Cross-Sectional Imaging of the English Bulldog: the Use of Computed Tomography For

Cross-Sectional Imaging of the English Bulldog: The Use of Computed Tomography for

a Novel Approach to Quantify Upper Airway Disease and Multi-Detector Cardiac

Angiography

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Masters of Science

in the Graduate School of The Ohio State University

Eric T. Hostnik, BS, DVM

Graduate Program in Comparative and Veterinary Medicine

The Ohio State University

2016

Master's Examination Committee:

Wm Tod Drost, DVM, DACVR, Advisor

Brian A. Scansen, DVM, DACVIM (Cardiology)

Amy Habing, DVM, DACVR

Kathleen Ham, DVM, MS, DACVS

Copyrighted by Eric T. Hostnik, DVM 2016

Abstract

Part 1. Computational Fluid Dynamics Using Computed Tomography to Assess

Airway Resistance in English Bulldogs.

Obstructive airway disease is common in brachycephalic dogs. Stenotic nares, edematous intranasal turbinates, mucosal swelling, and an elongated, thickened soft palate are sources of airflow resistance. Surgery has traditionally focused on resection of excessive nares and soft palate, without objective measures to validate efficacy.

Twenty-one non-operated brachycephalic dogs were recruited for this pilot study.

A 128 multi-detector computed tomography (MD-CT) scan was performed in all dogs, from rostral nares to diaphragm (SOMATOM Definition Flash; Siemens Healthcare).

MD-CT examinations were performed using conscious sedation and without endotracheal intubation. Raw MD-CT data were imported into ScanIP software (Simpleware, Version

7.0) to render a three-dimensional surface mesh model by automatic segmentation using -

1024 to -450 Hounsfield units to isolate the air-filled nasal passage from the nares to the caudal soft palate. Three-dimensional surface models were then imported into COMSOL

Multiphysics 5.0 with MATLAB (COMSOL, Inc., Version 5.0.1.276) for computational fluid dynamic (CFD) modeling and calculation of airway resistance.

The nasal passages were modeled and airway resistance calculated in all dogs.

Airway resistance varied widely; mean and SD of 9,859.19 +/- 12,818.53 Pa/L/s. Airway

resistance did not correlate with age (r = 0.344, P = 0.126) or weight (r = -0.058, P =

0.803). In 19/21 dogs, the rostral third of the nasal passage showed the greatest step-up of airflow resistance. The remaining 2/21 dogs, the caudal third of the nasal passage showed the greatest resistance with the greatest increase identified at the caudal portion of the soft palate.

Computational fluid dynamics derived from nasal MD-CT can quantify airway resistance in dogs. This methodology may have utility for objectively studying surgical interventions in canine brachycephalic airway syndrome.

2. Cardiac Dimensions Measured by Multi-Detector Computed Tomography

Angiography and Transthoracic Echocardiography in Normal English Bulldogs.

Transthoracic echocardiography (TTE) is the primary modality for evaluating cardiac dimensions and function in dogs. In the English bulldog, TTE is challenging due to the breed’s unique thoracic conformation with dorsoventral compression and narrow intercostal spaces. Multi-detector computed tomography angiography (MD-CTA) circumvents body conformational challenges and is a gold standard for cardiac dimensions in humans.

Eleven English bulldogs underwent both TTE (Vivid 7; GE Medical Systems) and sedated MD-CTA (SOMATOM Definition Flash; Siemens Healthcare) within 24hrs of the other. Standard cardiac dimensions were compared between modalities, measured twice by the same observer and separately by two other observers. Comparisons of TTE to MD-CTA dimensions were performed by Student’s t-test if normal or Wilcoxon signed-rank test if not normal; intra-observer and inter-observer variability was assessed by coefficient of variation (CV).

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Eight of the 25 measurements of linear cardiac dimensions were significantly

different between TTE and MD-CTA (all P < 0.033). Overall intra-observer agreement

was strong with average CVs of 5.34% for TTE and 2.50% for MD-CTA. Overall inter- observer agreement CVs averaged 6.5% for TTE and 8.75% MD-CTA.

Differences were found between cardiac dimensions as measured by TTE and

MD-CTA, indicating the two methodologies are not equivalent. Sedated MD-CTA yielded high-quality imaging with strong intra-observer and inter-observer measurement repeatability in English bulldogs, providing cross-sectional reconstructions of cardiac morphology in a breed challenging to image by TTE.

Acknowledgments

A sincere thank you to Dr. Samir Ghadiali, Rachel Zielinski, and the department of

Biomedical Engineering at the Ohio State University for their time, work, support, and their education regarding three-dimensional model construction and computational fluid dynamics. Thank you to the diagnostic imaging team at the Martha Morehouse Medical

Plaza for their assistance with imaging of the English bulldogs.

Vita

2004...... Burr & Burton Academy

2008...... B.S. Biological Sciences and Animal

Sciences, University of Vermont

2012...... D.V.M University of Florida

2013 to present ...... Graduate Student, Department of Veterinary

Clinical Sciences, The Ohio State University

Fields of Study

Major Field: Comparative and Veterinary Medicine

Table of Contents

Abstract…………………………………………………………………………………..ii

Acknowledgements……………………………………………………………………....v

Vita……………………………………………………………………………………....vi

Fields of Study………………………………………………………………………..…vi

Table of Contents…………………………………………………………………..…...vii

List of Tables……………………………………………………………………..……...x

List of Figures…………………………………………………………………..………xii

CHAPTER 1: GENERAL INTRODUCTION...………………………………………….1

1.1 Computed Tomography……………………………………………...... 1

1.2 English Bulldogs Congenital Diseases…………….……………………………...... 8

CHAPTER 2: COMPUTATIONAL FLUID DYNAMICS……………………….…..…17

2.1 Background of Computation Fluid Dynamics……………………….………………17

2.2 Physics of Computational Fluid Dynamics…………………………..……………....19

2.3 Computational Fluid Dynamics in Veterinary Medicine……………………….……19

2.4 Specific Aims/Hypotheses………………………………………………………..….20

CHAPTER 3: MATERIALS AND METHODS - AIRWAY...……..…………………...22

3.1 Inclusion and Exclusion Criteria…………………………...………………………...22

3.2. Computed Tomography Procedure…...……………………………………………..22

vii

3.3 Three-Dimensional Mesh Construction…………………………………………….24

3.4 Computational Fluid Dynamics Analysis………….……………………………….25

3.5 Assumptions……………………...…………………………………………………26

3.6 Statistics Methods………………...…………………………………………………28

CHAPTER 4: RESULTS - AIRWAY…...………………………………………………34

4.1 Subject Demographics………………...…………………………………………….34

4.2 Descriptive Statistics and Airway Resistance……………………………………….34

CHAPTER 5: DISCUSSION - AIRWAY……………………………………....……….35

5.1 Discussion…...…..…………………………………………………………..………35

5.2 Conclusions..…..………………….…………………………………………………36

5.3 Limitations………………………….……….………………………………………37

5.4 Future Research………...……………………………………………………………38

CHAPTER 6: MULTI-DETECTOR CARDIAC COMPUTED TOMOGRAPHY…...... 41

6.1 Electrocardiographic Gated Multi-Detector Computed Tomography……………....41

6.2 Specific Aims/Hypotheses………………………………………………………..…46

CHAPTER 7: MATERIALS AND METHODS – CARDIAC..………………………...50

7.1 Case Selection……………………………………………...………………………..50

7.2 Transthoracic Echocardiography…………………………...………………………..50

7.3 ECG-Gated Computed Tomography Angiography………….………………………51

7.4 Volumetric Analysis…………...…………………………………………………….52

7.5 Linear Measurements…………………………...…………………………………...53

7.6 Statistical Methods………………...………...……………………………………….55

CHAPTER 8: RESULTS - CARDIAC.………..………………………….…………….64

viii

8.1 Subject Demographics………………...……………………………….…………….64

8.2 Descriptive Statistics..…………………………………..……………...……………64

8.3 Inter-observer and Intraobserver Results……………………………………………65

CHAPTER 9: DISCUSSION - CARDIAC……………………...………..……..………67

9.1 Discussion…………………………..………………………...………..……………67

9.2 Conclusions…………………………...………………………..……………………69

9.3 Limitations…………………………...………………………..……….……………69

LITERATURE CITED…………………………………………………………………..74

APPENDIX A: DESCRIPTIVE STATISTICS – AIRWAY …………………………...85

APPENDIX B: PHASE OF CARDIAC CYCLE & ABBREVIATION KEY …..……..86

APPENDIX C: DESCRIPTIVE STATISTICS & NORMALITY TEST: CARDIAC….87

APPENDIX D: COMPARISON OF TRANSTHORACIC ECHOCARDIOGRAPHY & MULTI-DETECTOR COMPUTED TOMOGRAPHY…………………………………89

APPENDIX E: INTRA-OBSERVER & INTER-OBSERVER MEASUREMENTS…102

List of Tables

Table 1. Descriptive statistics for age, weight, and airway resistance…………………..85

Table 2. Pearson correlation between age, weight, and airway resistance………………85

Table 3. Computed tomography ED and ES phase for measurements…………………..86

Table 4. Key of abbreviations for measurements of CT and TTE…………………….…86

Table 5. Shapiro-Wilk test for normality left ventricular measurements………………..87

Table 6. Shapiro-Wilk test for normality left atrial measurements…………………...…88

Table 7. Descriptive statistics for cardiac angiography……………………………….…88

Table 8. Significantly different MD-CT and TTE measurements…………………...... 89

Table 9. LA ED descriptive statistics for normally distributed data……………………..90

Table 10. Left atrial end diastolic t-Test comparing means……………………………...90

Table 11. LA ES descriptive statistics for normally distributed data…………………....91

Table 12. Left atrial end systolic t-Test comparing means………………………………91

Table 13. LV ED descriptive statistics for normally distributed data……………………92

Table 14. Left ventricular end diastolic t-Test comparing means……………….………93

Table 15. LV ED descriptive statistics for non-normally distributed data………….…...94

Table 16. Left ventricular end diastolic Wilcoxon-signed rank test……………………..94

Table 17. Left ventricular end diastolic Wilcoxon-signed rank test………………….….95

Table 18. LV ES descriptive statistics for normally distributed data……………………96

Table 19. Left ventricular end systolic t-Test comparing means………………...………97

Table 20. LV ES descriptive statistics for non-normally distributed data………….……98

Table 21. Left ventricular end systolic Wilcoxon-signed rank test……………………...98

Table 22. Left ventricular end systolic Wilcoxon-signed rank test………….…………..99

Table 23. Echocardiography LV volumetric and functional measurements……….……99

Table 24. Computed tomography LV volumetric and functional measurements………100

Table 25. Student’s t-test for MD-CT and TTE volumes for ESV, EDV, SV, and EF...101

Table 26. Coefficient of variation of agreements………………………………………102

Table 27. Inter-observer agreements for transthoracic echocardiography………...……102

Table 28. Inter-observer agreements for multi-detector computed tomography……….103

Table 29. Pearson correlation of CT and TTE for LV ES………………………...……103

Table 30. Pearson correlation of CT and TTE for LV ED…………………………...…103

Table 31. Pearson correlation of CT and TTE for LA ES……………………………...104

Table 32. Pearson correlation of CT and TTE for LA ED………………………...……104

List of Figures

Figure 1. Types of potential interaction between mass and radiation……………………14

Figure 2. Computed tomography of stenotic nares………………………………………14

Figure 3. Computed tomography of elongated and thickened soft palate……………….15

Figure 4. Computed tomography of caudal aberrant turbinates (transverse)…………….15

Figure 5. Computed tomography of caudal aberrant turbinates (zoomed)………………16

Figure 6. Computed tomography of caudal aberrant turbinates (sagittal)……………….16

Figure 7. Schematic for generation of 3-dimensional model…………………………….29

Figure 8. Auto-segmentation of the airway……………………………………………...29

Figure 9. Three-dimensional model of the brachycephalic upper airway……………….30

Figure 10. Change in CT parameters causing change in resistance measure……………30

Figure 11. Three-dimensional model of airway with mask……………………………...31

Figure 12. Computational fluid dynamics model after Navier-Stokes equation………...31

Figure 13. Computational fluid dynamics model in 20 slices (lateral)…………………..32

Figure 14. Computational fluid dynamics model in 20 slices (diagonal)……………..…32

Figure 15. Line graph of resistance change relative to the upper airway anatomy…...…33

Figure 16. Asymmetry of pressure between the nasal passages…………………………40

Figure 17. Dual source multi-detector computed tomography schematic…………….…49

Figure 18. Retrospective ECG gating……………………………………………………57

xii

Figure 19. CT and TTE long axis view of the left ventricle and left atrium………….…57

Figure 20. CT mitral valve annulus measurement………………………………….……58

Figure 21. CT Left atrial chamber measurements…………………………….…………58

Figure 22. CT left venticular length measurement………………………………………59

Figure 23. CT left ventricular mid-level luminal and chordal levellengths……...... 59

Figure 24. CT and TTE interventricular septum and free wall measurements………..…60

Figure 25. Labeled long axis CT of the left ventricle and left atrium measurements……61

Figure 26. Short axis of left ventricle at the level of the papillary muscles……………..61

Figure 27. CT cross-section of the pulmonary valve…………………………….………62

Figure 28. CT and TTE cross-section of the aortic valve…………………………..……62

Figure 29. CT of left ventricular outflow tract and aortic valve…………………………63

Figure 30. CT left ventricular chamber volumes through the cardiac cycle……..………70

Figure 31. CT left atrial chamber volumes through the cardiac cycle……………...……70

Figure 32. CT average left ventricular and atrial chamber volumes…………………..…71

Figure 33. Bland Altman plot comparing CT and TTE for LA end diastolic data………71

Figure 34. Bland Altman plot comparing CT and TTE for LA end systolic data….……72

Figure 35. Bland Altman plot comparing CT and TTE for LV end diastolic data………72

Figure 36. Bland Altman plot comparing CT and TTE for LV end systolic data….……73

xiii

CHAPTER 1: GENERAL INTRODUCTION

1.1 Computed Tomography

Computed tomography (CT) is a cross-sectional imaging modality that has been evolving and improving diagnostic imaging since its introduction in the 1970’s. 1 CT is

now a standard of care in the diagnostic work up for both human medicine and veterinary

medicine. CT utilizes the same radiation properties as conventional radiography; images

are generated from a spectrum of X-ray absorption in tissue of varied physical densities comprised of atoms with different atomic numbers. 2, 3, 4 The defining distinction between conventional radiography and CT is that the X-ray information is acquired in series around the anatomy of interest at numerous angles. 5 The increased number of projections

forms an intricate attenuation map of gray scale digitized in picture elements, or “pixels.”

The pixels are arranged and oriented by a filtered back-projection algorithm into a

sequence of contiguous two-dimensional images.6, 7

The CT system is comprised of two major components; the physical component

and the computer component.8 The physical component is made of four structural pieces: the gantry, the X-ray tube, the detector array, and the table. The gantry houses the anode,

the cathode, and detector electronics.5 The gantry gives the CT its circular shape allowing

the patient to pass through the central aperture while the imaging equipment travels

around the anatomy. The X-ray tube within the gantry is made up of the anode and

cathode, much like the tube in a conventional X-ray machine. The X-ray tube is the

source of the radiation that will be directed to the detector array. The purpose of the

detector array is to collect the radiation energies that pass through the patient and then

convert the projection values into electrical pulses that are transmitted to the computer.9

The table holds the patient and facilitates movement through the stationary gantry

allowing for imaging in the z-axis (cranial-caudal). The computer component consists of the operating system and console that allows for the user and utility to interface.10 The

computer receives the electrical signals from the detector array to generate an image by

back projection based on the numerous attenuation profiles. Computed tomography provides an additional plane of data to imaging. Information is gathered in a longitudinal z-plane axis building on a stacked series of x- and y- axis data.11

Electrons are generated at the cathode through thermionic emission.2 Voltage is

applied to a filament circuit which in turn produces an electron cloud as a result of the

tungsten filament heating up.12 The voltage applied to the filament circuit is set by the

milliamperage (mA); the amount of electrons generated at the cathode is proportional to

the mA setting. A positive potential energy is then established between the anode relative

to the cathode, this is set by the peak kilovoltage (kVp).2 The kVp then transitions into a

kinetic energy providing the inertia for electrons to free photons from the anode. The

angle of the anode bevel directs the photons to transmit through the tissue of the patient

to be collected by the detector array.13 The peak kilovoltage value is the maximum

amount of potential energy provided across the cathode-anode interface. High-frequency

generators and rectifiers minimize the ‘Ripple Effect’, or fluctuation of the voltage,

associated with alternating current letting it act more as a direct current.14 An electrostatic

focusing system coupled with kVp directs the electron cloud from the cathode toward the

focal spot of the anode. Electrons collide with the high atomic number metal of the

anode, most commonly an alloy made primary of tungsten with a small amount of

rhenium. 2 The transfer of energy dissipates mostly as heat, but a small amount of the energy provided generates a spectrum of x-ray photons energies, which may be as high as

the kinetic energy provided by the kVp. 12 The level of energy and the subsequent

interaction with the inherent contrast of bone, soft tissue, and fat creates the tissue

contrast that is reconstructed by the computer portion of the CT unit.

Photons interact with living tissue in a finite number of distinct processes. The

interaction of photons (or gamma-quantum) with tissue is dependent on the energy of the

photon packet, as well as the atomic number of the matter. 15 The energy used for CT and

radiographic studies is relative low on the spectrum of potential energy level, typically

between 60 – 120 peak kilovoltage. Within the spectrum of diagnostic imaging, the most

frequent interactions are Compton scattering, photoelectric effect, Rayleigh (coherent)

scattering, pair production, and photodisintegration (Figure 1). Pair production and

photodisintegration will not be discussed, as their relevance to diagnostic imaging does

not occur until photon energy reaches 1.024 MeV. Rayleigh scattering occurs to relatively low proportion of photons relative to Compton scattering and photoelectric effect for energy used in CT. 2 The photon energy is too low to free an electron. The

photon will interact with the tissue by changing direction, but there is no change in

energy level or absorption by the tissue.15 Since the photon is not absorbed, it may cause

degradation of the image due to the change in path, generating a scatter exposure.

Compton scattering is the most frequent interaction with tissue to occur at

imaging energy levels for CT. The peak kilovoltage of a CT imaging examination is

typically set between 80 – 140 kVp. Compton scattering is the predominant interaction with tissue typically within the range of 0.3 – 3 MeV.3 Compton scattering occurs when an incident X-ray interacts with a peripheral valance electron. The ejection of the electron leads to a change of angle for the photon with a drop in energy. 16 Scattered photons degrade the quality of the image by generating fog within the image. Compton scattering is also a major source of radiation safety for bystanders, which is limited to veterinary personnel by use of sedation, restraint, and distance with barriers. 5 The likelihood of

Compton scattering is independent of the atomic number, but is influenced inversely by the level of energy.12

Photoelectric effect is the second most likely interaction between radiation and soft tissue for energy levels used for CT exams. The photoelectric effect ultimately forms the image. 2 The incident photon is removed after an interaction with a valance electron creating a photoelectron. The lack of passage of the photon through the patient generates a region of attenuation and therefore contrast to the image based on the density of the tissue. The released photoelectron leaves an opening within the valance field around the nucleus. The opening has enough attractive force to pull an electron from an outer shell to fill the void. The cascade of an outer electron to an inner electron position causes the release of a characteristic X-ray.12 Characteristic X-rays are relative low energy and do not generally contribute directly to the energy sensed by the detector array.4 Instead, characteristic X-ray energy does not escape the patient dissipating as heat and/or energy within the surrounding tissue. The likelihood of the photoelectric effect occurring is proportional to the atomic number (Z) and inversely proportional to the energy (E) both raised to the third power of the incident electron.5

Photoelectric Effect ~ Z3/E3

Photoelectric effect and Compton scattering are major contributors of radiation interaction and attenuation in soft tissue within energy level ranges used for CT. 3

Understanding these interactions with photons helps generate a useful quantitative measure of attenuation in CT called Hounsfield Units (HU). CT utilizes tissue density in order to generate an image based on the linear attenuation coefficient and mass attenuation coefficient assigning HU number values to voxels. Linear attenuation coefficient is represented by Greek letter µ. 4, 5, 7

µ = ∆N/N∆x

∆N is the number of photons removed from the X-ray beam. N is the initial amount of photons. ∆x is the thickness of material. A linear attenuation coefficient is set for a given material and energy level.15, 17

Bone, soft tissue, and fat have intrinsic properties that result in specific attenuation values. Hounsfield units utilize the differing linear attenuations that are acquired from thousands of projections from up to 360 degrees around a patient to determine a specific attenuation factor of a volume voxel at a specific coordinate labeled

µ (x,y,z) in the three axes.4 The µ acquired from tissues are compared to a known linear attenuation coefficient of water (µw), which has been assigned the Hounsfield unit of 0.

The computer component assembles linear attenuation coefficients throughout the body and then translates those values relative to water to generate a gray scale image.8 Tissues like bone that has a high linear attenuation coefficient relative to water are assigned

positive numbers, while tissues like fat and gas that have low attenuation coefficients are

negative. The system of Hounsfield units works on a spectrum of -1024 to +3000.

The CT machine coordinates the movement of the anode and cathode relative to

the detector array. The X-ray tube and the detector array are oriented opposite to each

other with the patient positioned within the trajectory of the photons. How the pieces of

equipment move differs between the various generations of CT.6 Gathering attenuation

profiles at various angles improves the spatial information that is lacking with two-

dimensional radiographs. The additional dimension for interpretation overcomes the

superimposition of complex anatomy.

The four generations of CT are schematically different reflecting the growth of technology and improvement of the computers and machinery in the medical field.3, 4

First generation scanners are single detector scanners, also referred to as ‘pencil beam’ or translation/rotation scanners. First generation scanners use parallel beam projection with rigid lateral movement to make a single projection then the system rotates around the central gantry.1 The major disadvantage of the first generation scanner is the longevity of the scan time. Second generation scanners improved upon the temporal problems of the first generation scanner. The most important improvement between the first two generations is the addition of larger number of detectors in the array. Second generation scanners are called partial ‘fan-beam’ or translation/rotation multiple detector.4 The fan- shaped beam of radiation covers a larger portion of the patient reducing the time required to image the entire sample.

Third generation scanners eliminated the z-axis ‘step-and-shoot’ movement coordinated between the X-ray tube and the detector array. The movement of the third

generation scanner is exclusively rotational centered on the field of view. The slip-ring technology enabled scanners to acquire ‘helical’ or ‘spiral’ scans continuously around the patient.18 Third generation scanners are also called continuous rotation or rotate/rotate scanners. 7 The fourth generation of scanners is slightly different than the third

generation. Third generation scanners had both the X-ray tube head and detector array move in a coordinated fashion around the patient; however, the fourth generation has a fixed detector array with a rotating X-ray tube head. Fourth generation scanners are referred to as rotate-fixed scanners.3

Growth of CT technology has brought about a significant decrease in time required to complete a scan. An objective for every CT study is to balance time and resolution. Study parameters are chosen to minimize the time required for acquisition of the study while maximizing the image resolution. Conventional methodology for

veterinary medicine is to have patients placed under general anesthesia to minimize

motion to allow for imaging. Intubation of the patient allows for control of the airway for

breath hold techniques to minimize thoracic motion associated with respiration. Many of

the CT units in veterinary medicine do not have the temporal resolution to overcome the

breathing pattern of animal patients without the use of the breath hold technique. Patient

compliance in human medicine is accomplished by verbal communication between the

imaging team and the patient to minimize motion.

Cardiac motion is another obstacle that can be minimized with improved temporal

resolution and gating techniques. Dual-source computed tomographic units with multi-

detector arrays help improve temporal resolution. The area a multi-detector array and

tube are required to cover to generate an image is halved if two sources are used.19, 20 The

larger number of detectors for the detector array enables a larger region of anatomy to be

imaged simultaneously. Increasing the overall number of individual detectors makes for a

larger imaging target while allowing for each detector to maintain a small cross-sectional

size and therefore improve resolution.4 The dichotomy of gating techniques includes

prospective and retrospective gating. Prospective gating is also referred to as triggered

gating. The CT imaging is initiated by simultaneous use of an electrocardiogram.21, 22 The

prospective gating is prompted to start at a certain part during the cardiac cycle. In

theory, imaging will occur at the same point within a cardiac cycle each time. Prospective

gating offers the benefit of reducing the overall dose to the patient since image

acquisition is only during a short portion of the cardiac cycle without sacrificing

resolution.23, 24 The alternative method is retrospective gating. Computed tomography

acquires images continuously while collecting concurrent electrocardiogram data.21 The

computer associated with the CT unit then assembles the imaging information along side

the ECG information to reconstruct the entire cardiac cycle. Since information is

continuously gathered from the CT, the radiation dose to the patient is higher.21 Benefits

of retrospective gating include continuous data for functional analysis as well as a lower

appreciable amount of artifacts.22, 25

1.2 English Bulldog Congenital Diseases

The English bulldog continues to grow in popularity.26 The breed is predisposed

to multiple congenital disorders; many that may have a negative impact to the health of

the dog. Congenital defects are often concurrent and have been described within multiple

organ systems for the English bulldog. Commonly observed defects of the English

Bulldog include the brain (ventriculomegaly), spinal column (hemi-vertebrae and block

vertebrae), distal extremities (chondrodysplasia), respiratory (brachycephalic syndrome

with hypoplastic trachea), and cardiac (pulmonic stenosis, ventricular septal defect, and

coronary anomalies).27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42 Despite the recognition of the numerous problems within the breed, English bulldogs remain among the more commonly owned dog breeds. To minimize the potential morbidity associated with congenital anomalies, veterinarians intervene to minimize risk of developing respiratory and cardiovascular disease. 43, 44

Heterochronic growth patterns have been suggested to explain the wide diversity

of shapes and sizes of the dog (Canis lupus familiaris). Heterochrony describes varying

patterns and growth rates of cranial sutures and grow plates resulting in a spectrum of sizes and shapes within one species. 45, 46 The English bulldog, and other brachycephalic

breeds, have a shortened facial shape. Brachycephalic breeds have arisen from

generations of selective breeding to amplify and maximize the desired features, humans

have aided in the evolution of many different forms of dogs. In humans, early closure of the spheno-occipital suture lead to a premature craniosynostosis of the centers of growth

causing stunted elongation of the skull.47, 48, 49, 50 A veterinary comparison is seen with

early closure of the spheno-occipital synchondrosis resulting in shortened rostral to

caudal plane for the skull in the Cavalier King Charles Spaniel.51 As dogs diverge from a

work-related function to a companion purpose, appearance is among the most desired trait selected.

Shortened craniofacial skull conformation provides insufficient space necessary for appropriate intranasal development.45 The abnormal shape of the nasal cavity is thought to develop in an incongruent (heterochronic) growth pattern with truncation of

the bones of the base of the skull, as well as the exterior facial bones while the nasal/ethmoid turbinates continue to grow.52 The consequence is a nasal cavity with

many convoluted, intricate scrolls of bone with overlaying congested mucosal tissue.53

The intertwining of structures causes increased mucosal contact points with resultant

diminished intranasal passageways with a relative excess of nasal turbinates.54 The lack

of space for growth of these nasal bones culminates in aberrant rostral and caudal

turbinates that occupy the airway passage, which may further potentiate airflow

impedance.55, 56 Brachycephalic airway syndrome (BAS) is used to summarize the effects

of the anatomic anomalies that negatively impact the airway.57 Despite a high prevalence

and wide spectrum of affliction within brachycephalic breeds, there is a lack of

quantitative measures to help characterize how severely individual dogs may be

affected.58, 59 Previous work has used a combination of video-endoscopy and barometric

whole-body plethysmography to evaluate brachycephalic airway disease with no

significant correlation to severity of clinical signs.60, 61

Brachycephalic syndrome is a multifaceted collection of respiratory associated

structural anomalies of which each contributes to an overall compromise of airway

patency. Anatomically the various abnormalities span from the nares to the distal

trachea.62 The severity or number of abnormalities an individual may have is difficult to

assess with external evaluation alone. Brachycephalic breeds like English bulldogs may

live with little to no clinical signs; however, more severely affected dogs may develop

respiratory distress with the potential of death.56 Surgery is the current therapy of choice

to address conformational obstruction and airway hindrance.63 The goal of surgery is to

reduce the upper airway resistance; however, at this time there is a lack of quantitative

tools to objectively assess if a reduction in resistance occurs post surgery.

Brachycephalic syndrome summarizes a combination of primary and secondary

problems. An archetypical description of this syndrome includes stenotic nares (Figure

2), elongated and thickened soft palate (Figure 3), laryngeal collapse, everted laryngeal

ventricles (saccules), plus or minus a hypoplastic trachea. 43, 44, 64, 65 However, more recent literature investigated additional factors that may contribute to the impedance of airflow; these include increased mucosal contact points of the nasal turbinates, nasopharyngeal turbinates (caudal aberrant turbinates), rostral aberrant turbinates, macroglossia, and amgydalitis (Figure 4, Figure 5, Figure 6).52, 54, 66 Excess tissue

obscures an already highly restrictive airway leading to a further increase of resistance.

The upper airway impedance is thought to generate altered exaggerated pressures leading

secondary changes like everted laryngeal saccules and laryngeal collapse.58 Airway

compromise has generated concern with the quality of life for brachycephalic dogs that

are consistently working hard to maintain oxygenation. A dog owner questionnaire has

highlighted an increased frequency of stertorous breathing noises, exercise intolerance,

significant heat sensitivity, and prolonged recovery times after exertion of energy.68, 69

The increased upper airway resistance of BAS has also been implicated in an increased

rate of gastrointestinal disease like gastroesophageal reflux disease.63

A large percentage of airway resistance within brachycephalic dogs is thought to

arise from the initial nasal cavity as air passes through the narrow aperture of the nares

and then into convoluted nasal turbinates. The nasal cavity contributes 76.5% of the total

airflow resistance in non-brachycephalic dogs with the larynx and bronchi contributing

4.5% and 19%, respectively.69 The nasal cavity resistance increases to 80% in brachycephalic dogs.69 The rapid increase of resistant airway dynamics is similar to humans, especially with those afflicted with nasal airway obstruction (NAO) secondary to complex nasal defects.70 The English bulldog has been used as a reliable model for sleep apnea in people.71

Computational fluid dynamics (CFD) has recently become a tool to aid surgical planning in humans with nasal airway obstruction. 72 Personalized models of individuals are created from a CT study to test mechanics of flow through an ex vivo model to aid surgical planning. Studies have shown that this tactic may be used before surgery and then following surgery to quantitatively assess functional outcomes of surgical intervention. 73, 74 To the author’s knowledge, this technology would be a novel approach to evaluating upper airway resistance in veterinary medicine.

Avoiding strenuous activity is critical to managing dogs with brachycephalic syndrome. When activity restriction is not sufficient, surgical intervention is a keystone treatment for BAS dogs.43 Surgical techniques may include alar wedge resection or alaplasty, partial staphylectomy, and laryngeal ventriculectomy.75, 76, 77 Overall, the prognosis for surgery is good with low perioperative morality; however, there is little explanation for why some dogs do not respond well to surgery.63, 78, 79

Recent theories acknowledge possible additional structural aberrancies contributing to the respiratory resistance associated with brachycephalic airway syndrome. With dogs afflicted to differing degrees, there is a critical need to address the reality that empiric surgeries may resolve a majority percentage of the population, but not all dogs. Contributing factors, such as increased mucosal contact points and aberrant

turbinates, remain unaltered by conventional surgical techniques.52, 54, 66 One of the obstacles to fully assessing the severity of BAS is that currently there is no single modality to capture a global picture. Current diagnostics may include antegrade rhinoscopy, retrograde rhinoscopy, sedated airway examination, thoracic radiographs, and lateral cervical radiographs. A flaw in this work up is that the most internal nasal turbinates may not be visualized.

Figure 1. Types of potential interaction between mass and radiation. Adapted from Bushberg, JT. The Essential Physics of Medical Imaging. 3rd ed. Relationship of energy and mass attenuation coefficient for the types of potential interaction between mass and radiation. Diagnostic imaging typically uses radiation levels between 60 - 120 keV. Photoelectric effect predominates at lower level energy, whereas Compton Scattering is more common at higher energy.

Figure 2. Computed tomography of stenotic nares. Computed tomography of stenotic nares. Transverse image at the rostral nasal planum. Dog is in ventral recumbency with the right side of the dog in the left aspect of the image. White arrows highlight the stenotic aperature of the nares.

Figure 3. Computed tomography of elongated and thickened soft palate. Computed tomography of elongated and thickened soft palate. Sagittal reformat on midline. Dog is in ventral recumbency with the rostral skull oriented to the left of the image. White arrow points to thickened/elongated soft palate.

Figure 4. Computed tomography of caudal aberrant turbinates (transverse). Computed tomography of caudal aberrant turbinates. Transverse image at the choanae. Dog is in ventral recumbency with the right side of the dog in the left aspect of the image. White arrows highlight the caudal aberrant turbinates.

Figure 5. Computed tomography of caudal aberrant turbinates (zoomed). Computed tomography of caudal aberrant turbinates (zoomed). Transverse image at the choanae. Dog is in ventral recumbency with the right side of the dog in the left aspect of the image. White arrow highlights the caudal aberrant turbinates.

Figure 6. Computed tomography of caudal aberrant turbinates (sagittal). Computed tomography of caudal aberrant turbinates. Parasagittal reformat just off midline. Dog is in ventral recumbency with the rostral skull oriented to the left of the image. White arrow points to caudal aberrant turbinates that have retroflexed into the nasopharyngeal meatus.

CHAPTER 2: COMPUTATION FLUID DYNAMICS

2.1 Background of Computational Fluid Dynamics

Fluid motion has been studied and developed for centuries. Among the earliest

work exploring the fluid science is attributed to Leonardo Da Vinci in the 15th century.

Early work was brought about by a necessity to divert water sources from village to

village through elaborate canals.80 Isaac Newton was the next profound contributor to the field defining his three laws of motion. The most apropos is the second law of motion describing the sum of the vector of external forces on a system is equal to the mass of that object times its acceleration, or F = ma.81 Pertinent to our current study, Claude Navier and George Stokes built upon the work by Leonhard Euler to better understand the flow of a viscous substance through system, which is used as the basis for modern day CFD.82

It was the sophistication of computer growth of the late 20th century that facilitated

exponential growth of CFD converting from physical models into the digital medium

through refinement of computer programing.83

Medical CFD parameters used to construct models are derived from anatomy. It is

critical to acknowledge that the CFD flow is carried out in a virtual world; therefore, the

results of CFD are a theoretical product. The theoretical products have been tested with

reliable results that have forecasted results and demonstrated real life outcomes. A highly

accurate model and methodology is a valuable tool to improve medical care.

The value of CFD is irreplaceable in the physical sciences. Computational fluid dynamics is used in biomedical engineering, meteorology, oceanography, urban city planning, aeronautic construction, and thermal heat transfer and conduction.80, 81, 84, 85, 86,

87, 88 Computational fluid dynamics derived sleep apnea models in people replaced

English bulldogs.71, 89 A CFD laboratory can be established as a computer laboratory

without the necessity of acquiring cumbersome physical equipment, limiting the waste of

perishable material, and minimizing the upkeep of the laboratory. Requirements for CFD

modeling include a computer with adequate storage and random-access memory (RAM)

power as well as the software necessary to create meshes for CFD modeling. Unlike

traditional experiments, a wide breadth of models can be run using the same few tools.88

For laboratories that model CFD on a massive scale like weather patterns or plane aeronautics, an in vivo laboratory may not be feasible.

CFD allows a researcher to test a model at a variety of settings or quantities

simultaneously. The ability to run experiments simultaneously is referred to as ‘in

parallel’. An in vivo model may provide physical manipulation of the subject, as well as

provide quantitative values derived from a tangible model; however, only one test may be

run at a time - experiments are carried out in a serial fashion. The shortcomings of CFD are that results are predictions based on input information. Errors with CFD originate from modeling, discretization, iteration, and implementation. Traditional experiments are not without their own source of errors as measurement errors and equipment malfunction may negatively impact results.

2.2 Physics of Computational Fluid Dynamics

Computational fluid dynamics is based on fluid mechanics. The scope of CFD

will be focused to the Navier-Stokes equation. Navier-Stokes equations are used for models investigating the behavior of viscous, incompressible material.90 The equation

describes the relationship between velocity, pressure, temperature, and density of a

moving material.85 The derivation of the Navier-Stokes equation is extensive with

thorough previous vetting that is referred to within multiple textbooks.85, 86, 87, 90, 91 It is

common practice within the CFD field to use equations as an accepted reference.

Newton’s second law is a foundation in the development of the Navier-Stokes equations.87

2.3 Computational Fluid Dynamics in Veterinary Medicine

The pillars of responsible animal use in research are replacement, reduction, and

refinement.92 CFD remains underutilized for research in veterinary medicine despite the

potential to replace an animal model with a digital platform. CFD can help overcome

many of the animal welfare concerns. Animal welfare laws and committees across the

world have established the need to minimize unnecessary use of live animals in research.

CFD fills a niche that can enable an investigator extensive planning prior to involving

live animals. Multiple models can be run within the computer model at various operating conditions aiding to the reduction of animals used without having to limit the scope of research. Refinement of procedures and research method can be improved upon digitally

and then translated back into the animal model.

The field of CFD in veterinary medicine is yet to be developed. Conversely, CFD is used in research addressing human medical conditions such as nasal flow disease,

lower airway disease, Eustachian tube/middle ear disease, stenosis of the coronary vasculature, and aortic/peripheral vascular disease.73, 88, 93, 94, 95, 96, 97, 98 Human practitioners can utilize a CT study to generate a three-dimensional mesh. Flow through the model can be assessed and direct decision making used to customize surgical intervention for the individual patient.73 The most developed research involving CFD within a veterinary model has been directed to particle flow distribution during olfaction in dolichocephalic dogs. 99, 100, 101, 102 Other work has included the equine respiratory system, mouse cardiovascular, and water flow over fish gills. 103, 104, 105 The increased accessibility to cross-sectional imaging modalities like CT and magnetic resonance imaging at veterinary hospitals will increase the opportunity to utilize a resource like

CFD after further development.

2.4 Specific Aims/Hypotheses

The first specific aim of this study was to determine if a CFD value of airway resistance could be determined using a three-dimensional mesh generated from CT data.

We hypothesize that using CT data from a brachycephalic dog, a model could be generated to determine an airflow resistance value. The second specific aim was to determine a value for airway resistance of a sample of English bulldogs. A third specific aim was to determine if there was a correlation between the airway resistance values with age, weight, or clinical signs. We hypothesize that there will be no correlation between airway resistance with age or weight.

Computed tomography also enables a practitioner to assess for subclinical lower airway disease by simultaneously evaluating both upper airway and lower airway structures. We aim to provide an imaging method that will help quantify upper airway

brachycephalic airway syndrome while also screening for underlying asymptomatic

aspiration pneumonia prior to surgery. A computed tomographic scanner with a high

number of detectors minimizes the time required for imaging. Unfortunately, CT

scanners with a fewer number of detectors are more common within veterinary medicine.

The longer acquisition time of traditional scanners necessitates general anesthesia to

facilitate a patient compliant enough for a study of diagnostic quality. The prolonged

anesthesia increases the risk to develop aspiration pneumonia, especially in

brachycephalic breeds.106, 107 We will evaluate the use of a 128-detector multi-detector

CT scanner as a feasible method to rapidly acquire diagnostic quality images without the need of general anesthesia to assess English bulldogs for brachycephalic syndrome.

Additionally, computed tomographic studies can then be used to generate individual ex vivo models of English bulldogs for CFD to quantify and characterize airway resistance through the nasal cavity.

CHAPTER 3: MATERIALS AND METHODS – AIRWAY

3.1 Inclusion and Exclusion Criteria

Twenty-one privately owned English bulldogs were recruited for this study from clients of The Ohio State University Veterinary Medical Center. English bulldogs were

recruited due to the prevalence of brachycephalic airway syndrome within the breed.

Medical history for each patient was obtained. Owners completed a survey assessing

airway disease clinical signs at home. The dogs underwent routine physical examination,

cardiovascular examination, and a thorough screening echocardiogram. Dogs were

excluded from the study if they were unable to be sedated for CT study. Dogs were also

excluded if there was previous history of airway surgery or facial trauma. Informed client

consent was obtained for all dogs and the study was approved by the Institution Animal

Care and Use Committee as well as the hospital Clinical Research and Teaching

Advising Committee.

3.2. Computed Tomography Procedure

Computed tomography examinations were performed using conscious sedation.

The dogs were not intubated during the CT scan. Dogs received an intramuscular

injection of butorphanol (0.2 mg/kg) and dexmedetomidine (5 to 10 mcg/kg) 30 to 45

minutes prior to scheduled CT scan. A cephalic venous catheter was placed to maintain

vascular access and standard anesthetic rate of intravenous fluids provided during the

imaging. Atropine (0.04 mg/kg) or glycopyrrolate (0.01 mg/kg) were given on an

individual case by case basis or if clinically-significant bradycardia as determined by a board certified veterinary cardiologist. Anesthetic monitoring (ECG, pulse oximetry) was performed throughout the imaging. Dogs were under direct supervision until deemed adequately recovered from sedation.

The dogs were positioned in sternal recumbency with the neck extended, the forelimbs slightly abducted, and the hard palate parallel to the CT table with table straps to help secure the dog in place. A dual source 128-MD-CT unit (Somatom Definition

Flash, Siemens Healthcare) equipped for cardiac gating with temporal resolution of 75 ms and maximum scanning speed of 458 mm/s was used to perform the scans. The gantry angle was set to 0 degrees. The topograms were acquired in laterolateral and dorsoventral views to plan the slice series. Scan parameters were carried out with a fluctuating filament current that had a maximum milliamperage of 495 mA and fluctuating tube current of 100 – 120 kVp. The region of interest was scouted to include rostral to the nasal planum through the caudal aspect of the diaphragm. The region of interest for the scan included from rostral to the nasal planum to caudal to the mid-cervical region. The

CT dataset was reformatted with soft tissue and bone algorithms with appropriate window level and window width Hounsfield units to optimize conspicuity of upper airway structures. The slice thickness was acquired at a maximum of 1 mm. The spiral pitch varied from 0.17 to 0.65 based on the electrocardiogram as the dogs were also imaged using cardiac-gating for a second study focused on cardiac angiography.

Intravenous contrast was not administered for the airway portion of the study.

The CT dataset was reformatted into dorsal, transverse, and sagittal planes with the ability to manipulate multiplanar reformats. The datasets were saved as DICOM files

and studies were stored on the local picture archiving and communication system

(PACS).

3.3 Three-Dimensional Mesh Construction

The raw MD-CT bone algorithm transverse dataset was imported into ScanIP software (Simpleware, Version 7.0) (Figure 7). The region of interest included rostral to the nasal planum to the laryngopharynx. Borders of the images were cropped to include the upper airway from the nasal planum to the caudal aspect of the soft palate while ensuring the lateral and dorsal margins of the nasal cavity and nasopharyngeal meatus were included. The rostral border was cropped at the first image in which the nasal apertures, at the confluence of the wing of the nostril, were closed off to the external surroundings. A threshold was applied to the CT layers by automatic segmentation using

-1024 to -450 Hounsfield units (HU) to highlight the airways (Figure 8). A fill threshold was then applied to isolate the air-filled nasal passage throughout contiguous images generating a mask of the nasopharyngeal passage. Still within the ScanIP program, a

CFD model was applied to the nasopharyngeal mask. The only parameter altered was changing the minimum edge length of the tetrahedral units to 0.3 mm. If a three- dimensional mesh was not able to be constructed using 0.3 mm edge lengths, the model was reattempted by increasing the minimum edge length at 0.05 mm increments (Figure

9). Analysis of methods to refine the 3D mesh showed that altering parameters like the

size of the CT slice interval and the minimum edge length changed the overall resistance

measurement (Figure 10). The characteristic pressure curve through the airway decreases

with smaller edge length and smaller slice interval. Theoretically, the smallest possible

parameter would most accurately represent the anatomic structure; however, as the model

size approaches an absolute representative measure the resistance plateaus out with a

diminished overall change in the calculated value. The CFD model then generated a three-dimensional surface mesh that was exported as a MATLAB file (Figure 11).

The three-dimensional surface mesh model was then imported into COMSOL

Multiphysics 5.0 with MATLAB® (COMSOL, Inc., Version 5.0.1.276) for CFD

modeling and calculation of airway resistance. The Ohio State University Biomedical

Engineering research group with focus of CFD determined the parameters for modeling

airway CFD evaluation. Parameters were selected to test the flow of material consistent

with incompressible air oriented from rostral to caudal with a constant velocity.

The repeatability of calculating airway resistance was evaluated in three English

bulldogs. The generation of a second 3D mesh was repeated with the same procedure

within the ScanIP program from contiguous transverse CT DICOM files using identical

parameters. The mesh was then imported into COMSOL Multiphysics 5.0 with

MATLAB® to test the CFD for a second time. The repeatability was variable; the second calculation of airway resistance measured 79.0%, 95.3%, and 93.2% similar to the initial calculation for these 3 dogs.

3.4 Computational Fluid Dynamics Analysis

Computed tomography DICOM files were uploaded into the Scan IP software to render a three-dimensional mesh with finite borders. The three-dimensional meshes were exported as COMSOL Multiphyscis 5.0 with MATLAB® compatible files then uploaded

to apply CFD. The mesh was considered a rigid structure. The properties of the fluid

were maintained between all of the dogs. The properties were set to mimic air at

environmental conditions. An iterative solver was used for calculation of the equation.

Airway resistance maps were generated as color-coded overlays representing the shape of

the upper airway anatomy (Figure 12). Resistance values were calculated in Pascals per liter per second using a surface average of slices at each 5% interval throughout the airway (Figure 13) (Figure 14). The 0% slice was set at a resistance value of zero and it was considered the first slice at which the nasal passage was completely closed off. The

100% was established as the most caudal aspect of the soft palate just prior to the confluence of the nasopharynx and oropharynx into the laryngopharynx. The directional flow of the CFD equation was set as rostral to caudal, therefore the pressure values are 0 at the 0% slice and then pressure accrues moving caudally through the airway to the

100% slice. The most caudal slice then had the highest pressure. Resistance was considered a marker of the change in pressure between the slices. The greater degree of increase in pressure is demonstrated by a change in color for the color flow maps, as well as a greater slope on the line graph (Figure 15).

3.5 Assumptions

Assumptions were made to simplify the computational fluid model. The first assumption is that computed tomographic anatomy generated for CFD models are an adequate representation of the in vivo anatomy. The computer model is constructed as a rigid structure and considered static to physiologic processes. Mucosal soft tissue engorgement associated with alternating congestion and decongestion nasal cycling was not considered in this model.108 Computed tomography is a routine, reliable non-invasive

tool that is used clinically for anatomic evaluation. A decision was made to apply a

uniform rigidity to the entire model after three-dimensional reconstruction.

Computational fluid dynamics takes into account the interaction of a material passing

through the digital airway boundaries; in vivo friction, pliability, and resistance are

expected to occur. The interaction between the margins and the moving substance will

affect the overall resistance, but were not considered in this model for improved simplicity.

The anatomy examined in our models is comprised of two distinct anatomic locales; the nasal cavity incorporating the hard palate and the nasopharyngeal meatus of the soft palate. The nasal turbinates contain a latticework of fine skeletal scrolls that form a stiffer framework. However, caudal to the hard palate, the soft palate lacks underlying stiff bony structure. The model assumes interaction of the fluid material to occur between

an inelastic material and air. Future work may involve construction of a model that examines the flow resistance with a rigid portion through the turbinates and then a flexible model to represent the soft tissue soft palate and nasopharyngeal borders.

The velocity of the airway was standardized to a set value of 0.5 L/s. Developing the CFD model requires an in flow rate. The 0.5 L/s value was used based on work by

Craven100 which was found when formulating an olfaction model for CFD. The flow rate

0.5 L/s was determined to represent sniffing, a rapid inhalation of air. The velocity required to deliver flow of air particles through the dorsal nasal meatus to the concentration of olfactory sensors was found to be higher than normal respiration.101

Therefore, the velocity used in our CFD model was likely to overestimate the actual flow

rate of respiration. An increased velocity theoretically causes an increased value of

resistance.109, 110, 111 The absolute value of the velocity may influence the absolute value

of airway pressures, however, the standardization of a single velocity made for a uniform

parameter between dogs. Models with a Reynolds number that exceeded 2,000 were

determined to be turbulent and therefore were excluded from the use of the Navier-Stokes equation.82

The ‘air’ applied to the CFD models was assigned an incompressible quality. This

decision was also made to simplify the overall model and make for a uniform CFD within

the population of dogs. A compressible model would require more extensive calculations

with more complex iterations that may fail in an intricate model such as nasal turbinates.

These assumptions may limit the utility of the overall absolute value of pressure

within the models. Standardizing the parameters of the model allow for comparison

between dogs, as well as assessing the change in pressure over distance in the individual

model.

3.6 Statistical Methods

Statistical analysis was performed by two of the authors (E.T.H. and B.A.S.)

using commercial software (SPSS Software, Version 22.0.0, IBM Corp, Armony, NY).

Descriptive statistics were calculated by operator and examined for normality using

inspection of scatterplots and the Kolmogorov-Smirnov test. The distribution of the

overall data set was non-normal.

Figure 7. Schematic for generation of 3-dimensional model. Raw CT data and image processing occurs at CT unit. Image registration, image segmentaiton, and mesh surface generation is done using ScanIP computer program. Three-dimensional surface model is imported into COMSOL Multiphysics 5.0 with MATLAB®

Figure 8. Auto-segmentation of the airway. Hounsfield threshold of -450 to -1024 with green mask.

Figure 9. Three-dimensional model of the brachycephalic upper airway. The final product of the ScanIP program after image registration, image segmentation, and mesh surface generation. The mesh is imported into COMSOL Multiphysics 5.0 with MATLAB®

Figure 10. Change in CT parameters causing change in resistance measure. On left: Airway resistance (Pa/L/s) measured from a model generated form 1.25 mm CT slice interval. The legend represents the different minimum edge length in mm. On right: Airway resistance (Pa/L/s) measured from a model generated form 0.625 mm CT slice interval. The legend represents the different minimum edge length in mm. As the parameters used to generate the 3D mesh become smaller, the overall calculated resistance decreases.

Figure 11. Three-dimensional model with mask. Mask overlay of the brachycephalic upper airway using the ScanIP program is turned on. The final product of the ScanIP program after image registration, image segmentation, and mesh surface generation. The mesh is imported into COMSOL Multiphysics 5.0 with MATLAB®

Figure 12. Computational fluid dynamics model after Navier-Stokes equation. COMSOL Multiphysics 5.0 with MATLAB® model of pressure generated using CFD Navier-Stokes equation. Scale is measures pressure is Pascals. Low pressure areas are blue and high pressure areas are dark red.

Figure 13. Computational fluid dynamics model in 20 slices (lateral ). Computational fluid dynamics model divided into 20 equally distributed slices. Lateral projection of the airway. The rostral airway is to the left. The scale measures pressure in Pascals; the low pressure is blue and high pressure is dark red.

Figure 14. Computational fluid dynamics model in 20 slices (diagonal). Computational fluid dynamics model divided into 20 equally distributed slices. Diagonal projection of the airway. The rostral airway is to the left. The scale measures pressure in Pascals; the low pressure is blue and high pressure is dark red.

Figure 15. Line graph of resistance change relative to the upper airway anatomy. Line graph representing the change of resistance relative to the upper airway anatomy. The dotted line is the overall average change in resistance of the 21 English bulldogs. Each line represents one dog. 19/21 English bulldogs had the greatest step up of resistance within the first one-third.

CHAPTER 4: RESULTS - AIRWAY

4.1 Subject Demographics

Twenty-one English bulldogs without history of airway surgery or cranial trauma

were enrolled in the study. The average age was 28.5 months (range of 2.9 to 108.6

months) (Table 1). Four castrated males, eight intact males, four spayed females, and five

intact females were enrolled.

4.2 Descriptive Statistics and Airway Resistance

Airway resistance varied widely; mean and SD of 9,859.19 +/- 12,818.53 Pa/L/s.

The greatest step up increase of resistance occurred within the rostral one-third of the airway in 19/21 dogs. The remaining two dogs had the greatest increase in resistance occur in the caudal one-third airway, at the level of the confluence of the nasopharynx into the laryngopharynx (Figure 14).

Airway resistance did not correlate with age (r = 0.344, P = 0.126) or weight (r =

-0.058, P = 0.803) (Table 2).

CHAPTER 5: DISCUSSION - AIRWAY

5.1 Discussion

Mapping the changes of airway pressure through the model is a valuable tool for

addressing management of disease. An CT-based non-invasive tool to objectively to

measure the airway resistance has not been previously described. To the author’s

knowledge, CFD has not been used in the brachycephalic dog to map, model, and

measure pressure changes within the nasal passage. Current surgical intervention to

address airway obstructive disease includes widening the nasal apertures and removal

redundant tissue within the caudal pharynx caused by the soft palate. Our data shows that

the greatest step up of airway resistance occurs within the rostral third of the upper

airway, which includes not only the nasal apertures but also the nasal turbinates (Figure

14). We chose to broadly divide the airway into thirds. The rostral one-third includes the

nasal planum to the rostral aspect of the frontal sinus. The middle one-third includes the frontal sinus into the choanae ending at the pterygoid bone. The caudal one-third extends from the caudal pterygoid bone/hard palate to the confluence of the nasopharyngeal meatus/soft palate to the laryngopharynx. The rostral one-third of the airway involves lacy scrolls of bone with edematous mucosa.

Edematous mucosa has been proposed as a complicating factor to airway disease, but surgical correction in this area has not become routine. Nasal turbinectomy using a diode laser has been proposed and performed, but this intervention has yet to become

common practice.112, 113. Complications observed after nasal turbinectomy included regrowth and hyperplasia of the turbinates in between 65%-98% of brachycephalic breeds, which negated the effectiveness of the procedure.114 Regrowth of nasal turbinates

with recurrent increased airway resistance is also seen in people after turbinectomy.115

Asymmetry of the airway pressure between the two nasal cavities was identified

in one dog (Figure 16). The differing pressures may indicate that the nasal cavities are afflicted to different degrees. The discrepancy of pressures between the nasal cavity may

be a consequence of deviation of the nasal septum; septal deviation has been identified in

21% of brachycephalic dogs in a post-mortem study.66 Surgical intervention may be

directed to alleviate pressure within the more affected side so minimize trauma caused by

surgery. Directing efforts to the region of the anatomy contributing to the greatest change

in pressure would maximize the impact of surgery. Nasal cycling is a normal

phenomenon in which the nasal mucosa associated with the turbinates sporadically

engorges and then recedes. Nasal cycling is a potential confounding factor that may alter

the measure of resistance utilizing CT to generate meshes for CFD.108

5.2 Conclusions

Twenty-one English bulldogs successfully had CFD applied to a three- dimensional finite element model construction using upper airway CT studies. Our study

shows that cross-sectional CT can provide a method for generating computer based three- dimensional models to apply CFD. A numeric measure of airway resistance is achievable to quantify airway disease. The assistance of a characteristic curve demonstrates the elevation of pressure through the upper airway passage. Visualizing the change in

pressure over distance within the anatomy of the bulldog correlates the impedance of

flow with structures from the nasal planum to the caudal nasopharynx.

A wide degree of variation for the quantified resistance is observed between the

twenty-one English bulldogs within this study. This population of English bulldogs were not clinically affected to the same degree supporting the theory that brachycephalic

syndrome is a spectrum. Unfortunately, the poor compliance by owners to complete

surveys made statistical correlation to clinical signs not possible.

5.3 Limitations

We focused the model to include the airway from the nasal planum to the caudal

soft palate. The model was directed to encompass anatomy addressed by surgery. The

model excluded other components of brachycephalic airway syndrome, including

hypoplastic trachea, everted laryngeal saccules, or laryngeal collapse. The thoracic inlet

ratio to tracheal lumen diameter of the English bulldog is significantly lower than other

breeds, which likely contributes to the over airway resistance.28, 32 Hypoplastic tracheas

are medically managed and therefore do not act as a source of surgical intervention. The

model also excluded the dynamic component of brachycephalic airway syndrome, which may include laryngeal collapse and a soft palate that may intermittently obstruct flow

depending on freely movable tissue. Decreasing the overall radius of a tubular system

such as the nasopharynx will increase the overall resistance to the fourth degree,

according to Poiseuille’s Law.116 The chronic increased resistance has been theorized to

culminate in terminal stage airway disease of laryngeal collapse. No dogs investigated in

this study had everted laryngeal saccules or laryngeal collapse.

5.4 Future Research

Using the information and methodology produced with this study, we plan to quantitatively assess brachycephalic airway syndrome in dogs pre- and post surgery.

Current methods to evaluate brachycephalic airway syndrome and response to surgery are subjective measures. Evaluation involves direct visualization of the external nares and oropharynx with surgical intervention aiming to resect the presumed obstructive tissue within the nares, soft palate, +/- larynx. Clinical outcomes after surgery are variable. A non-invasive method to objectively assess if a reduction in airflow resistance is achieved

by current surgical techniques does not exist. The aim of our follow up study is to

evaluate a novel CT-based quantitative measure of airflow resistance in brachycephalic

dogs before and after surgical intervention.

Clients will fill out an airway severity score using a survey to assess the dog’s clinical signs related to brachycephalic airway syndrome prior to surgery. Under sedation and without orotracheal intubation, each dog will have a CT scan of the upper airway

performed. Advanced imaging software will be used to generate a high-resolution three-

dimensional mesh geometry of the airway from nares to larynx from each CT scan. The

mesh volumes will be evaluated by CFD with simulated airflow to quantify airway

resistance. The dog will then undergo alarplasty and partial staphylectomy. Three weeks

after surgery the client survey and airway CT scan will be repeated. Each dog’s airway

resistance will be compared pre- and post-surgery; client survey scores will be correlated to airway resistance by non-parametric tests. We anticipate finding a significant

reduction in airway resistance post-surgery in these dogs and that airway resistance significantly correlates to client perceptions of respiratory signs as assessed by the airway survey.

Figure 16. Asymmetry of pressure between the nasal passages. Asymmetry of pressure between the two nasal passages was identified in one dog. Left: Rostrocaudal oriented model split into 20 evenly distributed slices. The right nasal cavity has a yellow color depicting a higher pressure relative to the blue color coded left nasal cavity. Right: Lateral orientation; complete, smoothed airway 3D model demonstrating the differing pressures within the rostral one-third of the airway.

CHAPTER 6: MULTI-DETECTOR CARDIAC COMPUTED TOMOGRAPHY

6.1 Electrocardiographic Gated Multi-Detector Computed Tomography

Structural and functional analysis of the left ventricle and atrium are essential to assessing left-sided heart disease. Visualization of cardiac structures is accomplished through different modalities, making diagnostic imaging a pivotal component to the cardiac examination in veterinary medicine. Transthoracic echocardiography (TTE) is the modality used by cardiologists to evaluate chamber size and assess function in cardiac disease in small animal medicine.117, 118, 119 Thoracic radiography is a readily available

diagnostic to small animal practitioners; however, the chambers are indirectly assessed by

changes in the cardiac silhouette. Major shortcomings of radiography of the cardiac

silhouette are a low sensitivity for mild changes the cardiac silhouette cannot highlight

individual structures due to border effacement, and radiography is a snap shot that does

not provide a functional assessment.120, 121 Quantitative analysis, including stroke volume

(SV) and cardiac output, as well as individual chambers size during diastole and systole are an objective measure to characterize pathology. Transthoracic echocardiography is

required to discern between myocardium and luminal chamber, which is not possible by

screening three view thoracic radiographs. Qualitative observations of function are used to compliment auscultation and physical exam to diagnose cardiac disease.122, 123

Classifying the degree of pathology helps to guide medical management.121, 124

Diagnostic tests must be accurate, reliable, and repeatable in order to prescribe an

appropriate care plan and monitor response to treatment.

Thoracic radiography and two-dimensional (2D) TTE are first tier diagnostics for

the veterinary cardiac work-up. Radiography and TTE provide complimentary

information regarding size, shape, and function. Transthoracic echocardiography uses a

combination of utilities (Brightness-mode, Motion-mode, color and spectral Doppler modes) to assess the individual chambers and valvular function within the heart.

Measurements obtained with 2-dimensional imaging are used to estimate a 3-dimensional

(3D) chamber volume and functional values such as ejection fraction (EF) and SV by pre- determined equations. The 2D nature of the TTE relies heavily on geometric assumptions to calculate structural and functional data making it vulnerable to extrapolation errors.125,

126 An additional benefit of TTE is the ability to evaluate myocardial thickness. Cardiac

ultrasound remains user dependent requiring extensive training to develop proficiency

with a limited examination to the heart and outflow tracts. Access to TTE is variably based on the availability of trained specialists.

The pitfalls of thoracic radiography and 2D TTE are particularly troublesome with the English bulldog. The English bulldog as a breed has a number of unique issues that arise when attempting to apply the standard thoracic radiographic interpretation paradigms. The bulldog thorax is compressed dorsoventrally causing the heart to lay differently compared to other breeds. Furthermore, there are varying degrees of vertebral conformation anomalies (hemivertebrae) that confound cardiopulmonary radiographic interpretation. The vertebral heart score is dependent on positioning of the cardiac

silhouette within the thorax while the dog is in lateral recumbency, as well as a ratio of

full formed vertebral bodies. Shortened vertebral bodies due to malformation and

malpositioning of the cardiac silhouette invalidates the vertebral heart score ratio.127 The

narrow intercostal spaces limit the acoustic window making accurate echocardiographic

measurements difficult.128 Chamber size and functional parameters are based on

geometric assumptions for 2D TTE and inaccurate measurements may be amplified.123,

129, 130

Cross-sectional imaging overcomes some of the inherent deficiencies of thoracic

radiography and 2D TTE. Cardiac magnetic resonance imaging (CMR) is considered the

gold standard modality for assessing the chamber size and ventricular function in human

medicine for some of these similar issues.131, 132 CMR has the best temporal resolution,

but lags behind MD-CT spatial resolution for contemporary imaging techniques.133 The

raw data is then reconstructed into a 3D model for volumetric analysis throughout the

cardiac cycle. The major limiting factor for utilization of CMR in veterinary medicine is access to a high field magnet with ECG gating technology. Also, the acquisition times are relatively long compared to an echocardiogram, the utility is typically cost prohibitive, and general anesthesia is required in order to get diagnostic images, which may in turn influence functional measures. Magnetic resonance imaging for cardiac assessment is in its infancy in veterinary medicine, and therefore not yet ready to take the place of TTE.

Transthoracic echocardiography remains the modality with highest accessibility, repeatability, and confidence to direct management plans.

Computed tomography has been correlated to CMR in both human medicine and more recently in veterinary medicine as an effort to maximize imaging efficiency without sacrificing accuracy.134,135 Human medicine and veterinary medicine have both shown

that MD-CT with over 64 detectors has a high correlation with CMR for volumetric measurements like left ventricular end-diastolic volume (LV EDV), LV end-systolic volume (LV ESV), and left atrial size, as well as, functional analyses like LV EF and

SV.133, 136, 137, 138 The accuracy of measurements between these two modalities supports

MD-CT as an alternative gold standard for evaluating cardiac structure and function.139

The temporal advantages of MD-CT makes cross-sectional imaging using MD-CT in the

English bulldog a promising diagnostic tool to acquire an accurate, repeatable, efficient assessment of cardiac structure and function.

The technologic development of dual source scanners for MD-CT has improved the temporal resolution to as low as 66 milliseconds; comparatively MRI is around 25 milliseconds and TTE is about 20 – 30 milliseconds.130, 133, 140, 141, 142 Dual source

scanners use two X-ray tubes to acquire partial data that is compiled and reconstructed

into one complete set of data throughout the cardiac cycle.19(Figure 17) Heart rate is

among the major influences to drive the necessity of better temporal resolution; a higher

heart rate may cause motion artifact if the CT scanner acquisition speed is too slow.

Motion artifact can then make functional and quantitative analyses inaccurate. Using a

single X-ray tube 64 multi-detector helical scanner with a 330 ms rotation time provides

diagnostic quality resolution with heart rates up to 140 beats per minute.143 In order for a

single source scanner to accomplish the temporal resolution of 100 ms, the gantry would

require a rotational speed of 0.2 ms to achieve a similar resolution. However, the

rotational speed would generate over 75 Gs of force, which is beyond mechanical

feasibility.20 In dogs,, heart rates are often higher than humans requiring a CT scanner capable of better temporal resolution or the use of pharmacologic slowing of the heart

rate. Dual-source scanners overcome time obstacles by only needing to cover a fraction

of a complete rotation, therefore improving the temporal resolution to 50 – 100 ms.

Raw data from CT can be constructed into 3D using a variety of filters and

strategies to maximize spatial resolution.135 The use of MD-CT may be especially beneficial in veterinary medicine to minimize the necessity of general anesthesia to obtain diagnostic quality images. The improved speed of acquisition has prompted our research to conduct imaging examinations utilizing sedation alone instead of general anesthesia.144

Transthoracic echocardiography remains the keystone utility in the clinical setting

to assess cardiac function despite the anatomic limitations due to the shape of the English

bulldog. Multiple formulae have been developed in humans and translated into veterinary

medicine to calculate volume from 2D measurements; these include Simpson’s method of

discs, Teichholz method, and bullet method.126, 145, 146 These geometric assumptions have

not been validated in dogs, particularly in dogs with abnormal body habitus such as the

English bulldog. We propose that cross-sectional imaging like MD-CT is a more

appropriate modality to overcome the obstacles in breeds like the English bulldog. MD-

CT has shown to be highly correlated with the gold standard of CMR in humans.133

Because TTE is the mainstay for diagnostics, we aim to investigate the correlation of left-

sided chamber size and function between 2D TTE and 128-detector MD-CT in a

population of healthy adult English bulldogs. This study simulates a clinical hospital

setting; non-sedated echocardiographic exams were correlated to sedated MD-CT. To our

knowledge, this also presents a novel approach to computed tomographic cardiac

angiography of a brachycephalic breed without the use of general anesthesia or

intubation.

A high correlation comparing chamber measurements was found between 2D

TTE to MD-CT in human studies studies.130, 137 Studies in healthy dogs have mirrored the

findings showing a positive correlation between 2D TTE with MD-CT with both

modalities performed under general anesthesia. However, despite the strong overall

correlation between the modalities, there was some variation between the studies.144, 147,

148 A recent study comparing structural measurements between TTE and 4-slice non-

ECG-gated contrast enhanced MD-CT showed a poor correlation between the modalities.149 The American Society of Echocardiography recommends Simpson’s

method of discs for 2D technique for echocardiographic quantification, though this has

not been validated in bulldogs.123, 145

The conformation of the English bulldog is an obstacle to ideal imaging using

TTE and thoracic radiography. Hemi-vertebrae result in narrowing intercostal spaces

with little flexibility for angling the sound waves. The dorsoventral compression of the

body wall causes intrathoracic structures like the heart to be positioned differently

compared to other breeds. Multi-detector computed tomographic cross-sectional imaging

overcomes these obstacles. The additive contribution of a dual source scanner improves

the temporal and spatial resolution for cardiac imaging, accomplishing cardiac functional

and structural assessment.

6.2 Specific Aims/Hypotheses

The initial focus of the study was to evaluate the feasibility of performing diagnostic

quality cardiac angiographic examinations in sedated English bulldogs. Previous work

has described methodology of cardiac angiography in dogs under general anesthesia.135,

136, 150, 151, 152 Intravascular contrast studies like cardiac angiography are routinely

performed without sedation or anesthesia in humans with little adverse effects, 2-4% of

studies using nonionic monomer contrast medium report mild skin reaction like

erythema.153 A recent study evaluating intravenous Iohexol administration in anesthetized

dogs reported a severe reaction in only 0.8% (3/356) dogs; severe was described as

requiring intervention from an anesthetist.154 English bulldogs were chosen as the breed of interest due to their high prevalence of cardiac disease, most notably pulmonic stenosis and coronary anomalies. English bulldogs were also chosen as a proof of principle to demonstrate that using a 128-detector dual source computed tomographic (DSCT) unit, high quality intravascular contrast studies could be achieved safely and effectively. It was hypothesized that diagnostic quality cardiac angiographic studies could be accomplished using a 128-detector dual source MD-CT machine in sedated, non- intubated English bulldogs.

The left ventricular (LV) and left atrial (LA) volume and function was evaluated throughout the cardiac cycle in sedated English Bulldogs. The left ventricular and left atrial measurements by MD-CT were then compared to transthoracic echocardiographic

(TTE) measurements. Methodology to evaluate the levocardia function was set up to mimic a clinical setting. The transthoracic echocardiographic values were evaluated in non-sedated patients, while CT values were sedated with dexmedetomidine (alpha-2

agonist) and butorphanol (mixed agonist and antagonist mu-opioid and agonist kappa-

opioid). Therefore, an additional aim of this study was to compare the LV and LA

volumes and function using non-sedated transthoracic TTE and sedated MD-CT. It was

hypothesized that the sedated MD-CT and unsedated TTE would not yield equivalent data, but that there would be a good overall correlation between the modalities, with end- systolic volume, and EF reduced on MD-CT due to the effects of sedation.

Also, it was hypothesized that the SV and cardiac output would be decreased for MD-

CT compared to TTE due to the effects of sedation.

Another objective of this study was to compare linear left atrial and left ventricular measurements by TTE with MD-CT in English bulldogs. Linear dimensions of cardiac structures during end systole and end diastole served as the basis for comparison. Inter- and intra-observer agreements were tested for both MD-CT and TTE. We hypothesized that there would be good agreement for intra-observer and inter-observer values using

MD-CT and TTE.

Figure 17. Dual source multi-detector computed tomography schematic. Schematic of dual source geometry with two tubes and detectors within gantry. Tubes are offset by 90 degrees. Adapted from Petersilka M, Bruder H, Krauss B, Stierstorfer K, Flohr TG. Technical principles of dual source CT. Eur J Radiol 2008. 68:362–368.

CHAPTER 7: MATERIALS AND METHODS - CARDIAC

7.1 Case Selection

Eleven privately owned English bulldogs were recruited for this study from clients of The Ohio State University Veterinary Medicine Center. English bulldogs were recruited as a part of a separate study on cardiac coronary artery anatomy. Medical history for each patient was obtained. The dogs underwent routine physical examination, cardiovascular examination, and a thorough screening echocardiogram. Dogs were excluded from the study if they could not be sedated for CT study. Informed client consent was obtained for all dogs and the study was approved by the Institution Animal

Care and Use Committee as well as the hospital Clinical Research and Teaching

Advising Committee.

7.2 Transthoracic Echocardiography

All echocardiographic studies were performed by a boarded certified veterinary cardiologist (BAS) using a GE Vivid 7 or Vivid 9 consider echocardiographic system with transducer selection (4, 7, or 10 MHz nominal frequency) matched to the size of the dog and preset for optimal imaging. Echocardiographic recordings were made with a simultaneous ECG, and all raw data were captured digitally for off-line analysis at a digital workstation. Standard imaging planes were utilized with the dogs manually restrained in right and left lateral recumbency without the use of sedation.

7.3 ECG-Gated Computed Tomography Angiography

The dogs were positioned in sternal recumbency with the neck extended and the forelimbs slightly abducted with table straps to help secure the dog in place. A dual source 128-MD-CT unit (Somatom Definition Flash, Siemens Healthcare) equipped for cardiac gating with temporal resolution of 75 ms and maximum scanning speed of 458 mm/s was used to perform the studies. The gantry angle was set to 0 degrees.

Electrocardiogram pads were adhered to the metacarpal/metatarsal pad of each limb and a standard bipolar ECG was acquired. Lead II was used for ECG-gating. Retrospective cardiac gating was recorded at 5% increments with the 0% increment set to the initial downslope of the R wave (Figure 18).

The topograms were acquired in laterolateral and dorsoventral views to plan the slice series. Scan parameters were carried out with a fluctuating filament current that had a maximum milliamperage of 495 mA and fluctuating tube current of 100 – 120 kVp.

Scans were performed with a single energy setting. The region of interest was scouted to include rostral to the nasal planum through the caudal aspect of the diaphragm. The gated region of interest included the entire heart base and aortic arch extending caudal through the apex of the heart. The CT dataset was reformatted with soft tissue and bone algorithms with appropriate window level and window width Hounsfield units to optimize conspicuity of contrast-enhanced cardiac chambers. The slice thickness was acquired at a maximum of 1 mm. The spiral pitch varied from 0.17 to 0.65 based on the electrocardiogram.

Cephalic venous catheter served as vascular access for the angiographic study.

® Iohexol (Omnipaque 350 ; GE Healthcare) (350 mgI/mL) was administered to each dog

using a power injector at a dose of 1.2 to 2.0 mL/kg at a rate of 4 to 5 mL/sec. A 0.9%

NaCl saline flush at a dose of 0.8 to 1.8 mL/kg at a rate of 4 to 5 mL/sec was delivered via the power injector immediately following contrast administration. Bolus-triggering technique was used with the detector set at the aortic root and a threshold of 100 HU triggered the initiation of the scan. Retrospective gating software reformatted the CT data in 20 increments of 5% through the cardiac cycle. The CT dataset was reformatted into dorsal, transverse, and sagittal planes with the ability to manipulate multiplanar reformats. The datasets were saved as DICOM files and studies were stored on the picture archiving and communication system (PACS).

7.4 Volumetric Analysis

Computed tomography studies were reviewed using TeraRecon iNuition (Version

4.4.12, TeraRecon, Foster City, CA). Retrospective gating was divided into 20 5% increments through the cardiac cycle (0% - 95%). Cropping and cutting tools were used to isolate the cardiac structures from the surrounding ribs and vertebral bodies. Semi- automatic segmentation using a threshold minimum of 300 HU and maximum of 3070

HU was used to generate an overlay of the intravascular contrast medium. Region of interest (ROI) and free region of interest (FreeROI) tools were used to outline the left atrium and left ventricle. The left atrium was isolated to include the chamber from the pulmonary veins to the mitral annulus. The left ventricle was isolated to include the chamber from the mitral annulus to the aortic valve. The mask overlay was assessed throughout each 5% increment of the cardiac cycle for each dog to best represent luminal filling of contrast medium from endocardial borders. If the overlay underestimated or overestimated the chamber size, the dilation and erosion tools, respectively, were used to

better fit the selected mask area. Total volume analysis (TVA) of the left atrium and left

ventricle was automatically calculated based on the threshold values using TeraRecon

software. Stroke volumes and EFs were automatically calculated using the volumes

determined in end diastolic and end systolic phases. Stroke volume was calculated as the

end diastolic volume minus the end systolic volume. Ejection fraction was calculated as

SV divided by end diastolic volume multiplied by 100%.

7.5 Linear Measurements………………...………………………………………………

Linear measurements of left ventricular and left atrial dimensions during the end

systolic and end diastolic phases were compared between MD-CT and TTE. DICOM

files of each dog were imported into OsiriX DICOM viewer (OsiriX 5.8.5 32-bit,

http://www.OsiriX-viewer.com/index.html). 3D Multi-planar reformatting (MPR) was

used with the MD-CT studies to form long axis and short axis imaging planes that

compared to the echocardiographic images. The MPR images were generated for the end

systolic volume (ESV) and end diastolic volume (EDV) phases as determined by cardiac-

gating analysis. The MD-CT end-diastolic measurements were acquired at the 90%

increment, which corresponded to the phase just prior to the onset of the R wave. The

MD-CT end-systolic measurements were done at the phase determined to have the

smallest chamber volume (Table 3).

Long axis measurements of the left ventricle included interventricular septal

thickness, left ventricular free wall thickness, left ventricular lumen diameter at the

chordal height, left ventricular lumen diameter at the mid-level of the ventricle, left ventricular lumen apicobasilar length, diameter of the mitral annulus, and diameter of the

aortic valve annulus. Short axis measurements of the left ventricle include

interventricular septal wall thickness, left ventricular lumen diameter, left ventricular free wall thickness, and the diameter of the pulmonary valve annulus. The dimensions were measured during the end systolic phase and end diastolic phase with the exception of the pulmonary valve diameter, which was measured at end systolic phase only. Left atrial dimensions included the height and width of the chamber on long axis view during both the end systolic phase and end diastolic phase.

The MD-CT long axis plane of the left ventricle was made to maximize the length of the left ventricle (Figure 19). The mitral annulus diameter was measured from the base of the anterior leaflet to the posterior leaflet (Figure 20). The height and width of the left atrial lumen were measured from endocardial surface to endocardial surface at the maximum distance (Figure 21). The left atrial width was measured to exclude the inflow of the pulmonary veins. The left ventricular apicobasilar length was measured from the line created from the mitral valve annulus to the apex of the left ventricular endocardial surface (Figure 22). The left ventricular length was then divided in half; a perpendicular line from the endocardial surface of the left ventricular free wall and the endocardial surface of the interventricular septum was designated as the mid-level ventricular lumen diameter. A perpendicular line from the endocardial surface of the left ventricular free wall to the endocardial surface of the interventricular septum at thirty percent of the left ventricular length on the side closer to the mitral valve annulus was labeled the left ventricular chordal luminal diameter (Figure 23). The thicknesses of the left ventricular free wall and interventricular septum were measured from leading edge to leading edge at the mid-level luminal diameter (Figure 24). Figure 25 is a labeled long axis image with the collection of the left atrial and left ventricular measurements (Figure 25).

The short axis MD-CT plane was made perpendicular to the long axis of the left

ventricle. The left ventricular short axis measurements of the interventricular septum

thickness and free wall thickness were made leading edge to leading edge at the level of

the papillary muscles. The short axis left ventricular luminal diameter was made from

endocardial surface to endocardial surface, intersecting the left ventricular free wall

between the papillary muscles (Figure 26). A cross-section MPR image of the right ventricular outflow tract was generated to measure the pulmonary valve (Figure 27). A

cross-section of the aortic valve was generated to measure the aortic valve from the luminal edge of the unification of the non-coronary and left leaflets to the luminal edge of

the right leaflet (Figure 28). A long axis image of the left ventricular outflow tract during

the end diastolic phase was formed and the aortic valve was measured from the base of

the opened leaflets (Figure 29). Abbreviations for all measurements and phase respective

dimensions are included within Table 4.

7.6 Statistical Methods

Statistical analysis was performed by two of the authors (E.T.H. and B.A.S.) using commercial software (SPSS Software, Version 22.0.0, IBM Corp, Armony, NY).

Descriptive statistics were calculated by operator and examined for normality using inspection of scatterplots and the Kolmogorov-Smirnov test. The distribution of the

overall data set was non-normal. Each group of linear measurements was tested for normality using Shapiro-Wilk test. Groups that passed the normality test were compared between modalities using Student’s t-test. If data were non-parametric, groups were compared by Wilcoxon signed-ranked test (Table 5 & Table 6).

Coefficient of variation was calculated for interobserver repeatability and intra- observer repeatability. The intra-observer repeatability was performed by a third-year radiology resident (E.T.H.) for both MD-CT cardiac angiography and TTE. Each measurement was repeated a total of three times at two different rounds of measurements.

Interobserver repeatability was assessed by comparing TTE measurements between a third year radiology resident (E.T.H.) and a Diplomat of the American College of Internal

Medicine (Cardiology) (B.A.S.). Interobserver repeatability was assessed by comparing

MD-CT measurements between a third year radiology resident (E.T.H.) and a Diplomat of the American College of Radiology (A.H.). Information-based measure of disagreement (IBMD) was calculated for each interobserver pairing with 0 meaning no disagreement and 1 meaning complete agreement.155 The intraclass correlation coefficients (ICC) were calculated for interobserver pairings and graded into three categories: high (>0.90), moderate (0.75 – 0.90), and poor (< 0.75).156, 157, 158

Figure 18. Retrospective ECG gating. 0% phase starts at the peak of the R wave.

Figure 19. CT and TTE long axis view of the left ventricle and left atrium. Comparison of the long axis view of the left ventricle and left atrium using CT and TTE. Left: Computed tomography. Right: Transthoracic echocardiography.

Figure 20. CT mitral valve annulus measurement. Mitral valve annulus measurement, taken at the hinge point of the leaflets. The left atrium is above the green line and the left ventricle is below the green line.

Figure 21. CT Left atrial chamber measurements. CT left atrial chamber measurements. A: Left atrial width measurement was the widest aspect of the chamber excluding the inflow of the pulmonary veins - measuresments paralleled the mitral valve annulus. B: Left atrial height measurement was taken as the longest aspect of the left atrium chamber perpendicular to the mitral valve annulus. Measurements were made endocardial surface to endocardial surface. Black arrow: Mitral valve annulus.

Figure 22. CT left venticular length measurement. A: Left ventricular length was made from a line perpendicular to the mitral valve annulus to the longest luminal length of the cardiac apex. Black arrow: Mitral valve annulus.

Figure 23. CT left ventricular lengths for mid-level luminal diameter and chordal level luminal diameter. Lumen diameters were made parallel to the mitral valve and perpendicular to the mid-level and chordal level lines. A: Chordal level length is 30% of the left ventricular length measurement. B: Mid-level length is 50% of the left ventricular length measurement. Black arrow: Left ventricular length. White arrow: Mitral valve annulus.

Figure 24. CT and TTE interventricular septum and free wall measurements. Long axis CT and TTE of the left ventricle and atrium. Left: CT long axis. A: Mid-level left ventricular luminal diameter. B: Chordal level left ventricular luminal diameter. C: Interventricular septum thickness; measured as the same level at LV chordal level. D: Free wall of left ventricle thickness; measured at the same level as LV chordal level. Right: TTE long axis. E: Chordal level left ventricular luminal diameter. F: Interventricular septum thickness. G: Free wall of left ventricle thickness. White arrows: Mitral valve annulus.

Figure 25. Labeled long axis CT of the left ventricle and left atrium measurements. Long axis CT image of the left ventricle and left atrium with labeled measurements. A: Mitral valve annulus. B: Left atrial width. C: Left atrial height. D: Left ventricular length. E: Left ventricular mid-level lumen. F: Left ventricular chordal level lumen. G: Interventricular septum thickness. I: Left ventricular free wall thickness. White arrows points to contrast medium in right ventricle.

Figure 26. Short axis of left ventricle at the level of the papillary muscles. Left: Computed tomography. A: Free wall of the left ventricle. B: Left ventricle luminal diameter at the level of the papillary muscles. C: Interventricular septum. Right: Transthoracic echocardiography. D: Free wall of the left ventricle. E: Left ventricle luminal diameter at the level of the papillary muscles. F: Interventricular septum.

Figure 27. CT cross-section of the pulmonary valve. Computed tomography cross- section of heart base. The aortic root is seen at center. The green line shows the diameter of the pulmonary valve annulus.

Figure 28. CT and TTE cross-section of the aortic valve. Cross-section of the aortic valve. Left: Computed tomography. Green line from the edge of the right leaflet through the unification left leaflet and noncoronary leaflet. Right: Transthoracic echocardiography. Red line from the edge of the right leaflet through the unification left leaflet and noncoronary leaflet.

Figure 29. CT of left ventricular outflow tract and aortic valve. Computed tomography image through the left ventricular outflow tract. The aortic valve is measured (Green line) at the hinge point of the leaflets when the aortic valve is open.

CHAPTER 8: CARDIAC RESULTS

8.1 Subject Demographics

Eleven English bulldogs were enrolled into the study. The average age of the bulldogs was 33.75 months with a standard deviation of 28.28 months. The maximum age was 91.97 months and the minimum age was 5.6 months (Table 7). The group of

English bulldogs included three castrated males, two intact males, two spayed females, and four intact females. Nine of the English bulldogs were structurally normal on TTE and CT. One bulldog had mitral valve dysplasia characterized as mild with subjectively normal chamber dimensions. One bulldog had a small ventricular septal defect with aortic insufficiency characterized as mild with subjectively normal chamber dimensions.

8.2 Descriptive Statistics and Comparisons

Eight of the 25 measurements of linear cardiac dimensions were significantly different between TTE and MD-CTA (all P < 0.032) (Table 8). Those parameters that were different between modalities included: LV ES short axis free wall thickness, LV ES mid-level lumen, mitral valve annulus, aortic valve annulus, LV ES short axis lumen, LV

ED short axis free wall thickness, LV ED aortic valve cross-section, and LA ED height.

No significant differences between 17/25 measurements made by MD-CTA and

TTE were found, including LV ES interventricular septum thickness (IVS), LV ES pre- chordal lumen, LV ES short axis IVS thickness, LV ES short axis FW thickness, LV ES ventricular length, LV ES pulmonary valve annulus, LV ED IVS thickness, LV ED FW

thickness, LV ED pre-chordal lumen, LV ED short axis lumen, LV ED mitral valve

annulus, LV ED ventricular length, LV ED mid-level lumen, LV ED short axis IVS, LA

ES width, LA ES height, and LA ED width (Table 9 – 22).

The mean ESV and EDV determined by TTE using Simpson’s Method was 10.45

mL (+/- 5.97 mL) and 37.13 mL (+/- 9.38 mL). Mean TTE values for SV and EF were

19.99 mL (+/- 4.77 mL) and 69.60% (+/- 9.22%), respectively (Table 23). The mean ESV

and EDV determined by MD-CT volumetric analysis using TeraRecon iNtuition software

was 25.73 mL (+/- 9.56 mL) and 43.54 mL (+/- 13.02 mL). Mean MD-CT values for SV and EF were 17.80 mL (+/- 5.33 mL) and 42.75% (+/- 11.28%), respectively (Table 24).

A significant difference was identified between MD-CT and TTE for measurements of

ESV, SV, and EF (p <0.02). No significant difference was found between MD-CT and

TTE for EDV (p = 0.188) (Table 25).

8.3 Inter-observer and Intra-observer Results

The total interobserver coefficient of variation (CV) averaged 6.65% for TTE and

8.75% MD-CT. Intra-observer agreement was strong with a total CV of 5.34% for TTE and 2.50% for MD-CT (Table 26). The intra-observer agreement CV for LV ES, LV ED,

LA ES, and LA ED were each lower for MD-CT than the intra-observer agreement CV by TTE. Intra-observer CV for each phase was lower than the corresponding inter- observer CV on both modalities. The inter-observer agreement CVs using TTE were lower than the MD-CT on all phases. The lowest coefficient of variation was the left ventricular end diastolic phase using MD-CT. The highest coefficient of variation was for the left atrial end systolic measurements.

Transthoracic echocardiography had an over lower inter-observer measure of disagreement compared to MD-CT. The inter-observer measurements using TTE showed a lower disagreement using the IBMD; TTE inter-observer was 0.11, while MD-CT was

0.15. The IBMD was lower for TTE for the LV ED, LA ES, and LA ED phases. The

IBMD for LV ES was comparable for TTE and MD-CT, calculated to be 0.12 (Table 27

& 28).

Multi-detector computed tomography and TTE have a comparable measure of reliability according the intraclass correlation coefficient (ICC). The total ICC for MD-

CT inter-observer measures was 0.978, while TTE showed an inter-observer measure of

0.971 with a large overlap of the confidence intervals 0.972 – 0.983 and 0.961 – 0.979, respectively (Table 27 & 28). For both TTE and MD-CT, the inter-observer measurements of the left ventricular ES and ED had a higher ICC than the LA ES and ED measurements.

CHAPTER 9: DISCUSSION - CARDIAC

9.1 Discussion

High quality cardiac angiography diagnostic studies were acquired using MD-CT without the use of general anesthesia. A combination of an alpha-2 agonist, a mixed mu-

/kappa-opioid, and a parasympatholytic agent provided sufficient sedation and a regular cardiac rhythm to perform cardiac angiography in this sample of English bulldogs using a dual source 128-MD-CT. Retrospective cardiac gating enabled volumetric analysis throughout the cardiac cycle possible in increments of 5%. Values for LV and LA ESV,

EDV, SV, and EF were determined in a small sample of sedated English bulldogs were

achieved using MD-CT data (Table 24). Additionally, the left ventricular and left atrial

volumes throughout the cardiac cycle were achieved and a tracing through the cycle was

possible for both left-sided chambers (Figure 30 - 32). The sample of English bulldogs in

this study is too small to use the data collected as a representation of the population.

Multi-detector computed tomography and TTE are not interchangeable modalities

in the clinical setting. The data presented in this study were collected from unsedated

TTE exams and sedated MD-CT studies. The comparison between the two modalities is

not direct, but rather represents what would be expected in the clinical setting. TTE is

routinely performed prior to any sedation so as to not influence cardiac function.

Unfortunately, unsedated exams are not possible for MD-CT in dogs. Significant

differences were found between cardiac dimensions as measured by TTE and MD-CTA,

indicating the two methodologies are not equivalent (Table 8 & Table 25). Notably, LV

EDV was not different between modalities, though SV, EF, and ESV showed significantly different values on TTE as compared to MD-CT. These latter 3 variables

(SV, EF, ESV) are all directly impacted by LV systolic function, which was expected to be reduced by the sedative required for MD-CT. The distribution of data points in the

Bland-Altman plots was non-uniform for all phases (Figure 33 - 36).

Sedated MD-CTA yielded high-quality imaging studies with strong intra-observer and inter-observer measurements for agreement and reliability in English bulldogs. MD-

CT had a strong intra-observer measure of agreement with a better measurement than

TTE. The intra-observer CV was good. However, inter-observer measurements for agreement were better for TTE compared to MD-CT. Preparation was made to prior to measurements to standardize the routine for measuring dimensions on both MD-CT and

TTE. However, experience for measuring structures on TTE was greater than that of MD-

CT. ECG-gated MD-CT cardiac angiography was a new modality for both observers.

Also, the dimensions picked for measurement were based on TTE, making them more routine on that modality. MD-CT comparison also required the two observers to generate the MPR plane that mimicked the long axis and short axis images prior to measurement.

The extra step introduces an additional source of error. Measuring TTE dimensions did require each observer to choose the end systolic and end diastolic frames of the cine loop; however, potential variability from this step was minimized as an ECG accompanied the echocardiographic studies.

9.2 Conclusion

Multi-detector computed tomography cardiac angiography using a dual source

128-MD-CT is feasible in sedated English bulldogs. High quality examinations are possible with the use of volumetric analysis. MD-CT in a sedated dog is not equivalent to unsedated TTE with significant differences between the two modalities. Further work must be done to compare the two modalities. Also, sample sizes must increase in order to generate standard reference intervals for assessing cardiac form and function in dogs.

MD-CT with ECG-gating provides a cross-sectional imaging alternative to evaluate cardiac morphology in a breed that is challenging to image by TTE.

9.3 Limitations

A limitation of the study is the small number of English bulldogs enrolled. Eleven individual dogs are insufficient to make a conclusion of the volumetric and functional analysis as a representation of the general population for the breed. Also, two of the dogs included had cardiac pathology (mitral valve dysplasia and ventricular septal defect with aortic insufficiency). However, since the aims of the study were to accomplish diagnostic quality MD-CT cardiac angiography, as well as compare measurements between the modalities, the two abnormal dogs were included due to the mild classification of their pathology.

Figure 30. CT left ventricular chamber volumes through the cardiac cycle. Left ventricular chamber volumes through the cardiac cycle. Y-axis: Volume in mL. X-axis: Phase of cardiac cycle in 5% increments. 0% corresponds to the R-wave peak. Each thin line corresponds to an individual dog. Thick black line: Average of all dogs.

Figure 31. CT left atrial chamber volumes through the cardiac cycle. Left atrial chamber volumes through the cardiac cycle. Y-axis: Volume in mL. X-axis: Phase of cardiac cycle in 5% increments. 0% corresponds to the R-wave peak. Each thin line corresponds to an individual dog. Thick black line: Average of all dogs.

Figure 32. CT average left ventricular and atrial chamber volumes. Left ventricular (black line) and atrial (red line) chamber average volumes through the cardiac cycle. Y- axis: Volume in mL. X-axis: Phase of cardiac cycle in 5% increments. 0% corresponds to the R-wave peak.

LAED

Figure 33. Bland Altman plot comparing CT and TTE for LA end diastolic data. Bland Altman plot comparing left atrial end diastolic measurements on CT and TTE.

Figure 34. Bland Altman plot comparing CT and TTE for LA end systolic data. Bland Altman plot comparing left atrial end systolic measurements on CT and TTE.

Figure 35. Bland Altman plot comparing CT and TTE for LV end diastolic data. Bland Altman plot comparing left ventricular end diastolic measurements on CT and TTE.

Figure 36. Bland Altman plot comparing CT and TTE for LV end systolic data. Bland Altman plot comparing left ventricular end systolic measurements on CT and TTE.

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APPENDIX A: DESCRIPTIVE STATISTICS - AIRWAY

Table 1. Descriptive statistics for age, weight, and airway resistance. Descriptive statistics for age (months), weight (kilograms), and airway resistance (Pa/L/s) in 21 English bulldogs.

Table 2. Pearson correlation between age, weight, and airway resistance.

APPENDIX B: PHASE OF CARDIAC CYCLE & ABBREVIATION KEY

Name ED-LV ES-LV Dog 1 90% 65% Dog 3 90% 45% Dog 4 90% 40% Dog 5 90% 35% Dog 6 90% 30% Dog 7 90% 50% Dog 8 90% 25% Dog 9 90% 50% Dog 10 90% 55% Dog 11 90% 55% Dog 12 90% 35% Table 3. Computed tomography ED and ES phase for measurements. Phase used from measuring CT end diastolic measurements and end systolic measurements for each dog respectively. End diastole was standardized to prior to R-wave peak. End systole was determined by the lowest volume as determined by volumetric analysis. Dog 2 was excluded due to poor ECG-gating results causing volumetric analysis to fail.

Table 4. Key of abbreviations for measurements of CT and TTE. Abbreviation key for the cardiac measurements on CT and TTE.

APPENDIX C: DESCRIPTIVE STATISTICS & NORMALITY TEST – CARDIAC

s: alpha value Wilk test for for Wilk test - Shapiro

. ES: End systolic. ED: ED: systolic. End . ES: normal distribution. normal - ull hypothesis is accepted (normal distribution). is acceptedboxeull Red (normal hypothesis left ventricular measurements d TTE (‘_Echo’) left ventricular null hypothesis inferring null hypothesis non Wilk for test normality left ventricular measurements rejected - (‘_CT’) an

CT . Shapiro . Table 5 normality for boxes: N diastolic. End Green 0.05 and less than

Table 6. Shapiro-Wilk test for normality left atrial measurements. Shapiro-Wilk test for normality for CT (‘_CT’) and TTE (‘_Echo’) left atrial measurements. ES: End systolic. ED: End diastolic. Green boxes indicate a null hypothesis is accepted (normal distribution). Red boxes indicate an alpha value less than 0.05 and the null hypothesis is rejected inferring non-normally distributed data.

Table 7. Descriptive statistics for cardiac angiography. Descriptive statistics of age (months) for 11 English bulldogs in cardiac angiography study.

APPENDIX D: COMPARISON OF TRANSTHORACIC ECHOCARDIOGRAPHY &

MULTI-DETECTOR COMPUTED TOMOGRAPHY

Comparison of Computed Tomography to Echocardiography Measurements Accept Null Reject Null LV ES LV ES Interventricular Septum (IVS) Short Axis FW Pre-Chordal Lumen Mid-Level Lumen Short Axis IVS Mitral Valve Annulus Free Wall (FW) Aorta LV Length Pulmonary Annulus Short Axis Lumen LV ED LV ED Interventricular Septum (IVS) Free Wall (FW) Mid-Level Lumen Short Axis FW Pre-Chordal Lumen LV Length Aorta Cross-section Short Axis Lumen Short Axis IVS Mitral valve annulus LA ES LA ES LA Width LA Height LA ED LA ED LA Width LA Height Table 8. Significantly different MD-CT and TTE measurements. Comparison of measurements between MD-CT to TTE dimensional measurements. 8/25 measurements (reject null column) were significantly different between CT and TTE. LV = Left ventricle, LA = Left atrial, ES = End systolic, ED = End diastolic.

Table 9. LA ED descriptive statistics for normally distributed data. Left atrial end diastolic descriptive statistics for normally distributed dimensional measurements in millimeters.

Table 10. Left atrial end diastolic t-Test comparing means.

Table 11. LA ES descriptive statistics for normally distributed data. Left atrial end systolic descriptive statistics for normally distributed dimensional measurements in millimeters.

Table 12. Left atrial end systolic t-Test comparing means.

Table 13. LV ED descriptive statistics for normally distributed data. Left ventricular end diastolic descriptive statistics for normally distributed dimensional measurements in millimeters.

Table 14. Left ventricular end diastolic t-Test comparing means.

Table 15. LV ED descriptive statistics for non-normally distributed data. Left ventricular end diastolic descriptive statistics for non-normally distributed dimensional measurements in millimeters.

Table 16. Left ventricular end diastolic Wilcoxon-signed rank test.

Table 17. Left ventricular end diastolic Wilcoxon-signed rank test.

Table 18. LV ES descriptive statistics for normally distributed data. Left ventricular end systolic descriptive statistics for normally distributed dimensional measurements in millimeters.

Table 19. Left ventricular end systolic t-Test comparing means.

Table 20. LV ES descriptive statistics for non-normally distributed data. Left ventricular end systolic descriptive statistics for non-normally distributed dimensional measurements in millimeters.

Table 21. Left ventricular end systolic Wilcoxon-signed rank test.

Table 22. Left ventricular end systolic Wilcoxon-signed rank test.

LV Measurements TTE (Simpson's Method) Average Stan Dev Range ESV (mL) 10.45 5.97 3.14 - 26.87 EDV (mL) 37.13 9.38 19.45 - 47.87 SV (mL) 19.99 4.77 16.31 - 35.31 EF 69.60% 9.22% 40.02% - 87.77%

Table 23. Echocardiography LV volumetric and functional measurements. Left ventricular volumetric measurements and functional parameters using TTE.

LV Measurements MD-CTA Average Stan Dev Range ESV (mL) 25.73 9.56 4.68 - 36.50 EDV (mL) 43.54 13.02 14.09 - 57.91 SV (mL) 17.80 5.33 9.41 - 25.56 EF 42.75% 11.28% 27.32 - 66.78%

Table 24. Computed tomography LV volumetric and functional measurements. Left ventricular volumetric measurements and functional parameters using MD-CT.

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CT - CT and CT and - Levene’s test for equality

. es for es ESV, SV, EDV, and EF ficant difference between volumetric measures using MD CT and volum TTE - test compares the volume means for ESV, volumeEDV, the MD for between means test EF compares SV, and - test for MD - s t . Student’ . 25

TTE. Significance is considered at p < 0.05. p < is at considered signiA Significance TTE. EDV. ESV,significant No was for for TTE difference found EF. and SV, and Table Student’s and variances t of

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APPENDIX E: INTRA-OBSERVER & INTER-OBSERVER MEASUREMENTS

Table 26. Coefficient of variation of agreements. Coefficient of variation of agreement for intra-observer and inter-observer agreement for MD-CT and TTE for both left atrium (LA) and left ventricle (LV) during end diastolic (ED) and end systolic (ES), as well as total.

Table 27. Inter-observer agreements for transthoracic echocardiography. Measures of inter-observer agreement for TTE including information-based measure of disagreement (IBMD) and the intraclass correlation (ICC).

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Table 28. Inter-observer agreements for multi-detector computed tomography. Measures of inter-observer agreement for MD-CT including information-based measure of disagreement (IBMD) and the intraclass correlation (ICC).

Correlations LVESCT LVESEcho LVESCT Pearson Correlation 1 .903** Sig. (2-tailed) .000 N 121 121 LVESEcho Pearson Correlation .903** 1 Sig. (2-tailed) .000 N 121 121 **. Correlation is significant at the 0.01 level (2-tailed). Table 29. Pearson correlation of CT and TTE for LV ES. Correlation of measurements comparing CT and TTE during left ventricular end systolic phase.

Correlations LVEDCT LVEDEcho LVEDCT Pearson Correlation 1 .954** Sig. (2-tailed) .000 N 110 110 LVEDEcho Pearson Correlation .954** 1 Sig. (2-tailed) .000 N 110 110 **. Correlation is significant at the 0.01 level (2-tailed). Table 30. Pearson correlation of CT and TTE for LV ED.Correlation of measurements comparing CT and TTE during left ventricular end diastolic phase.

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Correlations LAESCT LAESEcho LAESCT Pearson Correlation 1 .839** Sig. (2-tailed) .000 N 22 22 LAESEcho Pearson Correlation .839** 1 Sig. (2-tailed) .000 N 22 22 **. Correlation is significant at the 0.01 level (2-tailed).

Table 31. Pearson correlation of CT and TTE for LA ES. Correlation of measurements comparing CT and TTE during left atrial end systolic phase.

Correlations LAEDCT LAEDEcho LAEDCT Pearson Correlation 1 .845** Sig. (2-tailed) .000 N 22 22 LAEDEcho Pearson Correlation .845** 1 Sig. (2-tailed) .000 N 22 22 **. Correlation is significant at the 0.01 level (2-tailed).

Table 32. Table 32. Pearson correlation of CT and TTE for LA ED. Correlation of measurements comparing CT and TTE during left atrial end diastolic phase.

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