Modeling the hearts of patient with hypoplastic left heart syndrome (HLHS) has remained an ongoing challenge due to its unique single ventricular morphology. Severe distortions have been observed when using generic biventricular shape templates to create three-dimensional models of HLHS anatomy, which can lead to inaccurate or unconverged numerical analysis. Thus, in this work, we developed a HLHS-specific biventricular template to capture single ventricle morphology in this cohort more accurately and robustly. We applied the HLHS-specific template to reconstruct HLHS patient-specific models from cardiac magnetic resonance images. Models created using the HLHS-specific template resulted in significantly higher accuracy compared with using the generic template to model the same cohort of patients. The models created using the cohort-specific template were also qualitatively more anatomically realistic with the size of left ventricle and relative location of the apex well captured. When patient-specific models are used for finite element analysis of biomechanics or electrophysiology, it is important to ensure that all elements in the mesh are within an acceptable level of distortion. Element distortion metrics, element edge angles and aspect ratios, confirmed that element distortion in meshes created using the HLHS-specific template is comparable with that of biventricular anatomic models previously used in finite element analysis. A semi-automated workflow, developed to use HLHS-specific template to create patient-individual models from manually segmented contours, will allow future users to create 3D models consistently and efficiently. Accurate 3D patient-specific models will serve as useful tools for statistical shape and physiological analysis to provide insights into new associations between ventricular morphology and clinical outcomes.

Cardiac resynchronization therapy (CRT) is an effective treatment for dyssynchronous heart failure. Most patients perform better during clinical tests of cardiac function and may even have their hearts reverse remodel to a more normal state. As many as 30-40% of patients, however, do not respond. A focus of current research is identifying which patients will respond to CRT, though current clinical indications for CRT are based on dyssynchrony and heart failure and not on validated predictors of CRT response. In this thesis, five patient-specific computational models based on non-invasive data were developed and compared with eight previous patient-specific models that were based on more detailed and invasive clinical information to test whether the dyssynchrony metrics from the original study were still predictive in the new group. Model properties such as the volume fraction of negative work (VFNW) and coefficient of variation of work (COVW), that had correlated with patient outcomes in the original cohort, did not correlate with reverse remodeling as measured by reduction in end-systolic volume in the new group. The sensitivity analysis showed that these quantities were sensitive to the parameters of ventricular filling mechanics that could not be included in patient-specific models based on non-invasive data. Non-invasive estimates of filling parameters are available, but their reliability has been questioned. We conclude that it is likely to be necessary to obtain invasive measurements of diastolic pressures for patient-specific models to predict CRT outcomes. However, these measurements are available by cardiac catheterization, which could be justified for CRT patients.

Marker-based motion analysis is used to evaluate human movement and identify biomechanical features related to injury risk. However, these studies require extensive expertise, are labor intensive, time consuming, and high cost, making them impractical for routine use. Open-source smartphone-based motion capture systems such as OpenCap offer scalable, low cost, and automated alternatives to conventional motion capture systems. The goal of this study was to compare OpenCap to gold standard clinical marker-based motion capture for movement screening tasks. Sixty-two retroreflective markers were placed on ten healthy collegiate female athletes who completed a set of tasks commonly used to assess movement quality. A musculoskeletal model was used to estimate hip adduction, hip flexion, hip rotation, knee flexion, and ankle flexion with both OpenCap and marker-based inverse kinematics. OpenCap was approximately 12 times faster for data collection and processing, with only 2% of trials deemed unusable. RMSEs ranged from 3.5 to 11.3° across all joints and movement tasks. Pearson’s correlation coefficients for peak joint angles for select movements ranged from moderate to very strong for hip, knee, and ankle flexion and weak to very strong for hip adduction and hip rotation. Bland Altman plots showed varying trends, bias, and limits of agreement depending on the movement and joint angle. This suggests that smartphone markerless motion capture offers a time and cost-effective alternative for capturing movement and should be further evaluated for suitability to specific clinical questions. Moreover, this platform can be further developed to increase accuracy with enhanced training of algorithms and become a standard tool for routine, high-throughput movement screening in athletes.

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease accounting for about 10% of all congenital cardiac malformations. Due to improvements in surgical technique, individuals with repaired TOF (rTOF) are surviving into adulthood but face residual pulmonary regurgitation that can lead to adverse ventricular remodeling and, ultimately, heart failure. Cardiovascular magnetic resonance (CMR) imaging is the gold standard for evaluation in patients with rTOF, but the wealth of information available in CMR images is under-utilized. We sought to use computational tools to extract atlas-based biomarkers of regional biventricular shape and mechanics from standard of care CMR images to better aid clinical management of rTOF. Specifically, the aims of this dissertation were to 1) rapidly build biventricular shape models from CMR data using machine learning; 2) formulate shape atlases from these models to identify clinically meaningful shape variation within the population; and 3) construct biventricular biomechanics models to quantify shape marker relationships with differences in myocardial mechanical properties. Herein we demonstrate a fully automated, end-to-end pipeline that can robustly create biventricular shape models for the challenging anatomies present in rTOF. We also discovered specific markers of biventricular shape that are better discriminators of clinical prognosis than standard imaging indices. These markers of biventricular shape were also partial determinants of systolic function and may also be surrogate measures for altered myocardial contractility. Overall, patients with rTOF may benefit from routine atlas-based analyses of biventricular shape and mechanics that can supplement clinical decision making and provide insight into mechanisms underlying myocardial pathophysiology.

The lesser Egyptian jerboa, Jaculus jaculus, is a small bipedal rodent with unique morphological features such as disproportionately long hindlimbs and tail, fused metatarsal bones, and the loss of medial and lateral digits. These contribute to an extraordinary repertoire of locomotion including high accelerations and decelerations resulting in unpredictable ricochetal motion. In addition to speed, jerboa are capable of producing immense ground reaction forces, allowing for propulsion of their bodies forward and upward over ten times their hip height. This unmatched performance combined with their unique morphological characteristics separates them from other small mammals and invites great interest in the study of their biomechanics and movement. Investigating muscle interactions and how they ultimately result in whole body movement using in-vivo experimentation alone is not always practical. Therefore, implementing a detailed computational model can provide insights into the musculoskeletal dynamics of the jerboa. This study describes and evaluates the development of the first three-dimensional model of jerboa hindlimb biomechanics based on detailed anatomical measurement collected from micro computed tomography (microCT) scans. Joints are generated for all bones in the hindlimb following International Society of Biomechanics (ISB) standards, with segment mass properties of each geometry measured experimentally and calculated computationally. Tendon insertions and muscle lines of action were validated using microdissections and biomechanics experiments. A sensitivity analysis was conducted to evaluate the model's robustness to changes in input parameters and to identify muscle and joint parameters that are particularly important for locomotor performance. This model combined with measured kinematics, ground reactions forces, and contractile muscle properties can be used to better understand how anatomic and physiological adaptations in the jerboa have evolved to generate the joint moment arms and control mechanisms that give rise to extreme locomotor performance and stability.

The cardiovascular system is regulated through numerous control systems, which operate on various time scales. The baroreflex operates on the scale of seconds to minutes, responding to acute changes in pressure by altering heart rate, heart contractility, and blood vessel diameter. Blood volume control operates on a time scale of minutes to hours, in which the kidneys regulate blood pressure by means of blood plasma osmolarity and volume in the circulatory system. When pressure is altered on a longer time scale of days to years, growth and remodeling occur in the heart and blood vessel walls.

In this thesis, a multi-scale model was created to improve the capacity for study of the summed or individual effects of different time scales. This time scale consideration resulted in a more physiological approach to modeling the cardiovascular system than previous models. The time scales modeled were an acute seconds-to-minutes scale, during which the baroreflex acts, and a minutes-to-hours scale during which blood volume control occurs. The model was then optimized to allow for future coupling to computationally expensive growth and remodeling models. Arterial pressure regulation was demonstrated in both normal conditions and the pathophysiological condition of aortic valve disease. The work of this thesis successfully reproduced the local effects of the disease, and demonstrated the physiologic response on multiple time scales to the reduction in arterial pressure at an aortic stenosis.

Heart failure is a major healthcare challenge, and most existing treatments mitigate its symptoms without addressing underlying mechanical dysfunction. Therefore, recent advancements aim to directly target the contractile machinery of the heart. In this work, we utilized a combination of multiscale modeling approaches spanning from the atom to whole heart to investigate the therapeutic potential of targeting proteins within the sarcomere to improve cardiac contractile function in heart failure with reduced ejection fraction. We specifically investigated 2-deoxy-ATP (dATP), a potential myosin-activating therapeutic. dATP improves cardiac function by increasing the rate of crossbridge cycling and calcium transient decay. However, the molecular mechanisms of these effects and how therapeutic responses to dATP are achieved, especially for small fractions of dATP, remain poorly understood. This is especially true in heart failure, where energy metabolism is impaired. We utilized a combination of molecular dynamics (MD), Brownian dynamics (BD), and Markov state modeling, to show that dATP increases the actomyosin association rate via stabilization of pre-powerstroke myosin. We also showed using MD and BD that dATP acts on the sarcoendoplasmic reticulum calcium-ATPase (SERCA) pump to accelerate calcium re-uptake into the sarcoplasmic reticulum during cardiac relaxation by increasing the rate of calcium association to SERCA. We then employed a spatially explicit model of the sarcomere to show that dATP increases the pool of myosin heads available for crossbridge cycling, increasing steady state force development at low dATP fractions due to mechanosensing and nearest-neighbor cooperativity. We extended our analysis to assess cardiomyocyte mechanics and excitation-contraction coupling, and found that the effects of dATP on SERCA, along with increased myosin recruitment, contributed to improved cell contraction and relaxation. These mechanisms extended to the ventricular level to improve contractility and metabolism, especially in heart failure, where our model of ventricular mechanics and circulation predicted that dATP increased ejection fraction and the energy efficiency of cardiac contraction. We finally extended our approach to demonstrate how our multiscale computational modeling approach can be utilized to provide insight into the link between genotype and phenotype in heart failure and to develop novel therapeutics.

Here we describe an original phenotypical platform to identify novel regulators of cardiac rhythm and arrhythmia-causing genes in hPSC-derived atrial-like cardiomyocytes (hPSC-ACM).The system applies well-characterized atrial subtype cardiomyocytes generated from Id1-induced cardiogenic mesoderm progenitors. The platform integrates automated high-throughput/high-content kinetic imaging system with fluorescence quantification and single-cell resolution trace analysis algorithm to retrieve physiological metrics of hPSC-ACMs biology. This generic platform enables the high-throughput phenotypical evaluation of functional genomics and small molecules on cardiac physiological parameters in both healthy or disease contexts. The system is also functionally validated with genes previously associated with atrial fibrillation (AF) and confirmed the occurrence of arrhythmia-like activity in hPSC-ACMs induced by siRNA-mediated knockdown of the genes along with AF-associated perturbagens. We then modeled and categorized different arrhythmia-subtypes arise from distinct molecular events. Overall, the hPSC-ACM differentiation protocol provides a robust resource to study atrial-specific cardiac diseases and development; the platform and single-cell analysis generate higher resolutions of information without sacrificing the throughout; and the modeling and characterization of arrhythmia-like activity shed light upon this unique approach to identify novel regulators of cardiac rhythm and arrhythmia-causing genes in an atrial-specific manner.

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Calmodulin is a ubiquitous calcium-sensing protein which activates many downstream cellular processes. Calmodulin cooperatively binds up to four calcium ions which can occupy the four EF-hand motif sites. As more calcium ions bind to calmodulin, this protein becomes more likely to change conformation from the Open/Inactive state to the Closed/Active state. Studying the kinetics of calcium binding to calmodulin can lead to further insight into how the conformational state of calmodulin depends on the local calcium concentration and the effect of cooperative binding due to calcium-induced conformational changes. This project investigates the kinetics of calcium binding to calmodulin binding sites by combining Brownian Dyanmics and Molecular Dynamics to analyze how the presence of calcium ions affects the subsequent binding of additional calcium. Obtaining the kinetic information for these interactions can inform the mechanism for cooperative calcium binding influencing the conformational state of calmodulin.