptomatic patients; this illustrates the Bayesian implications of all diagnostic tests. Particularly, ETT in women has a lower diagnostic accuracy for coronary artery disease 81 73; the mechanism is unclear. Ignoring the lower incidence of ischemic heart disease in pre-menopausal 42 women, other possible explanations include the higher prevalence of resting ST segment anomalies in females, the potential occurrence of “cardiac syndrome X”, reflecting small coronary artery dysfunction 83, and poor exercise tolerance in ageing women.

In order to determine the incremental clinical value of exercise ETT in a variety of scenarios, Goldman et al 74 designed a multivariate model taking into account clinical history. The basis for Goldman’s study was that in many patient populations, clinical data available before ETT provide strong positive or negative predictive information related to the presence/absence of “fixed” coronary disease. In the first of component of his study, the multivariate analysis model was performed on 3840 patients who underwent coronary angiography procedure utilizing information from the Duke medical centre data bank.

Firstly, it is important to mention that within this population, 65% of patients had >70% “fixed” coronary stenoses. Significant pre-ETT parameters correlated with presence of CAD included typical pain, Q waves on ECG, (male) gender, history of AMI, smoking, hyper- cholesterolaemia and advance age while none of these are surprising, combined use of these seven parameters generated a model with overall 84% predictive accuracy pre-ETT for this population.

Secondly, having derived this model retrospectively, Goldman then tested it prospectively on a cohort of 324 further patients with similar clinical characteristics, all of whom underwent ETT and coronary angiography. The pre-ETT parameters proved equally predictive in this cohort. The key aspect of the study was the incremental contribution of ETT to this pre-test 43 information. Of the various data generated by ETT, (essentially) extent of ECG changes proved useful incrementally. Incorporation of ETT data into the model only increased its predictive accuracy to 87%, a very small gain.

Finally, Goldman et al explored the potential value of ETT for correctly crossing decision-making thresholds. Overall, as predicted from the minor incremental value of ETT data, ETT results only marginally improved decision-making. Assuming that a threshold probability of 25% activates decision towards angiography, patients with pre-ETT probability of CAD of 25 - 50% benefited most from ETT, in this case, by about 26%. Therefore, ETT can be seen as a limited diagnostic tool which is the best employed in patients with moderate pre-test probability of CAD.

Consistent with these finding, the American Heart Association (AHA), the American College of Cardiology (ACC), and the US Preventive Services Task Force (USPSTF) do not recommend routine ETT in healthy asymptomatic individuals. It is generally agreed that the ETT may be value in individuals with at least an intermediate risk of CAD 84; it also may be useful for predicting death from CAD when it combined with the European global risk SCORE 27.

1.4.3 Myocardial Perfusion Imaging, MPI (Nuclear Medicine Imaging of the Heart)

1.4.3.1 Introduction of MPI

The most commonly utilized forms of MPI utilize intravenously administered radiopharmaceuticals (thallium-201, or technetium-99m-labed agents such as sestamibi and technetium tetrofosmin) to image and assess

44 coronary blood flow to the myocardium. This technology is based on single photon emission computed tomography (SPECT) and is able to provide color-contrasted images in different views related to the presence, the sites, and extent of stress-induced perfusion abnormalities, and also whether or not these abnormalities represent reversible ischemia.

This technology represents a noninvasive diagnostic technique. It also can be used to assess myocardial function and quantitate myocardial viability. It accurately detects myocardial ischemia and quantitatively evaluates extent of ischemia for patients with either known or suspected CAD 85 86. Furthermore, it can evaluate the size of infarcts. In addition, it can be utilized simultaneously to quantitate ventricular systolic function 87.

The principle of MPI is based on the concept of “coronary blood flow reserve”. During stress, particularly dynamic exercise, oxygen demand of the myocardium increases in response to the increased cardiac output leading to homeostatic coronary vasodilatation. “Coronary blood flow reserve” is the proportional difference in blood flow between resting and maximally dilated coronary flow. Myocardial ischemia, whether exercise- induced or pacing- or drug-induced or spontaneous, can result in an absolute reduction in regional myocardial blood flow. More commonly, if there is a stenotic lesion in a coronary artery, blood flow distal to the lesion is reduced compared with that to the normal areas of myocardium, leading to reduction of the blood flow reserve in that region. This corresponds to a ‘defect’ area on imaging – really an area of diminished coronary reserve in most cases. Either planar or single photon emission computed tomography (PECT or SPECT) technologies are able to detect and quantitate these changes of blood flow reserve. 45 Quantitation of reversible ischemia, by definition, requires paired imaging; therefore all patients in whom an initial “stress” study shows a defect should subsequently undergo a repeat study at rest.

Figure 1.5 shows two SPECT studies: Panel A shows a normal study (no re- injection for rest imaging) while panel B shows a patient with substantial ischemia corresponding to the distribution of border-zone of the circumflex coronary artery (CX) and infarction in the territory of the right coronary artery(RCA).

46

Figure 1.5A: Normal myocardial perfusion imaging from short axis, horizontal long axis, and vertical long axis views.

47

Figure 1.5B: MPI imaging after stress (upper panels of each pairs) and at rest (lower panels of each pairs). In this case, there is partial reversibility of perfusion “defect”, largely in the circumflex artery (CX) region. (see: 4 clock position: CX, reversible “defect” from stress to rest and 5-8 clock position: RCA, fixed “defect”).

48 The combination of ETT with SPECT imaging increases the diagnostic accuracy for the presence of significant CAD. For example, Guerra et al 88 reported sensitivity and specificity rates of 96% and 84% respectively for detection of coronary disease utilizing SPECT with technetium imaging. While various authors have also documented prognostic implications of SPECT results 89 90, these results are not primarily relevant to the experiments described in this thesis.

1.4.3.2 Forms of Stress for MPI

1.4.3.2.1 Exercise MPI Exercise represents the most commonly utilized provocative test for induction of ischemia; MPI is commonly combined with treadmill exercise to improve diagnostic yield.

Exercise MPI can identify and quantitate multivessel ischemia or infarction. Most published results showed that sensitivity and specificity of stress MPI was greater than 90% 91. Stress myocardial perfusion scintigraphy is particularly helpful in detection of significant CAD in patients with abnormal resting ECG findings and those in whom ST-segment responses cannot be accurately interpreted, such as patients with left bundle-branch block or LV hypertrophy. On the other hand, stress MPI is a relatively expensive test compared with ETT alone; hence, a relevant issue is the cost- benefit implications of such tests: this issue has never been addressed adequately.

1.4.3.2.2 Pharmacologic Stress MPI

49 In patients in whom induction of ischemia by exercise is not practicable (for example because of concomitant orthopedic or lung disease), it may be possible to induce ischemia pharmacologically, either by induction of tachycardia, for example with dobutamine infusion 92, or by induction of asymmetric coronary vasodilatation and coronary “steal”, for example with adenosine or dipyridamole 93. Both of these methods are in common clinical use for screening infirm patients for ischemia.

1.4.3.2.3 Tachycardia Pacing Stress

In theory, myocardial ischemia can be induced without exercise, simply by increasing heart rate, and hence myocardial oxygen demand. Hence, temporary pacing offers a potential means for stress testing in infirm individuals. This form of provocation is invasive and expensive, requiring either intra-cardiac or trans-esophageal pacing, and is therefore, of very limited practicality. However, it may be regarded as more “physiological” stress, for example, dipyridamole. There is a limited literature on diagnostic pacing in complication, with SPECT imaging in most cases this has involved pacing via the right atria.

For example, Stratmann et al 94, utilizing atrial pacing in patients with limited exercise capacity, demonstrated that presence of thallium perfusion defects predicted adverse outcomes. Worthley et al 95 demonstrated utility of atrial pacing as a component of ischemia detection protocol in patients with chronic renal failure.

50 1.4.4 Stress Echocardiography

1.4.4.1 Introduction

Echocardiography imaging can potentially be utilized to detect inducible ischemia. However, induction of ischemia will be contraction and/or relaxation, while perfusion will not be visualized directly utilizing normal echocardiography. Nevertheless, stress echocardiography offers substantial incremental diagnostic yield for detection of ischemia: - as with MPI, such stress may be exercise, or pharmacological in nature 96 97. The detection of ischemia utilizing stress echocardiography requires considerable operator expertise: - in addition to the detection of changes in regional wall motion 98, there is increasing evidence that concomitant tissue Doppler imaging/stress imaging may improve diagnostic accuracy 99.

Exercise induced stress echocardiography is useful in evaluation of patients with suspected chronic CAD. The test is more sensitive and accuracy than ETT. Published studies have shown that stress echocardiography has very similar accuracy as the stress MPI for detection of coronary disease 100.

American College of Cardiology/American Heart Association (ACC/AHA) guideline suggested that pharmacological stress echocardiography is a validated technology for the diagnosis and prognosis of coronary artery disease 90. Either dobutamine or dipyridamole showed effective risk stratification for the induction of ischemia 101 90. Stress echo and stress MPI provide similar accuracy in detecting CAD. Dipyridamole stress Echo showed far greater specificity than ETT to that of patients with suspected coronary artery disease; however, the two methods had similar sensitivity values 102.

51 1.4.4.2 Contrast Echo (Real Time Contrast Echo)

A rapidly evolving field in noninvasive testing for diagnosis and assessment of CAD utilizes echo contrast myocardial imaging. A major objective is development of intravenous ultrasonic contrast agents for noninvasive echocardiography examination. Echo has the potential for evaluating transmural distribution of blood flow heterogeneity, velocity reserve and detecting changes in subendocardial perfusion. While it is accurate in detecting transmural myocardial infarction 103, its efficacy regarding diagnosis of reversible ischemia is less clear. Furthermore, the technology has not yet been widely used clinically due to poor availability of appropriate ultrasonic contrast agents and technical skill required 104.

1.4.5 Magnetic Resonance Imaging (MRI)

The MR technique has superior spatial resolution, multiplanar nature imaging, and high reproducibility characteristics compared to most other imaging modalities. It can be used to create alternative imaging modalities to evaluate cardiac structure and function. It can detect both subendocardial and transmural myocardium perfusion defects 105. The technique can also assess possible myocardial ischemic events by evaluation of regional wall movement, myocardial perfusion, and/or contrast/delayed enhancement imaging. It may thus detect both myocardial ischemia and/or viability. There are no definitive comparisons to date of the predictive accuracy of stress MRI vs. nuclear modalities for detection of inducible ischemia 87 106 107.

Nagel’s study 107 determined that MRI had 88% sensitivity, 90% specificity, and 89% predictive accuracy for diagnosis of patients with suspected 52 myocardial ischemia and was more sensitive for detection of 3 vessel disease. Furthermore, delayed enhancement MRI is also able to assess myocardial infarction size 105. However, there are major practical constraints to the performance of exercise MRI, which do not apply to nuclear techniques. For the reasons, the limitations of chemical provocation methods apply particularly to MRI induction of ischemia.

53

CHAPTER TWO

ELECTROCARDIOGRAPHY FOR DETECTION OF MYOCARDIAL ISCHEMIA: DEVELOPMENTS

54 CHAPTER TWO

Electrocardiography for Detection of Myocardial Ischemia: Recent Developments

2.1 Introduction: ECG: Continued Utility?

The 12-lead standard electrocardiogram has been used clinically for diagnosis of cardiac anomalies for more than one hundred years. It still plays an important role for diagnosis and monitoring of heart conditions. Diagnoses are based on changes that indirectly reflect changes of heart structure and function. The ECG is a noninvasive, relatively simple, inexpensive method, which is much more cost-effective than echocardiography, nuclear myocardial perfusion imaging, and MRI technologies.

However, the relevance of ECG techniques may be questioned in particular in light of development of alternative diagnostic imaging techniques. Nevertheless, one area of continued investigative interest in ECG analyses concerns the late potential of QRS complex and high-frequency QRS complex signals (low-amplitude) for diagnosis of arrhythmic risk. The standard ECG signal can be divided into P wave, QRS complex, T wave, U wave, and ST segment. One normal cardiac circle produces one normal ECG waveform as shown in figure 2.1. The P wave is produced by right and left atrial depolarization. Ventricular depolarization produces the QRS complex, while ST segment and T wave represent different phases of ventricular repolarization. The ST segment is also part of the ventricular repolarization phase. It starts from the J point (at the end of the QRS

55 complex, shown in the figure by an arrow) to the beginning of the T wave. It is normally isoelectric or slightly slanted upward.

Figure 2.1: A typical ECG waveform. Between the end of the QRS complex and the beginning of the ST segment, there is the J point (indicated by arrow), which is also important for assessment of ST segment deviation.

Displacement of the ST segment from the isoelectric point is generally regarded as a potentially important diagnostic and prognostic marker of coronary artery disease. For example, marked persistent elevation of ST segment of greater than 1 mm in at least two contiguous ECG leads indicates evolving acute myocardial infarction. If the ST segment is depressed, often together with T wave inversion, this may indicate subendocardial ischemia/infarction, but the specificity of this finding is variable, increasing with the degree of ST depression.

ST segment deviation can also be used to localize the site of myocardial ischemia. In general, myocardial ischemia or infarction of the anterior wall of heart causes ST segment elevation in the anterior precordial leads (V2-

56 V4); whereas inferior wall infarction causes ST segment elevation in II, III, and aVF; the lateral wall infarction causes changes in V5, V6, I, aVL. The site of ST segment change corresponds to the probable distribution of particular coronary arteries. Thus, ST elevation in leads V2-4 is categorized both as “anterior” and as “left anterior descending artery-related” evolving infarction. The ST segment deviation is always used as a marker for detection and localization of myocardial ischemia. Furthermore, it is also used for monitoring of non-invasive reperfusion therapy, for example with thrombolysis, and for monitoring after emergency percutaneous revascularization.

However, the ST segment is imperfect for detection and diagnosis of ischemic heart disease, especially less severe or intermittent ischemia. It is very common for patients with ischemic heart disease to lack ST segment changes 108 32 109. Conversely, resting ST segment depression of 1-2mm is relatively nonspecific, in the absence of transient regional fluctuations during symptoms. It should be therefore seen that the resting 12-lead ECG represents more of a screening tool for episodic, extensive ischemia or evolving infarction than a diagnostic test for definitive evaluation of coronary circulation status.

2.2 Automated ST Segment Analysis

Therefore, ST segment deviations are used for diagnosis and localization of myocardial ischemic episodes or for evaluation of resolution of an ischemic episode. The utility of such detection also extends to diagnosis of silent ischemia 65. Continuous ST segment monitoring may be used for detection

57 of myocardial ischemia and monitoring of patients with variant angina, after acute myocardial ischemia, and stable angina, after acute myocardial ischemia, and stable angina following elective percutaneous coronary intervention. However, calibrated ST segment monitoring over 24 hours offers evaluation of asymptomatic ischemic episodes 110 111 65, which are relatively common in patients with angina pectoris. However, the clinical advantage of detection of “total ischemic burden” is equivocal 23.

While many ST segment monitoring devices are adapted for ambulatory use 69, there is a case for the availability of continuous 12-lead ST segment monitoring in the Coronary Care Unit, for example for evaluation of spontaneous episodes of ischemia in patients with unstable angina, or for evaluation of resolution of ST segment elevation (see previous section).

The ST segment monitoring device utilized in the current experiments was developed by GE Marquette (ST Guard Monitor, developed in 1998 with software version 004). This equipment displays ST segment reading to be available over intervals varying from 0.5 to 24 hours in 12-lead format, together with the capacity to quantitate values both T wave fluctuations, and QRS difference. A typical ST segment trend in a patient undergoing angioplasty to the left anterior descending artery is shown in Fig 2.2.

58

Figure 2.2 GE Marquette ST segment trend (12-leads) including transient occlusion of the left anterior descending artery with associated anterior ST elevation (V2-V4) greater than 5mm.

59 2.3 T Wave Analysis

The T wave represents the ventricular repolarization phase. The T wave, normally combined with the ST segment, is also potentially a guide for detecting myocardial ischemia. For example, regional ischemia may cause tall peaked T waves. On the other hand, T wave abnormalities without ST segment changes are commonly seen and are clinically of minimal diagnostic value, although they also may occur with limited ischemia or infarction.

Studies by Jacobsen et al 112 showed that approximately 75% of patients with T wave abnormalities alone (i.e. without ST segment elevation) had myocardial ischemia. Numerous studies suggest that T wave abnormalities may correlate with propensity to severe ischemia, acute myocardial infarction, and cardiac death 112 113.

There is still ongoing uncertainly about mechanisms of T wave fluctuation during myocardial ischemia 114 113 112. Furthermore, T waves are markedly affected by changes in position, breathing, and medication, limiting the diagnostic specificity of T wave availability. In the current study, T wave changes were not evaluated for these reasons.

2.4 QRS Complex Evaluations

2.4.1 General Principles: the QRS Complex and Ischemia

The QRS complex reflects ventricular depolarization. It usually lasts 0.08 - 0.10 seconds and amplitude varies with age and gender. Myocardial

60 ischemia leads to increases in extracellular potassium (K+), acidosis, and anoxia. These conditions consequently cause reduction in membrane excitability, shortening of action potential duration (APD), and prolongation of recovery of excitability following an action potential (see section 1.2.3). Thus, QRS complexes theoretically are affected by extensive ischemia.

2.4.2 “Late Potentials” of QRS Complex

The concept of “late potentials” or abnormal potentials in the “terminal portion of the QRS complex” started in the late 1960s and early 70s. The late potentials referred to are certain microvolt-level, high-frequency electrical signals, present late within the QRS complex 115. These signals only can be detected reliably by using special techniques and equipment such as signal-averaged ECG (SAECG) 109 116 117.

Several investigations have suggested that late potentials represent abnormally delayed ventricular depolarization activity. They correlated with increased risk of developing arrhythmias 118 119 120 121 116. Therefore, they may be useful for predicting risk of sudden cardiac death 120.

2.5 Signal-Averaged Electrocardiogram (SAECG)

The signal-averaged ECG (SAECG) method is a computer-based process of analysis of variable frequency signals from 0.5 to 300Hz 109. Each electrode lead input is amplified, then its voltage is measured, each result of sample is then converted into digital number by computer process. After the process, the ECG signals are coded as a series of digital numbers from voltage

61 waveforms. There are two types of averaging processes in clinics. The temporal SAECG is more commonly used rather than the spatial SAECG, which utilizes orthogonal x, y, and z leads 122 123.

The SAECG technique can improve signal to noise ratios, thus delineating high-frequency signals from background noise 124. While the SAECG uses an extended frequency range, it also can detect other abnormalities such as hypertrophy, prior infarction, and ventricular aneurysms. The method can be averaged in multiple beats from standard orthogonal bipolar x, y and z leads and is able to reduce background “noise” 109. Because the ensemble or sequential averaging waveform is repetitive, it will detect large amplitude low-frequency signals. The SAECG data can be analyzed in either the time domain or the frequency domain, or both 125.

2.6 High-Frequency QRS Complex Studies

2.6.1 High-frequency Technique

As mentioned in 2.1 section of the thesis, there are a few groups, especially in Europe, interested in this phenomenon from both theoretical and technical aspects. The recorded signals from normal surface ECG leads always include background “noise” from factors including skeletal muscle movement, amplifier, instrumentation noise, other power sources, and tissue electrode artifacts. To avoid these signal contaminants, a low frequency filter is required to exclude them from the ECG. However, this also may filter out some normal low-microvolt electrical signals. Particularly, some normal electrical signals within the QRS complex, at the end of depolarization phase may have very important roles in predicting

62 arrhythmogenesis. Furthermore, these signals possibly provide incremental clinical information for detecting ECG changes during myocardial ischemia. The “traditional” ECG technique may limit sensitivity of detection of myocardial ischemia via incomplete consideration of these signals 126 127 128.

In contrast with the normal ECG technique, the high-frequency technique has a detection range of 100Hz to 300Hz. The most acceptable frequency range is up to 250Hz, which is able to exclude extraneous background noise and also to obtain normal microvolt-level electrical signals. In particular, the work of Abboud and co-workers in animal experiments and clinical setting confirmed that the high-frequency ECG was useful in detecting myocardial ischemia 126 129 130 127.

2.6.2 Clinical Studies Utilizing High-frequency QRS Methodology

A large number of studies have provided evidence that the occurrence of myocardial ischemia is associated with changes in the frequency distribution of electrical activity generated within the myocardium both during depolarization, and potentially during repolarization. Their results demonstrated that diminution of high-frequency QRS signals technique utilized an extended ECG frequency range, which was able to detect low- voltage signals resulting in increases of the sensitivity for detecting of myocardial ischemia 130 131 132 133 128 134 135 115 136.

One of Abboud’s early studies 126 utilized patients undergoing angioplasty to the left anterior descending coronary artery.

63 Intracoronary unipolar ECG recording was performed with high-frequency filter range, and compared with standard surface ECG recording. The results showed that 10 of 11 patients had significant ST-segment and T wave changes on the intra-coronary leads during balloon inflation, while only 6 patients had abnormalities of ST – T on the surface ECG. While Abboud et also performed many studies to evaluate evidence that high-frequency QRS complex methodology can detect transient ischemia, the study design for the above experiment is imperfect. Basically, it is uncertain whether the superior detection of ischemia utilizing intra-coronary leads and a high- frequency filter results from lead proximity to the ischemic zone and/or from superior analytic processes.

Pettersson et al 131 also used a high-frequency signal-averaged ECG technique, compared with conventional ST segment analysis to study patients undergoing angioplasty balloon inflation. The study found that overall diagnostic sensitivity for localization of acute coronary artery occlusion was about 88% by using high-frequency QRS method based on calculation of Root Mean Square (RMS) values while the sensitivity of the conventional ST elevation assessment was only 71%. If both ST elevation and depression were included as diagnostic criteria, the sensitivity could be improved up to 79%. The study also found if individual arteries were considered, the two methods had similar detection accuracies for ischemia related to the left anterior descending artery (LAD); the high-frequency method was better for detecting ischemia in the right coronary artery (RCA) than conventional ST analysis; while both two methods had low detection accuracies for circumflex artery (CX) ischemia. The mechanism for this heterogeneity was not clear.

64 Michaelides et al 135 studied patients with spontaneous typical ischemic-type chest pain, using the signal-averaged ECG technique, also comparing results with those of normal 12-lead ECG analysis. The results were also correlated with coronary angiography. The study found the signal-averaged ECG method had greater sensitivity for detecting myocardial ischemia than conventional ECG changes. However, it is very doubtful whether testing a new technique in a high-probability setting such as this is appropriate for demonstrating clinical utility. Clearly validation in a low-risk population would have been much more impressive for a potential decision-making tool.

Because these studies have shown some evidence that the high-frequency QRS complex technique may useful for detecting myocardial ischemia, the National Aeronautics and Space Administration (NASA) developed computer-based ECG software program based on analysis of high- frequency QRS in 12-lead conventional ECG in real time. The program is different from the “late potential” concept because it analyses high- frequency components within the entire QRS interval with frequency from 150Hz to 250Hz but not only in the very latest portion of the QRS interval (late potential) 134. The program is being evaluated for evaluation of ACS, for monitoring of known or suspected myocardial ischemia in high-risk patients, for assessment following percutaneous coronary interventions, for “early” detection and diagnosis of CAD, and for monitoring of heart failure patients. However, it showed little value for patients with .

Recently, the Rahman group 137 also used the program for patients with chest pain or for preoperative evaluation undergoing adenosine/technetium 65 tetrofosmin MPI. The study compared 12-lead high-frequency QRS changes with 12-lead ECG ST Segment assessment before and during adenosine stress MPI tests. In this study, the high-frequency QRS analysis program utilized analysis by using reduced amplitude zones (RAZs) score and root mean square (RMS) score. The result suggested that the RAZs s combined with RMS score in high-frequency QRS analysis had 94% sensitivity and 85% specificity for identifying reversible myocardial perfusion defects. Clearly these are very promising data.

The detected high-frequency signals data can be calculated either root mean square (RMS) 109 or reduced amplitude zones (RAZs) 129. The RMS is focus on measurement of high-frequency QRS complex amplitudes. It is calculated by square root of mean of squaring the amplitude of each selected point within the QRS complex. The result of calculation decreases when myocardial ischemia occurs. The RAZs are calculated by using an algorithm involving fast Fourier transform formula, which is able quantitate high-frequency signals and more accurately calculate changes in the morphologic QRS amplitude zone 134 138.

These previous studies suggested that low amplitude, high-frequency potentials detected by using high-frequency technique might be useful to help diagnose myocardial ischemia or myocardial infarction. However, these studies had not been generally incorporated into clinical practice. How can these signals be analyzed by computer programs properly? Are these computer programs reliable for clinical utilization? Several research groups have performed large studies and try to give a clear, confident, and definite answer so that can improve diagnostic sensitivity of the “old” ECG technique for myocardial ischemia. In such studies, a modified high 66 frequency QRS method is used to detect transient reversible myocardial ischemia. The core issue is to determine whether the program on the basis of modified high-frequency QRS may be more sensitive than the conventional ST-segment assessment method in practice.

2.7 Entropy Method: A Modified High-frequency QRS and/or ST- segment Method for the Current Investigation

2.7.1 Introduction

In preliminary studies in a canine model of reversible ischemia, it was observed that coronary ligation was associated with an increase in heterogeneity of component electrical transients within the frequency- domain analysis of the QRS complex and ST segment. The selectivity of these reversible changes was not investigated (Ginzburg et al, unpublished observation). Based on this observation and the previously mentioned studies, it appears that some low-frequency signals within the QRS complex and ST segment may be associated with reversible myocardial ischemia. Ginzburg derived a method of evaluation of changes in entropy of QRS complexes and/or of ST segments, which might constitute the basis for an alternative or supplementary basis for myocardial ischemia detection.

The method expresses changes in entropy related to both QRS and ST segments of all ECGs, utilizing raw data derivative smoothing, followed by fast Fourier transform of component signals and summation of squares of all amplitudes. The algorithm derivation was:

2 ∞ 2 1 ∞ )( dttx = )( dffX ∞− 2π ∫∫ ∞−

67 Where the = {}txFfX )()( represents the Fourier transform of tx )( and ƒ represents the frequency component (in Hertz) of x . The interpretation of this form of the theorem is that the total power contained in a waveform tx )( summed across all of time t is equal to the total power of the waveform’s Fourier transform X ()f summed across all of its frequency components f . From these data, an index is derived quantifying the normalized entropy functions of the QRS complexes and ST segments from the 12-lead ECG, calculated as:

 1  2  ∑ Ai  n  where n is the total number of frequency components and i=1………n and

Ai is the magnitude of frequency spectral component after conventional derivative. This method forms the basis of a potential new method of ECG analysis. Entropy changes in QRS and ST segments are obtained by both frequency and time consideration.

2.7.2 Presentation of regional entropy data

For the purposes of the experiments outlined in chapter 3 and 4, it was necessary for the entropy-based methodology to fulfill the following requirements: 1. Ability to quantitate changes in the entropy based parameter from any components of the ECG signal, including all or part of the QRS complex and/or ST segment. 2. Ability to perform frequent off-line analysis of entropy changes in each of the conventional 12 ECG leads.

68 3. Ability to coordinate changes in entropy-based parameters with simultaneous ST segment shifts in the 12-lead ECG. 4. Ability to quantitate agglomerate regional entropy changes, in order potentially to improve regional assessment, from 12-lead ECG data.

For these purposes, preliminary investigations were performed in normal adults and in patients with stable angina pectoris (n=10). Prior to institution of formal clinical evaluations, the technology was developed to the extent that: 1. Data for all ECG segments could be quantitated on a 15 second acquisition basis. 2. Data could be presented routinely on the basis of changes in all 12 ECG leads over a pre-defined time period, together with the simultaneous availability of agglomerate data from anterior, inferior and lateral leads. This methodology forms the basis for hypothesis testing in both chapters 3 and 4.

69

CHAPTER THREE

DETECTION AND LOCALIZATION OF MYOCARDIAL ISCHEMIA DURING CORONARY ANGIOPLASTY: ENTROPY- BASED TECHNIQUES

70 CHAPTER THREE

Detection and Localization of Reversible Myocardial Ischemia during Coronary Angioplasty: Entropy-based Techniques

3.1 Introduction

In order to test the program based on the modified high-frequency QRS method, we designed an appropriately blinded clinical study. The primary hypothesis was that region-selective changes in QRS and/or ST entropy can be utilized to localize reversible myocardial ischemia associated with coronary angioplasty.

In generally, myocardial ischemia is diagnosed on the basis of reversible shifts of ST segment and/or T wave morphology on the ECG. The study set out to compare the recently developed methodology utilizing QRS and/or ST entropy with a conventional ST segment assessment method. The patients examined were assumed to have reversible myocardial ischemia during balloon inflation at angioplasty.

Given that the entropy-based technology had been evaluated in controlled circumstances previously including transient coronary occlusion, it was considered that the ability or otherwise to localize ischemia associated with transient occlusion of a vessel (in the absence of movement artifact, such as might occur on a treadmill) would be a suitable initial investigation.

In order to minimize potential for bias, the investigation was designed with the following objectives:

71 A: Principal objective: to compare the accuracy of entropy-based and ST segment-based methodology for localizing transient but potentially severe myocardial ischemia in humans. B: Secondary objectives: 1. To compare the diagnostic yield of entropy-based analyses of various components of the QRS complex and ST segment for localization of ischemia. 2. To evaluate the utility of entropy-based analyses of QRS complex and ST segment in the localization of ischemia in patients with abnormal resting ECGs. In order to complete this study without bias all objectives were assessed with evaluations blinded as to (1): coronary anatomy; (2): results of all investigations other than the one under consideration (i.e. each investigation was evaluated data in isolation rather than as cumulative procedures).

3.2 Methodology

Patient selection: Patient who undergoing selectively cardiac catheterization with potential coronary angioplasty/stent insertion gave informed consent for 12-lead ECG monitoring continuously during the procedure from August 2004 to December 2005 at the Queen Elizabeth Hospital. The protocol was approved by the institutional Ethics of Human Research Committee. Inclusion criteria were: (1) Class II-IV angina pectoris without prolonged ischemic pain in the 12 hours proceeding PCI. (2) PCI of a patent rather than occluded coronary artery. Patients with complete left or right bundle

72 branch blocks or ST segment depression on the baseline ECG were potentially eligible for the study.

Exclusion criteria were: (1) patients with acute ST elevation myocardial infarction within the preceding 48 hours. (2) patients with permanent pacemaker insertion. (3) Patients with frequent episodes of atrial or ventricular tachyarrhythmia.

Standard 12-lead ECG recording: In all cases, patients underwent continuous 12-lead ECG monitoring from the time of commencement of cardiac catheterization. Using radiolucent electrodes allowed ECG monitoring through the whole procedure without interfering with fluoroscopy. The ECG signal quality was visualized synchronously on a GE Marquette Gateway monitor, located in the catheterization laboratory and connected with a GE Marquette ST Guard monitor network, located in the coronary care unit. The ST Guard monitor recording in connection with the Gateway monitor extended throughout the angioplasty procedure. At the same, the connection was paired with an analog-digital EKG master USB (Tea Inc, Ankara, Turkey) which was able to record ECG signals. These signals were interfaced with a computer laptop for collection, and storage of ECG data.

The baseline ECG period was divided into three parts: Control 1 (before local anesthetic), control 2 (before insertion of sheaths into patient’s groins), and control 3 (before contrast injection). We separated this period into 3 phases because of potential induction of ischemia with stress, and contrast effects.

73 12-lead ECG recordings were performed four times or more in each phase of the baseline. Data from every phase were acquired every 15 seconds. Time of initiation of the first balloon inflation was recorded. In associated with the first balloon inflation, the 12-lead ECG was recorded continuously for 120 seconds, irrespective of actual duration of balloon inflation. ECG changes following the first balloon inflation were compared with the baseline ECG data. During this inflation period, patients’ symptoms were recorded, in order to determine whether there was symptomatic ischemia.

Data analysis: Changes in entropy-based parameters related to both QRS complex and ST segment were analyzed by using a modified entropy method (mentioned in chapter 2 – page 67-68). All 12-lead ECGs were analyzed separately for the purpose of entropy calculation. The QRS complex for the purpose of the study was defined via utilization of automatic cursors with individual verification of accuracy in each case. The ST segment entropy signal consisted of all components from the J point to 0.08 seconds thereafter. Entropy data were presented visually both as fluctuations relative to time on a 12-lead basis and as mean fluctuations on the regions of interest: anterior (V1-V6); lateral (I, all, V5, and V6); and inferior (II, III, aft). Data regarding changes in QRS complex and ST segment entropy were analyzed by examination of entropy changes in individual leads and mean changes in regional groups of leads. Interpretation of entropy data changes was performed in isolation by an individual blinded to the complementary clinical data including the site of PCI.

74 ST segment shifts were subsequently analyzed both via visual inspection of individual ECG traces and by evaluation of 12-lead ST trends from the GE Marquette ST Guard monitor.

Criteria for regional localization of ECG-based and entropy-based parameters were developed on the basis of the pilot study described on page 67. For ST segment elevation, a regionally specific transient elevation of 0.05mV or greater was regarded as evidence of ischemia, provided this change was greater than 3-fold baseline noise on the individual ST segment time plots. For entropy data, a regionally specific increase of > 20% in either QRS or ST entropy on ≥ 3 consecutive estimates was taken as indicative of the occurrence of ischemia in that region. Attempts to localize ischemia on the basis of these criteria for ST segment and entropy parameters changes were classified as either definitive, or equivocal, or not possible. An example showed below figure 3.1 for the entropy-based analysis.

Figure 3.1 illustrates fluctuations in ST segment entropy in a single subject during angioplasty. The program agglomerates mean ST entropy data for groups of leads utilizing data assessed 80 msecs after the J point in the illustrated case.

75

Figure 3.1: Example: ST segment entropy fluctuations during balloon inflation. Data shown reflect mean entropy changes at 80 msecs after the J point in this case. Each time point is the mean of 30 seconds of data acquisition. Balloon inflation occurred at time point 4 and continued for 2 minutes. The 4 groups represent “clusters” of regional leads (laterior, inferior, anterior, and global region). The patient had angioplasty to a stenosed left anterior descending artery.

76 The primary end-point of the study was the accuracy of localization of potential ischemia, in the region subtended by the coronary artery being occluded during balloon inflation. Localization was classified as either concordant (i.e. consistent with the site of balloon inflation) or discordant (inconsistent with the vessel occluded).

A prospectively defined secondary objective of the study was to compare localization of ischemia in patients with abnormal resting ECGs (>2 mm ST segment depression and/or complete bundle branch blocks). Data were analyzed separately for this subset.

Signal-noise ratio analysis In order to take into account the possibility that fluctuations of the extent of fluctuation of ST segment and ST segment entropy might be affected by sub-clinical ischemia, these parameters investigated were measured both in ischemic (“signal”) and non-ischemic (“noise”) zones separately during a 15-minute pre-procedure period. 10 patients undergoing elective PCI for signal vessel coronary artery disease with positive diagnosis for both ST segment and ST segment entropy were further studied. We investigated the “noise” associated with these parameters under the study conditions. All fluctuation data were expressed as SD of mean from 4 consecutive (10 second for each) estimates.

The ratio was defined on the basis of signals at peaks of ST segment fluctuation in leads with most significant changes associated with balloon inflation compared with “noise” in leads from a region remote to the balloon-inflated region. For example, when a balloon was inflated in RCA, lead III was chosen for evaluation of “ischemic” zone while lead V2 or V3 77 was chosen for evaluation of “non-ischemic” zone. The peak change on lead III (signal) was at least 3 times greater than “noise” changes on lead V2 or V3. If the balloon inflated in LAD, the most significant change of ST segment fluctuation on lead V2 as “ischemic” zone while lead II was chosen as “non-ischemic” zone. Furthermore, if the balloon was inflated in CX, lead V5 or V6 showed the most significant change and lead V2 was designated as “non-ischemic” zone as “noise” signals.

Criteria for adequate signal-noise ration analysis were that ST segment elevation of >0.05mV was greater than 3 times “noise” level. For the entropy-based data, because single recording increases of >20% in ST segment entropy presented only 1.3 times more than “noise” level, but it was considered ischemia if at least 3 traces with at least 3 consecutive increases in entropy values of >20% were present..

Proportion of correct localization of ischemia zone was determined via both methods. Changes of ST segment and entropy index on proper leads of 12- lead ECG recording must subject to a proper vessel that was inflated. Otherwise, it was classified as incorrect localization and failure of diagnosis/localization of ischemia.

Statistical analysis: All results are expressed as mean± SD. Comparisons of diagnostic accuracy of ST segment and entropy methods for localization of ischemia were compared by Chi-squared test. The limit of statistical significance was defined at p<0.05. Other data comparisons were performed via paired and non-paired t tests.

78 3.3 Results

Patient characteristics A total 103 Patients were studied. Approximately 40% of patients had balloon angioplasty of the left anterior descending coronary artery while only 2 patients had angioplasties involving saphenous vein grafts rather than native coronary arteries. 39% patients had single vessel disease. The first balloon inflation time was variety from 30 to 120 seconds. The majority of patients had prolonged index balloon inflation ( ≥60secs). Approximately 40% patients had suffered previous myocardial infarction, usually in the regions supplied by vessels dilated and 22 of the 103 patients had resting ECG abnormalities (significant ST segment depression or complete left or right bundle branch block) potentially might limit the accuracy of the detection of ST segment, which might “localize” ischemia. No patients suffered adverse events associated with angioplasty. However, there were approximately two third of patients experienced angina with balloon inflation. In this study, age group range was around 50 - 74 and male were predominant. All patients’ characteristics are summarized in Table 3.1.

79 Table 3.1: Patient Characteristics – entire patient group (n=103) Parameter Characteristics (no) (%)

Age (Mean ± SD) 62 ± 12 Gender (n) (M: F) 70: 33 68: 32 Single: Multivessel disease* (n) 75: 28 73: 27 Vessel dilated (n) LAD/diagonal 42 41 Circumflex/intermediate 27(±2) 26 Right coronary 34 33 Known previous MI (n) (Y/N) 42: 61 Duration of index inflation (n) 30-59secs 30 29 60-120secs 73 71 Pain during index inflation (Y: N) (n) 68: 35 66: 34 Resting S-T depression (>2mm) (n) 9 9 Resting complete BBB (n) 13 13

*: >50 % stenosis in a major vessel classified as significant disease ±2: subjects had PTCA/stent to vein grafts supplying to these vessels n: is the number for each category

80 Localization of ischemia Both ST segment analysis and entropy fluctuations were associated with “definitive” localization of ischemia in less half of patients, with similar and high concordance with sites of actual balloon inflation. On proportional (χ2) analysis, there was no significant difference between the assessment modalities as regards either proportions of diagnostic categories (definite, equivocal or not possible) or localizations concordant with the site of PCI. The clinical study results and statistical result were shown in table 3.2.

81

Table 3.2 - A: Diagnostic Categories of PCI Data for both of ST Segment and Entropy based Analyses ST Segment (n=103) (%) Entropy Analysis (n=103) (%) Definitive 49 (48) 48 (47) Equivocal 17 (16) 25 (24) Non-diagnostic 37 (36) 30 (29) X2=0.075

Table 3.2 - B: Accuracy of Localization of Ischemia of PCI Data for both of ST Segment and Entropy-based Analyses ST Segment (n=103) (%) Entropy Analysis (n=103) (%) Localized/Correction 58 (88) 58 (80) Localized/Incorrection 8 (12) 15 (20) Not Localized 37 (36) 30 (29) X2=0.024

82

There were 22 of 103 cases who had either bundle branch block or ST depression greater than 2mm on their resting ECGs. The accuracy of localization of ischemic zone on both of ST segment and entropy based analyses had very similar results (13 vs. 14). The entropy-based analyses had slightly greater proportion of concordance localization of ischemia (86% vs. 69%), otherwise the difference was not statistically significant (χ2=0.348). See Table 3.3.

Table 3.3 - A: Diagnostic Categories for Abnormal Resting ECG Data ST Segment (n=22) (%) Entropy Analysis (n=22) (%) Definitive 9 (41) 9 (41) Equivocal 4 (18) 5 (23) Non-diagnostic 9 (41) 8 (36) Χ2=0.835

Table 3.3 - B: Accuracy of Localization of Ischemia for Abnormal Resting ECG Data ST Segment (n=22) (%) Entropy Analysis (n=22) (%) Localized/Correction 9 (41) 12 (55) Localized/Incorrection 4 (18) 2 (9) Not Localized 9 (41) 8 (36) X2=0.348

83 Overall the results, concordance of diagnostic categories within the study was poor. Specifically, 14% of patients without definitive localization of ischemia on ST segment analyses had definitive localization with entropy- based analysis. Thus, although the study was not designed primarily to assess the incremental value of entropy-based analyses, correct localization would potentially have occurred in 72% of patients using a combination of both diagnostic modalities.

On the patients with definitive localization of ischemia via entropy-based analyses, 60% of these localizations were based entirely or primarily on changes in ST segment entropy. Thus, the entropy-based analysis most depends on entropy ST segment. Therefore, 20 consecutive patients with definitive diagnosis in entropy method were re-analyzed at J point, 60 millisecond following J point, and 80 millisecond following J point to determine which part of ST segment could be relatively important contributed to the diagnosis of ST changes on the basis of entropy method. In each region of three components, these analyses considered a 10 millisecond interval centered upon the region analyzed. Comparisons of the result were shown in figure 3.2.

84

Distribution of Entropy Values at J Point, J60, and J80 ms of ST Segment

600

500

400

300

200

Changes of EntropyChanges (%) Value 100

0 40 60 80 Time Points

Figure 3.2: ST-segment entropy values at J point, 60 ms after J point, and 80 ms after J point.

85 Overall, from the figure 3.2, there was no significant variation in entropy signals between the 3 time segments analyzed, indicating the overall signal arose from the ST segment globally, rather than any single component thereof.

Theoretically, J point is an important component which is related with late potential of QRS complex. The high-frequency QRS technique should be detect these signal changes during cardiac ischemia from other studies mentioned previous sections. However, this study did not prove this point.

ST segment entropy: ST segment correlation Subsequently, in order to further demonstrate if the entropy-based method has better detection accuracy for ischemia, we studied the correlation between ST-segment and QRS and/or ST entropy. This is to determine whether patients with “positive” ST segment result can correlated with entropy values well. Results see figure 3.3. The correlation between the conventional ST and entropy ST was showed that R-squared value was 0.047<1. The R-squared value in ST with entropy QRS was 0.01 <1. There were no correlations among them.

86

260

210 160

110 2 R = 0.0467 60 2 10 R = 0.0099 -4 -2 - 0 2 4 6 8 40 - 90

Changes of Entropy values (%) values Entropy of Changes ST-segment deprssion (mm)

Figure 3.3: Individual data from myocardial zones of reversible ischaemia, demonstrating lack of significant correlation between extent of pacing- induced ST segment depression and regional increase in entropy value. ■▬■: ST segment entropy; R²=0.047, p=NS. ◊◊ : Q R S e n tro p y ; R ²= 0 .0 1 , p=NS.

87

Signal - “noise” analysis results In additional, signal-“noise” ratio data were provided both for leads reflecting the site of subsequent ischemic changes (ischemic region) and leads remote to these changes (non-ischemic region). In the cases of ST segment and entropy data analyses, single lead data were utilized for calculations. Neither the mean ST position nor the extent of the ST fluctuation varied significantly between ischemic (‘signals”) and non- ischemic (“noise”) regions on ST segment or entropy data. Results of data are shown in table 3.4.

88 Table 3.4 Results: “Spontaneous” pre-PCI fluctuations of ST segment and regional entropy values in non-ischaemic and potentially ischaemic regional pre-PCI.

Pre-PCI ECG/entropy position and fluctuation

ST segment (mV) [mean ± SD] ST segment entropy [mean ± Site of SD] Patient PCI Ischemic region Non-ischemic Ischemic Non-ischemic region region region 1 CX 0.085 ± 0.108 -0.193 ± 0.381 1477± 195 3457± 826 2 RCA -0.153 ± 0.095 0.200 ± 0.071 2179± 536 4564 ± 347 3 LAD 0.138 ± 0.063 -0.075 ± 0.050 1656 ± 110 2428 ± 742 4 RCA 0.008 ± 0.070 0.120 ± 0.179 1664 ± 256 2354 ± 97 5 RCA 0.013 ±0.103 0.100 ± 0.071 2907 ± 916 1399 ± 123 6 RCA 0.083 ± 0.318 -0.135 ± 0.121 1428 ± 97 3225 ± 125 7 RCA -0.305 ± 0.161 0.060 ± 0.090 2497± 723 7279± 2980 8 CX -0.075±0.065 0.033 ± 0.062 1628 ± 454 3471 ± 213 9 LAD -0.005±0.142 0.298 ± 0.199 8073± 1590 3625 ± 770 10 RCA 0.125 ± 0.029 0.100 ± 0.082 2548 ± 232 2696 ± 204 Mean ± SD -0.011 ± 0.115 0.051 ± 0.131 2600 ± 510 3450 ± 640

Note: (1) Pre-PCI variability was not greater in potentially ischaemic than in non-ischaemic regions. (2) There was no significant pre-PCI ST depression or entropy elevation in potentially ischaemic regions.

89 From table 3.4, the mean pre-PCI fluctuation in potentially ischemic ECG leads was ± 0.115mV on ST segment elevation and ± 510 arbitrary units on entropy data analysis. Fluctuations of both parameters were similar in non- ischemic ECG leads. On the basis of these finding, ST segment elevation of > 0.05mV were greater than 3 times “noise” levels and were utilized for detection / localization of ischemia during prospective investigation. However, single recording increases of > 20% in ST segment entropy represented only approximately 1.3 times “noise” level; hence only traces with at least 3 traces with at least 3 consecutive increases in entropy values of > 20% were considered as abnormal.

3.4 Discussion

The major finding of the current study is that ischemia, induced by transient occlusion of a major coronary artery, may be localized with similar degrees of accuracy both by (1) serial automated calculation of regional ST segment shifts and (2) by simultaneous evaluation of regional changes in entropy, again largely derived from ST segment data. Furthermore, we have therefore demonstrated for the first time that ischemia may be detected on the basis of regionally selective increases of > 20% in ST segment entropy.

There are other findings of interest from this study, first, localization of ischemia on the basis of entropy changes occurred essentially in different patients to those with the most marked ST segment shifts: there was poor concordance between the extent of ST segment elevation and increases in entropy. This raises the possibility that these two forms of diagnostic modality may have incremental yields. Secondly, it was apparent that ST

90 segment entropy induced by ischemia increases irrespective of the presence of resting ECG abnormalities (complete left or right bundle branch block or resting ST depression). Finally, post hoc analysis showed that ST segment entropy fluctuations arose from the entire ST segment, rather than predominantly the region of the J point. Majority of signals had similar distributions through the whole ST segment.

In the current study, one third of patients, ischemia could not be localized either via ST segment elevation or entropy changes. Of these 35 patients, 34% of them experienced no chest pain during balloon inflation and 41% had suffered prior myocardial infarction. Collateral blood flow was not evaluated. However, it is likely that these patients had less marked ischemia during balloon inflation than the remainder of the cohort.

There are some literatures to the effect that myocardial ischemia is associated with changes within the QRS complex 126 127 138 131 139 134. The concept that these might translate to entropy increases which might reflect the regions of ischemia has not yet been addressed specifically, but might be expected on the basis of these findings. However, in practice, only 14% of patients had localization of ischemia primarily or predominantly from QRS entropy changes. The actual development of entropy changes within the ST segment is also less than surprising due to “injury current” during ischemia 17 46.

However, it is of great interest that there was no strong correlation between marked ST segment elevation and the extent of entropy change in the ST segment. Therefore, it must be assumed that the electrophysiological determinants of ST elevation and entropy fluctuations are different. The 91 basis for these differences could be evaluated in single cell models of ischemia. Furthermore, no “reciprocal” changes in regions remote to the ischemic zones were observed in entropy fluctuations. This provided an additional basis for the accurate localization of ischemia.

The utility of our methodology in patients with abnormal resting ECGs cannot be determined in this study because of the small numbers of patients in this subset. However, if entropy-based analyses were to be utilized for detection of ischemia, this subgroup might be of particular significance, given the un-reliability of ST segment shifts in such patients.

92

CHAPTER FOUR

UTILITY OF ENTROPY METHOD TO DETECT, LOCALIZE, AND QUANTITATE PACING INDUCED MYOCARDIAL ISCHEMIA

93 CHAPTER FOUR

Utility of Entropy-based Technology to Detect, Localize, and Quantitate Pacing-induced Myocardial Ischemia

4.1 Introduction

In the experiments in chapter 3, the coronary artery which was transiently occluded was known, but whether the balloon inflation induced ischemia or not and how extensive was the ischemia was uncertain. Furthermore, the circumstances of the angioplasty experiment were artificial to the extreme, and did not relate directly to common clinical diagnostic problems.

The logical next step of evaluation of the technology, given that it had proved of potential utility in the localization of ischemia, was to evaluate its ability to detect ischemia. However, this begged the question of a clinical “gold standard” for ischemia. For this purpose, it was elected to use evaluation with stress myocardial perfusion imaging, utilizing single photon emission computed tomography (SPECT) for analysis, and temporary (atrial/ventricular) pacing for potential induction of ischemia. Technetium tetrofosmin was utilized as the radionucleide for myocardial blood flow scanning with SPECT.

In the current study, we tested the (null) hypothesis that continuous ST segment monitoring and both ST segment and QRS entropy monitoring would be equally accurate in predicting the presence, locality and extent of myocardial ischemia in a group of patients in whom exercise perfusion imaging was impracticable. The pacing tetrofosmin test aims to induce ischemia primarily by increasing heart rate 95; this test was utilized as a

94 “physiological” means of induction of ischemia for the current purposes. Furthermore, we sought to determine whether the utility of both methods was independent of whether ischemia was induced by rapid right atrial or right ventricular pacing.

4.2 Methodology

Patient Selection: Patients with known or putative coronary artery disease who were to undergo pacing stress imaging for diagnosis, localization and quantitation of myocardial ischemia were considered for this study. In general, patients were selected on the basis of uncertainty regarding inability to perform exercise testing. Patients with resting ECG abnormalities including complete bundle branch block were eligible for the study.

Experimental Protocol: 1. Pacing protocol and catheterization: The study protocol examined detection and localization of ischemia induced by pacing tachycardia. A bipolar pacing electrode was inserted into the right atrium via the right femoral vein and pacing initiated at 100 beats per min. A Swan- Ganz catheter was also inserted via the right femoral vein sheath, and pulmonary capillary wedge pressure (PCWP) monitored continuously. The pacing rate was increased by 10 beats per minute until onset of chest pain, or an increase in PCWP to greater than 30mmHg, or until a pacing rate of ≥140 beats per min had been reached 95. If right atrial pacing caused AV block, right ventricular pacing was utilized.

95 2. ECG recording: 12-lead ECGs were simultaneously recorded with GE Marquette ST Guard monitor and via EKG master cable. Before pacing started, An ECG was recorded on least four occasions as baseline data. Thereafter. ECGs were continuously recorded during increasing heart rates associated with the pacing procedure.

3. Myocardial perfusion imaging: At the pacing peak heart rate, technetium tetrofosmin 450 – 550 Mega Becquerel (MBq) was injected through a femoral vein. Patients underwent myocardial perfusion scanning approximately one hour after the pacing study. Repeat injection was performed after an interval of 4-6 hours if the initial scan was abnormal. Nuclear physicians reported perfusion images without knowledge of data regarding ECG changes. Quantitation of ischemia and infarction was performed utilizing 4D- MSPECT (University of Michigan) program, which scores both fixed and reversible defects according to presumptive coronary distribution. An example of raw data and analytic methods is given in figure 4.1.

4. ST segment analysis: The ST segment trend was analyzed throughout the pacing period analogously to methods in chapter 3. However, in the current study, it was anticipated that myocardial ischemia induction would be predominantly subendocardial, and that associated ECG changes would be predominantly those of ST depression, rather than elevation. Criteria for “diagnostic” ST segment fluctuation were therefore the appearance during pacing of > 1mm ST depression in at least 2 ECG leads reflecting the same region of myocardium. An example of a representative ST segment trace is shown in figure 4.2. 96 5. Entropy data analysis: This was performed analogously with chapter 3 methodology. A high-frequency range filter was used to process ECG signals for entropy-based data analysis. All heart beats in samples at each pacing interval were analyzed in 15 second groups. QRS and ST segment entropy changes expressed as percentage relative to mean baseline data. A “positive” result was categorized as greater than 20% region-selective entropy fluctuation, as for the methodology in chapter 3. Data were analyzed interactively to ensure that pacing spikes on ECG records did not cause misinterpretation of ECG changes.

97

Figure 4.1A: Analysis of stress perfusion imaging 1. In this case, ischemia was induced by right atrial pacing to 130 beats per min. The upper 2 panels (short axis views) reveal the induction of a large zone of ischemia in the CX ± RCA distribution, and partial reversal of this perfusion defect in the resting images, also suggesting a component of infarction in the circumflex. The defect blackout map (middle panel) was utilized to quantitate extent of ischemia and infarction, with extensive reversibility denoted by the hatched symbols area. In this case, the circumflex territory was considered 22% infarction and 31% reversible ischemia.

98

Figure 4.1B: Analysis of myocardial perfusion imaging 2. Perfusion “defect” region was localized and quantitated on blackout map. The top panel showed localization and quantitation of “defect” zone at the stress status. In this case, it showed “defect” zone around CX (53%) and RCA (13%) territories. The middle panel represents rest status, which showed 41% perfusion “defect” around CX region and no defect zone at RCA territory. The bottom panel showed reversibility of perfusion defect from the stress return to rest. Reversible defect [ischemia (hatched area)] showed 31% at CX and 11% at RCA. Fixed defect [infarction (black area)] showed 22% at CX and 2% at RCA.

99

Figure 4.2: An example of ST trend analysis: “positive” result based on ST depression from right atrial pacing-induced tachycardia with peak heart rate 150 beats per minute. Note: progressive development of extensive ST depression most marked in anterolateral leads. Serial ST monitoring reveals 2.15mm ST depression in V4 as maximal change.

100 Statistical methods: Differences between the conventional ST segment assessment method and the entropy analysis, and the myocardial ischemia score were analyzed utilizing Chi-square tests. The level of statistical significance was set at < 0.05. The potential correlation between PCWP and myocardial ischemia was evaluated utilizing linear regression. Data are presented as mean ± SD unless otherwise stated.

4.3 Results

A total of 43 patients were studied (23 women and 20 men). Patients were elderly (70±10), and many were known to have coronary artery disease (e.g. with previous intervention procedure). The most common predominant symptom leading to investigation was chest pain but dyspnoea was also common. The basis for utilizing a modality other than exercise for evaluation of inducible ischemia was usually presence of dyspnoea (due to lung and/or heart disease: n=29) and /or immobility (due to arthritis or claudicating; n=20). 25 Patients had diabetes. Patients’ clinical data are summarized in table 4.1. Importantly, 8 patients had complete bundle branch block on their ECGs. This is relevant because bundle branch blocks may be associated with appearances of septal ischemia on myocardial perfusion imaging 140 141.

101

Table 4.1: Pacing tetrofosmin test – patients’ clinical data (n=43)

Clinical data Number (n) Percentage (%)

Previous cardiac events:

Known myocardial infarction 14 33 Heart failure 16 37 Coronary surgery 14 33 PCI 6 14

Symptoms precluding exercise

Immobility 20 47 (e.g. arthritis/claudicating) Dyspnoea 29 67 (lung disease and/or heart failure)

Other symptoms precluding exercise

Chest pain 25 58

Other indications for SPECT

Pre-operative evaluation 6 14 Equivocal result of coronary angiography 5 12 (e.g. multiple moderate stenosis)

______

102 A peak heart rate of ≥ 150 beat per minute was reached in 53% of patients, but 9 patients required right ventricular pacing because of development of AV block with atrial pacing. Approximately half of patients had increases of pulmonary wedge pressure ≥ 6 mmHg and more than one third of patients experienced chest pain during pacing. 33% patients had clinically detected (as distinct from subsequently analyzed) ST depression (≥ 1mm) on 12-lead ECG during pacing.

As regards the experimental data, continuous ST segment trend monitoring revealed ≥ 1mm depression (“definitive change”) in about half the patients (51%), while the entropy analysis showed 40% patients had definitive fluctuations in QRS and/or ST segment entropy parameters. These data are shown in table 4.2.

103

Table 4.2: Clinical and experimental ECG data: pacing cohort (n=43).

Clinical data: Number of each category Percentage of each (n) category (%) ST depression ≥1mm on 12-lead ECG 14 33 Increase in PWP ≥6 mmHg 25 58 Developed chest pain (Y/N) 17/26 40/60

Experimental data:

ST trend: ST depression (definitive / equivocal) 22/11 51/26 Entropy fluctuation (definitive / equivocal) 17/8 40/19

104 Data for pacing tetrofosmin imaging analyzes are summarized in table 4.3. From myocardial perfusion data, defects of ≥ 10% within any designated zone were considered definite, whether reversible (myocardial ischemia) or fixed (myocardial infarction). In 40% of cases patient’s myocardial ischemia was detected while in 60% patients’ myocardial infarction was diagnosed from SPECT. One third of these diagnoses had 10% - 30% ischemic zone while half of them had 10-30% infarcted zones in the affected regions. Only 7% of patients had > 30% ischemic zone. However, 37% of patients had > 30% infarction. In 16% multivessel ischemia was present, 26% had multivessel infarction, and 30% of patients had both myocardial ischemia and infarction.

Left ventricular systolic function was usually well preserved despite the high frequency of exertional dyspnoea. Specifically, half the patient population had normal LV ejection fraction (EF) (> 50%) while only 5 patients had LVEF ≤ 30%.

105 Table 4.3: Summary of myocardial perfusion imaging results (n=43)

Extent of ischemia: Number (n) Percentage (%) 1. Nil detected 26 60 2. Limited to 10-30% in worst-affected zone 14 33 3. >30% in at least 1 region 3 7 4. Multivessel ischemia 7 16 Extent of infarction: Number (n) Percentage (%) 1. Nil detected 17 40 2. Limited to 10-30% in worst-affected zone 10 23 3. >30% in at least 1 region 16 37 4. Multivessel infarction 11 26 Ischemia: infarct relationship: Number (n) Percentage (%) 1. Neither ischemia nor infarct 13 30 2. Both ischemia and infarct 13 30 3. Only ischemia 4 10 4. Only infarct 13 30 Left ventricular ejection fraction: Number (n) Percentage (%) 1. 0 - 30% 5 12 2. 30 - 50% 16 37 3. > 50% 22 51 Peak heart rate paced (bpm): Number (n) Percentage (%) 1. 125-135 12 28 2. 140-145 7 16 3. 150-155 18 42 4. 160-170 6 14

106 Myocardial perfusion imaging results for all patients were correlated with those of the conventional ST segment assessment and the entropy data. Only the ischemia data are considered initially in accordance with the hypothesis tested. These cross-correlation results are summarized in table 4.4, while the infarction correlations considered in table 4.5, are provided in order to test the hypothesis that ST segment and/or entropy data might be affected by the presence of infarction alone.

107 Table 4.4-A: Concordance data: ischemia. Patients with either right atrial or ventricular pacing tetrofosmin test (n=43): ST segment assessment vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Cross- SPECT: Percentage SPECT: Percentage Total correlation ischemia (%) ischemia (%) (n) (+) (-) ST (+) 8 19 21 49 29 ST (-) 9 21 5 11 14 Total (n) 17 40 26 60 43

(χ²=0.0004, p=0.27)

Table 4.4-B: Concordance data: ischemia. Patients with either right atrial or ventricular pacing tetrofosmin (n=43): entropy-based analysis vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Cross- SPECT: Percentage SPECT: Percentage Total correlation ischemia (%) ischemia (%) (n) (+) (-) Ent (+) 12 28 13 30 25 Ent (-) 5 12 13 30 18 Total (n) 17 40 26 60 43

(χ²=0.04, p=0.25)

108 Table 4.5-A: Concordance data: infarction. Patients with either right atrial or ventricular pacing tetrofosmin (n=43): ST segment assessment vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Cross- SPECT: Percentage SPECT: Percentage Total correlation infarction (%) infarction (%) (n) (+) (-) ST (+) 13 30 15 35 28 ST (-) 13 30 2 5 15 Total (n) 26 60 17 40 43

(χ²=0.0008, p=0.25)

Table 4.5-B: Concordance data: infarction. Patients with either right atrial or ventricular pacing tetrofosmin (n=43): entropy-based analysis vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Cross- SPECT: Percentage SPECT: Percentage Total correlation infarction (%) infarction (%) (n) (+) (-) Ent (+) 14 32 12 28 26 Ent (-) 12 28 5 12 17 Total (n) 26 60 17 40 43

(χ²=0.037, p=0.16)

109 Therefore, as shown in table 4.4, only 13 (30%) patients had concordant results between conventional ST segment assessment method and myocardial perfusion imaging analysis for myocardial ischemia. 58% concordance for entropy-based analysis was similarly poor.

From the data shown in table 4.5, it can also seen that changes in ST segments and/or regional ST segment entropy provide no indication of either presence or localization of infracted region of myocardium.

In order to determine whether the right ventricular pacing markedly affected the total result, we also examined the effect of excluding 9 patients who had right ventricular stress pacing and derived tables 4.6 and 4.7 in the next pages.

110 Table 4.6 - A: Concordance data: ischemia. Patients with the right atrial pacing stress (n=34): ST segment assessment vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Cross- SPECT: Percentage SPECT: Percentage Total correlation ischemia (%) Ischemia (%) (n) (+) (-) ST (+) 7 20 18 53 25 ST (-) 4 12 5 15 9 Total (n) 11 32 23 68 34

(χ²=0.001, p=0.18)

Table 4.6 - B: Concordance data: ischemia. Patients with the right atrial pacing stress (n=34): entropy-based analysis vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Cross- SPECT: Percentage SPECT: Percentage Total correlation ischemia (%) Ischemia (%) (n) (+) (-) Ent (+) 8 24 12 35 20 Ent (-) 3 9 11 32 14 Total (n) 11 33 23 67 34

(χ²=0.07, p=0.19)

111 Table 4.7 - A: Concordance data: infarction. Patients with the right atrial pacing stress (n=34): ST segment assessment vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Cross- SPECT: Percentage SPECT: Percentage Total correlation infarction (%) infarction (%) (n) (+) (-) ST (+) 11 32 13 38 24 ST (-) 9 27 1 3 10 Total (n) 20 59 14 41 34

(χ²=0.0007, p=0.20)

Table 4.7 - B: Concordance data: infarction. Patients with the right atrial pacing stress (n=34): entropy-based analysis vs. SPECT analysis. (+ : abnormal findings; - : normal findings).

Corss- SPECT: Percentage SPECT: Percentage Total correlation infarction (%) infarction (%) (n) (+) (-) Ent (+) 11 32 10 29 21 Ent (-) 9 27 4 12 13 Total (n) 20 59 14 41 34

(χ²=0.046, p=0.15)

112 From table 4.6, excluding right ventricular pacing patients, these results showed that the ST segment assessment method had 35% (12) concordance with myocardial perfusion imaging analysis while the entropy analysis had 56% (19) for myocardial ischemia.

In table 4.7, the results showed similar poor concordance with myocardial perfusion imaging results for myocardial infarction from both of ST segment and entropy-based analyses (35% vs. 44%).

During pacing, increases in pulmonary capillary wedge pressure (PCWP) normally represented a possible basis for study termination. The correlation between changes in PCWP and myocardial perfusion imaging analysis to detect myocardial ischemia for total patients was plotted in figure 4.2. There was no significant correlation between increase in PCWP and reversible myocardial ischemia score in this study.

113

Correlation between ^PCWP and ischemia score

70 60 50 40 30

20 2 R = 0.0292 10 0 Ischemia Score (%) Score Ischemia -10 -5 0 5 10 15 20 25 ^PCWP (mmHg)

Figure 4.2: Correlation between PCWP changes and myocardial ischemia score. R² = 0.03, p=NS.

114 4.4 Discussion

As reviewed in chapter 1, section 1.4.2, exercise ECG testing in the absence of associated perfusion imaging represents a relatively poor basis for detection of reversible myocardial ischemia, especially in a “low risk” population 73 76. Most of these studies evaluated ST segment changes in 12- lead ECG on treadmill exercise. Only a few studies 142 have assessed ST segment fluctuation on ECG during atrial pacing-induced tachycardia. The results again demonstrated that ST segment analysis had limited diagnostic accuracy. Some investigators have suggested heart rate-adjusted ST segment analysis could improve diagnostic accuracy of exercise ECG in patients with coronary artery disease 143. However, women have variable and low diagnostic accuracy on exercise test even with consideration of heart rate- adjusted and age-adjusted ST segment analysis 73 143. All these studies utilized ST segment assessment on 12-lead ECG; none utilized computerized, continuous ST trend monitoring for automatic ST segment analysis.

In the current study, GE Marquette ST trend was utilized for automatic continuous ST segment analysis on 12-lead ECG. However, the results showed only 30% concordance with SPECT results for myocardial ischemia. The reason for this was not apparent, but first it should be considered that ECG artefacts (i.e. pacing “spikes”) may have contributed. These pacing spikes may not be properly recognized by the computerized programs for both methods. The entropy-based program exhibited difficulty in distinguishing pacing spikes from normal signals of ECG wave forms.

The most likely basis for the poor results of both ST segment-based and

115 entropy-based analyses relates to patient selection. The patient population studied had (1): a high prevalence of resting ST segment changes; (2): a high prevalence of “mixed” myocardial ischemia and infarction. Both of these represent well-known bases for impaired diagnostic accuracy of exercise- based diagnostic techniques, and would certainly apply here. Furthermore, the pilot studies utilizing entropy-based analyses were not conducted during tachycardia: it is possible that tachycardia affects entropy-based measurements.

In addition, SPECT was used as “gold standard” in this study. Myocardial ischemia can be detected, localized, and quantitated with considerable reliability with this technique: has 95% of diagnostic accuracy for detection of coronary artery disease has been reported 88 if combined with exercise. However, with 3-vessel disease, stress MPI may occasionally show “normal” imaging due to diffusely decreased perfusion 144. However, this is not likely to explain the current results.

Furthermore, gender is always a relevant factor for diagnosis of coronary artery disease. ST segment assessment on 12-lead ECG is not a sensitive tool for detecting ischemic heart disease in women. In many studies, women were more likely to have “false positive” ST segment depression on ECG during exercise 81. Hoilund-Carlsen’s study 81 showed that MPI had lower diagnostic sensitivity in women compared with men. About half (53%) the patients in this study were female.

Pulmonary capillary wedge pressure (PCWP) was monitored during the pacing procedure. No previous studies have investigated the relationship between PCWP changes and pacing-induction of myocardial ischemia. In 116 this study, 58% patients had definite increases of PCWP during pacing. However, these changes had no correlation with SPECT results for myocardial ischemia. The increases in PCWP reflect pressure of left ventricular diastolic dysfunction. In this population, apart from induced ischemia, previous infarction and/or left ventricular hypertrophy might have contributed PCWP increases.

Rahman et al 137 evaluated the utility of analysis of high-frequency components of the QRS complex for detection of myocardial ischemia induced by adenosine infusion. In a group of 45 patients, appearance of ST segment changes had very poor sensitivity (18%) for presence of myocardial anomalies, but high-frequency QRS fluctuation had up to 94% sensitivity, depending on the precise analysis method used. These data serve to reinforce that methods such as ST segment analysis are often little value, but the differences between adenosine infusion and atrial pacing are obvious and considerable. Of particular note, adenosine infusion does not markedly affect heart rate. Furthermore, the patient population evaluated by Rahman et al included few patients with multivessel ischemia and/or infarction.

Finally, it is important to compare the results of the current study with those of the PCI-induced-ischemia study described in chapter 3. The previously described data demonstrate that reversible transmural ischemia modified ST segment entropy-based parameters. Therefore, the essentially negative results of the current study require to be specifically contrasted with the previous data. As previously mentioned, potential sources of differences are: (1) pacing spike artifact; (2) possible effects of tachycardia per se on entropy-based parameters; (3) smaller ST segment shifts; (4) more diffuse, widespread ischemia; (5) presence of entropy changes/ST segment shifts due 117 to regional aneurysmal expansion during pacing.

All of the above need to be placed in perspective if entropy-based analyses are to prove clinically useful for evaluation of exercise induced ischemia in future.

118

CHAPTER FIVE

CONCLUSIONS

119 Conclusions, Limitations, and Future Perspectives

The current experimental data fall into two categories: 1. Chapter 3: In a group of patients undergoing angioplasty to a single, previously patent, major epicardial coronary artery, the presence of ischemia could be localized at least as by continuous ST segment monitoring. Importantly, entropy parameter changes permitting localization of ischemia occurred predominantly in the ST segment (and to a lesser extent within the QRS complex). This study establishes “proof of principle”: ST segment entropy represents a potential incremental method for ischemia detection and localization. 2. Chapter 4: In a group of patients undergoing atrial pacing stress myocardial perfusion imaging, neither ST segment analysis nor the above-mentioned entropy-based analyses were of any clinical value in the detection, localization or quantitation of ischemia. These were many possible reasons for this finding, but these could not be evaluated within the context of the actual experiments.

Form these findings, it is possible to discern that the ultimate objective of these studies (to improve the diagnostic accuracy of ECG diagnosis of ischemia) is not immediately feasible. The following studies need to be performed in order to evaluate the potential utility of entropy analyses as an adjunct to ST segment monitoring during treadmill exercise: (1) it is important to determine whether the entropy measures concerned are tachycardia-dependent. Studies in normal subjects during exercise would be definitive in that regard; (2) it is important to determine whether presence of significant infarcted tissue in the absence of ischemia modulates entropy

120 parameter changes. For example, recently revascularized patients with previous infarct could be used to test this possibility; (3) the differences between the chapter 3 and chapter 4 data might relate to sharply demarcated regions of intense ischemia, which are rare except in acute coronary syndromes. Studies in patients with known single vessel disease and no previous infarct might elucidate this issue.

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