Anthropometric and genetic determinants of cardiac morphology and function

Background Cardiac structure and function result from complex interactions between genetic and environmental factors. Population-based studies have relied on 2-dimensional cardiovascular magnetic resonance as the gold-standard for phenotyping. However, this technique provides limited global metrics and is insensitive to regional or asymmetric changes in left ventricular (LV) morphology. High-resolution 3-dimensional cardiac magnetic resonance (3D-CMR) with computational quantitative phenotyping, might improve on traditional CMR by enabling the creation of detailed 3D statistical models of the variation in cardiac phenotypes for use in studies of genetic and/or environmental effects on cardiac form or function. Purpose To determine whether 3D-CMR is applicable at scale, and provides methodological and statistical advantages over conventional imaging for large-scale population studies and to apply 3D-CMR to anthropometric and genetic studies of the heart. Methods 1530 volunteers (54.8% females, 74.7% Caucasian, mean age 41.3±13.0 years) without self-reported cardiovascular disease were recruited prospectively to the Digital Heart Project. Using a cardiac atlas-based software, these images were computationally processed and quantitatively analysed. Parameters such as myocardial shape, curvature, wall thickness, relative wall thickness, end-systolic wall stress, fractional wall thickening and ventricular volumes were extracted at over 46,000 points in the model. The relationships between these parameters and systolic blood pressure (SBP), fat mass, lean mass and genetic variationswere analysed using 3D regression models adjusted for body surface area, gender, race, age and multiple testing. Targeted resequencing of titin (TTN), the largest human gene and the commonest genetic cause of dilated cardiomyopathy, was performed in 928 subjects while common variants (~700.000) were genotyped in 1346 subjects. Results Automatically segmented 3D images were more accurate than 2D images at defining cardiac surfaces, resulting in fewer subjects being required to detect a statistically significant 1 mm difference in wall thickness. 3D-CMR enabled the detection of a strong and distinct regionality of the effects of SBP, body composition and genetic variation on the heart. It shows that the precursors of the hypertensive heart phenotype can be traced to healthy normotensives and that different ratios of body composition are associated with particular gender-specific patterns of cardiac remodelling. In 17 asymptomatic subjects with genetic variations associated with dilated cardiomyopathy, early stages of ventricular impairment and wall thinning were identified, which were not apparent by 2D imaging. Conclusions 3D-CMR combined with computational modelling provides high-resolution insight into the earliest stages of heart disease. These methods show promise for population-based studies of the anthropometric, environmental and genetic determinants of LV form and function in health and disease.Open Acces

Automated deep phenotyping of the cardiovascular system using magnetic resonance imaging

Across a lifetime, the cardiovascular system must adapt to a great range of demands from the body. The individual changes in the cardiovascular system that occur in response to loading conditions are influenced by genetic susceptibility, and the pattern and extent of these changes have prognostic value. Brachial blood pressure (BP) and left ventricular ejection fraction (LVEF) are important biomarkers that capture this response, and their measurements are made at high resolution. Relatively, clinical analysis is crude, and may result in lost information and the introduction of noise. Digital information storage enables efficient extraction of information from a dataset, and this strategy may provide more precise and deeper measures to breakdown current phenotypes into their component parts. The aim of this thesis was to develop automated analysis of cardiovascular magnetic resonance (CMR) imaging for more detailed phenotyping, and apply these techniques for new biological insights into the cardiovascular response to different loading conditions. I therefore tested the feasibility and clinical utility of computational approaches for image and waveform analysis, recruiting and acquiring additional patient cohorts where necessary, and then applied these approaches prospectively to participants before and after six-months of exercise training for a first-time marathon. First, a multi-centre, multi-vendor, multi-field strength, multi-disease CMR resource of 110 patients undergoing repeat imaging in a short time-frame was assembled. The resource was used to assess whether automated analysis of LV structure and function is feasible on real-world data, and if it can improve upon human precision. This showed that clinicians can be confident in detecting a 9% change in EF or a 20g change in LV mass. This will be difficult to improve by clinicians because the greatest source of human error was attributable to the observer rather than modifiable factors. Having understood these errors, a convolutional neural network was trained on separate multi-centre data for automated analysis and was successfully generalizable to the real-world CMR data. Precision was similar to human analysis, and performance was 186 times faster. This real-world benchmarking resource has been made freely available (thevolumesresource.com). Precise automated segmentations were then used as a platform to delve further into the LV phenotype. Global LVEFs measured from CMR imaging in 116 patients with severe aortic stenosis were broken down into ~10 million regional measurements of structure and function, represented by computational three-dimensional LV models for each individual. A cardiac atlas approach was used to compile, label, segment and represent these data. Models were compared with healthy matched controls, and co-registered with follow-up one year after aortic valve replacement (AVR). This showed that there is a tendency to asymmetric septal hypertrophy in all patients with severe aortic stenosis (AS), rather than a characteristic specific to predisposed patients. This response to AS was more unfavourable in males than females (associated with higher NT-proBNP, and lower blood pressure), but was more modifiable with AVR. This was not detected using conventional analysis. Because cardiac function is coupled with the vasculature, a novel integrated assessment of the cardiovascular system was developed. Wave intensity theory was used to combine central blood pressure and CMR aortic blood flow-velocity waveforms to represent the interaction of the heart with the vessels in terms of traveling energy waves. This was performed and then validated in 206 individuals (the largest cohort to date), demonstrating inefficient ventriculo-arterial coupling in female sex and healthy ageing. CMR imaging was performed in 236 individuals before training for a first-time marathon and 138 individuals were followed-up after marathon completion. After training, systolic/diastolic blood pressure reduced by 4/3mmHg, descending aortic stiffness decreased by 16%, and ventriculo-arterial coupling improved by 14%. LV mass increased slightly, with a tendency to more symmetrical hypertrophy. The reduction in aortic stiffness was equivalent to a 4-year reduction in estimated biological aortic age, and the benefit was greater in older, male, and slower individuals. In conclusion, this thesis demonstrates that automating analysis of clinical cardiovascular phenotypes is precise with significant time-saving. Complex data that is usually discarded can be used efficiently to identify new biology. Deeper phenotypes developed in this work inform risk reduction behaviour in healthy individuals, and demonstrably deliver a more sensitive marker of LV remodelling, potentially enhancing risk prediction in severe aortic stenosis

Killing many birds with two stones: hypoxia and fibrosis can generate ectopic beats in a human ventricular model

During cardiac diseases many types of anatomical and functional remodeling of cardiac tissue can occur. In this work, we focus on two conditions: hypoxia and fibrosis, which are part of complex pathological modifications that take place in many cardiac diseases (hypertrophic cardiomyopathy, hypertensive heart disease, and recurrent myocardial infarction) and respiratory diseases (obstructive pulmonary disease, obstructive sleep apnea, and cystic fibrosis). Using computational models of cardiac electrophysiology, we evaluate if the interplay between hypoxia and fibrosis is sufficient to trigger cardiac arrhythmia. We study the mechanisms behind the generation of ectopic beats, an arrhythmic trigger also known as premature ventricular contractions (PVCs), in regions with high hypoxia and fibrosis. First, we modify an electrophysiological model of myocytes of the human left ventricle to include the effects of hypoxia. Second, diffuse fibrosis is modeled by randomly replacing cardiac myocytes by non-excitable and non-conducting cells. The Monte Carlo method is used to evaluate the probability of a region to generate ectopic beats with respect to different levels of hypoxia and fibrosis. In addition, we evaluate the minimum size of three-dimensional slabs needed to sustain reentries for different stimulation protocols. The observed mechanism behind the initiation of ectopic beats is unidirectional block, giving rise to sustained micro-reentries inside the region with diffuse fibrosis and hypoxia. In summary, our results suggest that hypoxia and fibrosis are sufficient for the creation of a focal region in the heart that generates PVCs.We acknowledge support from CAPES by the grant 88881.065002/2014-01 of the Brazilian program Science without borders, and from MINECO of Spain under the Ramon y Cajal program with the grant number RYC-2012-11265Peer ReviewedPostprint (published version

Diffusion tensor magnetic resonance imaging-derived myocardial fiber disarray in hypertensive left ventricular hypertrophy: visualization, quantification and the effect on mechanical function

Left ventricular hypertrophy induced by systemic hypertension is generally regarded a morphological precursor of unfortunate cardiovascular events. Myocardial fiber disarray has been long recognized as a prevalent hallmark of this pathology. In this chapter, ex vivo diffusion tensor magnetic resonance imaging is employed to delineate the regional loss of myocardial organization that is present in the excised heart of a spontaneously hypertensive rat, as opposed to a control. Fiber tracking results are provided that illustrate in great detail the alterations in the integrity of cardiac muscle microstructure due to the disease. A quantitative analysis is also performed. Another contribution of this chapter is the model-based assessment of the role of the myofiber disarray in modulating the mechanical properties of the myocardium. The results of this study improve our understanding of the structural remodeling mechanisms that are associated with hypetensive left ventricular hypertrophy and their role

Novel cardiovascular magnetic resonance phenotyping of the myocardium

INTRODUCTION Left ventricular (LV) microstructure is unique, composed of a winding helical pattern of myocytes and rotating aggregations of myocytes called sheetlets. Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease characterised by left ventricular hypertrophy (LVH), however the link between LVH and underlying microstructural aberration is poorly understood. In vivo cardiovascular diffusion tensor imaging (cDTI) is a novel cardiovascular MRI (CMR) technique, capable of characterising LV microstructural dynamics non-invasively. In vivo cDTI may therefore improve our understanding microstructural-functional relationships in health and disease. METHODS AND RESULTS The monopolar diffusion weighted stimulated echo acquisition mode (DW-STEAM) sequence was evaluated for in vivo cDTI acquisitions at 3Tesla, in healthy volunteers (HV), patients with hypertensive LVH, and HCM patients. Results were contextualised in relation to extensively explored technical limitations. cDTI parameters demonstrated good intra-centre reproducibility in HCM, and good inter-centre reproducibility in HV. In all subjects, cDTI was able to depict the winding helical pattern of myocyte orientation known from histology, and the transmural rate of change in myocyte orientation was dependent on LV size and thickness. In HV, comparison of cDTI parameters between systole and diastole revealed an increase in transmural gradient, combined with a significant re-orientation of sheetlet angle. In contrast, in HCM, myocyte gradient increased between phases, however sheetlet angulation retained a systolic-like orientation in both phases. Combined analysis with hypertensive patients revealed a proportional decrease in sheetlet mobility with increasing LVH. CONCLUSION In vivo DW-STEAM cDTI can characterise LV microstructural dynamics non-invasively. The transmural rate of change in myocyte angulation is dependent on LV size and wall thickness, however inter phase changes in myocyte orientation are unaffected by LVH. In contrast, sheetlet dynamics demonstrate increasing dysfunction, in proportion to the degree of LVH. Resolving technical limitations is key to advancing this technique, and improving the understanding of the role of microstructural abnormalities in cardiovascular disease expression.Open Acces

Insights into cardiac remodelling by multi-modal magnetic resonance imaging and spectroscopy

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Identification of cardiac organ damage in arterial hypertension: insights by echocardiography for a comprehensive assessment

: Arterial hypertension, a widespread disease, whose prevalence increases with age, represents a major risk factor for cardiovascular events, causing damage in several organs, including the heart. In this context, echocardiography has a clear and pivotal role, being able to assess cardiac morphology and detect haemodynamic changes induced by this disease. 2018 European Society of Cardiology/European Society of Hypertension guidelines on AH identified main echo parameters such as left ventricular mass, relative wall thickness and left atrial volume, for detecting cardiac organ damage. The present review highlights the advantage of additional echocardiographic parameters such as diastolic measurement and both thoracic and abdominal aortic dimensions. An overlook on aortic valve should also be suggested to detect aortic regurgitation and stenosis, both frequent complications in hypertensive patients. In this kind of comprehensive assessment, the combination of standard and advanced echocardiography (speckle tracking echocardiography and, with a lesser extent, three-dimensional echocardiography) could be considered to improve the diagnostic accuracy, stratify prognosis and address management in arterial hypertension

On the left ventricular remodeling of patients with stenotic aortic valve: A statistical shape analysis

The left ventricle (LV) constantly changes its shape and function as a response to patho-logical conditions, and this process is known as remodeling. In the presence of aortic stenosis (AS), the degenerative process is not limited to the aortic valve but also involves the remodeling of LV. Statistical shape analysis (SSA) offers a powerful tool for the visualization and quantification of the geometrical and functional patterns of any anatomic changes. In this paper, a SSA method was devel-oped to determine shape descriptors of the LV under different degrees of AS and thus to shed light on the mechanistic link between shape and function. A total of n = 86 patients underwent computed tomography (CT) for the evaluation of valvulopathy were segmented to obtain the LV surface and then were automatically aligned to a reference template by rigid registrations and transformations. Shape modes of the anatomical LV variation induced by the degree of AS were assessed by principal component analysis (PCA). The first shape mode represented nearly 50% of the total variance of LV shape in our patient population and was mainly associated to a spherical LV geometry. At Pearson’s analysis, the first shape mode was positively correlated to both the end-diastolic volume (p < 0.01, R = 0.814) and end-systolic volume (p < 0.01, and R = 0.922), suggesting LV impairment in patients with severe AS. A predictive model built with PCA-related shape modes achieved better perfor-mance in stratifying the occurrence of adverse events with respect to a baseline model using clinical demographic data as risk predictors. This study demonstrated the potential of SSA approaches to detect the association of complex 3D shape features with functional LV parameters

MRI-Based Computational Torso/Biventricular Multiscale Models to Investigate the Impact of Anatomical Variability on the ECG QRS Complex

Aims:Patient-to-patient anatomical differences are an important source of variability in the electrocardiogram, and they may compromise the identification of pathological electrophysiological abnormalities. This study aims at quantifying the contribution of variability in ventricular and torso anatomies to differences in QRS complexes of the 12-lead ECG using computer simulations. Methods:A computational pipeline is presented that enables computer simulations using human torso/biventricular anatomically based electrophysiological models from clinically standard magnetic resonance imaging (MRI). The ventricular model includes membrane kinetics represented by the biophysically detailed O’Hara Rudy model modified for tissue heterogeneity and includes fiber orientation based on the Streeter rule. A population of 265 torso/biventricular models was generated by combining ventricular and torso anatomies obtained from clinically standard MRIs, augmented with a statistical shape model of the body. 12-lead ECGs were simulated on the 265 human torso/biventricular electrophysiology models, and QRS morphology,duration and amplitude were quantified in each ECG lead for each of the human torso-biventricular models. Results:QRS morphologies in limb leads are mainly determined by ventricular anatomy,while in the precordial leads, and especially V1 to V4, they are determined by heart position within the torso. Differences in ventricular orientation within the torso can explain morphological variability from monophasic to biphasic QRS complexes. QRS duration ismainly influenced by myocardial volume, while it is hardly affected by the torso anatomyor position. An average increase of 0.12±0.05 ms in QRS duration is obtained for eachcm3of myocardial volume across all the leads while it hardly changed due to changes in torso volume. Conclusion:Computer simulations using populations of human torso/biventricular models based on clinical MRI enable quantification of anatomical causes of variability in the QRS complex of the 12-lead ECG. The human models presented also pave theway toward their use as testbeds in silico clinical trial