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Estimation of Spatiotemporal Isotropic and Anisotropic Myocardial Stiffness Using

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Estimation of Spatiotemporal Isotropic and Anisotropic Myocardial Stiffness Using Estimation of Spatiotemporal Isotropic and Anisotropic Myocardial Stiffness using Magnetic Resonance Elastography: A Study in Heart Failure DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Ria Mazumder, M.S. Graduate Program in Electrical and Computer Engineering The Ohio State University 2016 Dissertation Committee: Dr. Bradley Dean Clymer, Advisor Dr. Arunark Kolipaka, Co-Advisor Dr. Patrick Roblin Dr. Richard D. White © Copyright by Ria Mazumder 2016 Abstract Heart failure (HF), a complex clinical syndrome that is characterized by abnormal cardiac structure and function; and has been identified as the new epidemic of the 21st century [1]. Based on the left ventricular (LV) ejection fraction (EF), HF can be classified into two broad categories: HF with reduced EF (HFrEF) and HF with preserved EF (HFpEF). Both HFrEF and HFpEF are associated with alteration in myocardial stiffness (MS), and there is an extensively rich literature to support this relation. However, t0 date, MS is not widely used in the clinics for the diagnosis of HF precisely because of the absence of a clinically efficient tool to estimate MS. Current clinical techniques used to measure MS are invasive in nature, provide global stiffness measurements and cannot assess the true intrinsic properties of the myocardium. Therefore, there is a need to non-invasively quantify MS for accurate diagnosis and prognosis of HF. In recent years, a non-invasive technique known as cardiac magnetic resonance elastography (cMRE) has been developed to estimate MS. However, most of the reported studies using cMRE have been performed on phantoms, animals and healthy volunteers and minimal literature recognizing the importance of cMRE in diagnosing disease conditions, especially with respect to HF is available. Additionally the existing cMRE techniques assume that the waves are propagating in a ii uniform, infinite, homogenous, isotropic medium. However, such assumptions are violated in the heart since it bears a complex anisotropic (orthotropic) geometry; current cMRE techniques may not provide the true mechanical properties of the myocardium and instead provide only an effective estimate of MS. The overall goal of this dissertation is to: i) implement the currently established cMRE technique in HF (both HFrEF and HFpEF) porcine models to validate MS as a diagnostic biomarker; ii) explore the scope of ex-vivo cardiac diffusion tensor imaging (DTI) in investigating myocardial architecture (required for anisotropic stiffness measurements) in a HF causing diseased model; iii) develop waveguide cMRE inversion (a tool to estimate anisotropic stiffness) and validate the algorithm using finite element (FE) simulations; and iv) implement waveguide cMRE inversion in a hypertensive heart model (that has the potential to trigger HFpEF) to demonstrate the feasibility of measuring anisotropic MS in HF causing disease conditions. From the results obtained it was observed that MS in a hypertensive heart (HFpEF causing condition) increased progressively with disease progression when compared to a normal heart; and this increase exhibited significant correlation with left ventricular pressure (increases due to hypertension) and thickness (increases secondary to hypertension). Additionally, MS demonstrated progressive focal increase in an infarcted myocardium (HFrEF causing condition) compared to non-infarcted remote myocardium with disease progression and the increase in MS exhibited significant correlation with i) iii mechanical testing-derived MS, ii) circumferential end-diastolic strain, iii) T1 values and iv) extra-cellular volume fraction. The next part of the dissertation investigates the change in cardiac geometry (essential for investigating anisotropic elastic properties) as a result of myocardial infarction (HFrEF causing condition) in formalin-fixed ex-vivo specimens using DTI. Since in-vivo DTI is very complex (due to cardiac and respiratory motion) and is still in its inception, formalin-fixed ex-vivo specimens were used for the preliminary investigation. Hence it was essential to ensure whether the alterations observed in cardiac geometry were related to pathology or if it was an effect of the fixation process. The results demonstrated that formalin-fixation did not alter the structural orientation of the fibers and that fibers in the infarcted myocardium were shorter and disarrayed. Additionally, a post processing filter was developed to reduce acquisition time in cardiac DTI, thereby assisting in faster imaging. The filter was implemented on formalin-fixed ex-vivo myocardial infarction (HFrEF causing condition) induced porcine hearts to demonstrate that the technique preserved subtle pathological alterations in myocardial structure. The last section of this dissertation validates the waveguide MRE inversion algorithm and demonstrates its feasibility in a hypertensive heart model. From the results it was observed that the inversion successfully resolved the anisotropic elastic properties of the materials in majority of the directions. The inversion failed in one shear direction because with the current actuation and geometric setting that particular mode was not being excited. Additionally, the anisotropic elastic coefficients estimated in the hypertensive iv heart model that is prone to triggering HFpEF demonstrated significant increase in one compressional direction and all three shear directions. In conclusion, this dissertation uses cMRE to demonstrate the potential of spatiotemporal isotropic and anisotropic myocardial stiffness as a diagnostic metric in heart failure porcine models. v Dedication This dissertation is dedicated to Maa. vi Acknowledgments This dissertation was nothing short of an exciting and amazing roller-coaster ride, and would be incomplete if I don’t express my gratitude to all those people who made it possible. First and foremost I want to thank my advisors Dr. Kolipaka and Dr. Clymer for, the continuous guidance, time, knowledge and experience that shaped me to become an independent researcher. Their endless discussion, scribbles on the white board, their enthusiasm despite the multiple dead ends, their motivation and their belief that “there is light at the end of the tunnel” is what kept me going till the end. I am grateful to the Department of Electrical and Computer Engineering, especially Dr. Anderson for the three years of TA support, the Department of Radiology, especially Dr. White for their funds (GRA), Hazel, Jennifer and Diane for offering me the GAA position, all of which kept me financially secured through the course of this PhD. I would like to thank Dr. White for being on my dissertation committee and for his invaluable feedback during our meetings and through manuscript preparations; Dr. Roblin for being on my candidacy and dissertation committee; Dr. Krishnamurthy for being on my qualifier and candidacy committee; Dr. Simonetti for his continuous feedback throughout the 3 years, Dr. Litsky for his help with mechanical testing and Dr. vii Potter and Dr. Raman for their insights during the weekly journal clubs. Thanks are due for Dr. Young and his student Renee, our collaborators in Auckland, for their help in generating the finite element simulations. I am grateful to Ding, Rizwan, Seongjin and Peter for their valuable perspectives whenever I was absorbed by an unsolvable mathematical/engineering abyss, Ning for her assistance with all scanner/pulse sequence related issues, Juliana for her insights as a radiologist and Molly for her help with statistics. Next, I would like to thank all the members of the lab who have contributed in some way to this dissertation, Brian for his help with imaging, Matt for his help with preparing the animals, Anirudh for his help with the initial set-up, Sam for his help with the processing and Prateek for his hands-on help. That apart, all the other past and present members of the lab, Faisal, Priyanka, Shantanu, Ben, Huiming, Kovid, Will, Chethan and Sangmin for their insights during lab meetings. Thanks are due to Debbie for being the motherly figure she is, Juliet for being an amazing friend and listener, for her help in everything, starting from course work to MATLAB errors to simple formatting, David and Sam for their occasional valuable advices. Beyond the boundaries of the lab, I would like to thank my network of friends both in US and India whose contributions may not have technical relevance but their support in the viii last couple of years was very essential to this dissertation. My neighbors for helping me sprint through the last lap of this dissertation without any injury. And last but not the least I am ever grateful to my family who forms an integral part of this dissertation. I sincerely thank my grandmother, aunts, uncles, cousins, nieces, nephews and in-laws and every other family member who believed in me. Without their constant support, encouragement and motivation that helped me stay sane; this dissertation would not have been possible. Special mention is needed for my sister Neha, for pampering me, bearing with my tantrums and keeping me company every single day. My parents (maa and baba), for believing in me and supporting me through thick and thin. It is their innumerous sacrifices and unconditional love that has given me the strength to pursue this research. Had it not been for maa’s trust in me, her passion for going beyond the ordinary and her willingness to put everything
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