Transmural remodeling of cardiac microstructure in aged spontaneously hypertensive rats by diffusion tensor MRI

The long-standing high blood pressure (also known as hypertension) overworks the heart. Microstructural remodeling is a key factor of hypertensive heart disease progression. Diffusion tensor magnetic resonance imaging (DT-MRI) is a powerful tool for the rapid noninvasive nondestructive delineation of the cardiomyocyte organization. The spontaneously hypertensive rat (SHR) is a well-established model of genetic hypertension. The goal of this study was to employ high-resolution DT-MRI and the SHR animal model to assess the transmural layer-specific remodeling of myocardial microstructure associated with hypertension. Ex vivo experiments were performed on excised formalin-fixed hearts of aged SHRs (n = 4) and age-matched controls (n = 4). The DT-MRI-derived fractional anisotropy (FA), longitudinal diffusivity (λL), transversal diffusivity (λT), and mean diffusivity (MD) served as the readout parameters investigated at three transmural zones (i.e., endocardium, mesocardium, and epicardium). The helix angles (HAs) of the aggregated cardiomyocytes and the orientation of laminar sheetlets were also studied. Compared with controls, the SHRs exhibited decreased epicardial FA, while FA changes in the other two transmural regions were insignificant. No substantial differences were observed in the diffusivity parameters and the transmural course of HAs between the two groups. A consistent distribution pattern of laminar sheetlet orientation was not identified for either group. Our findings are in line with the known cellular microstructure from early painstaking histological studies. Biophysical explanations of the study outcomes are provided. In conclusion, our experimental findings indicate that the epicardial microstructure is more vulnerable to high blood pressure leading to more pronounced changes in this region during remodeling. DT-MRI is well-suited for elucidating these alterations. The revealed transmural nonuniformity of myocardial reorganization may shed light on the mechanisms of the microstructure-function relationship in hypertension progression. Our results provide insights into the management of patients with systemic arterial hypertension, thus prevent the progression toward heart failure. The findings of this study should be acknowledged by electromechanical models of the heart that simulate the specific cardiac pathology

Age-associated Arterial Remodelling and Cardiovascular Diseases

Arterial remodelling is a major risk factor for a variety of age-related diseases and represents a potential target for therapeutic development. During ageing, the structural, mechanical and functional changes of arteries predispose individuals to the development of diseases related to vascular abnormalities in vital organs such as the brain, heart, eye and kidney. For example, aortic stiffness increases nonlinearly with advancing age – a few percent prior to 50 years of age but over 70% after 70 years of age. The elevated stiffness in large elastic arteries leads to increased transmission of high pressure to downstream smaller blood vessels, in turn affecting the microcirculation and end-organ functions. Meanwhile, the augmented remodelling of small arteries accelerates central arterial stiffening. This chapter is to provide an overview of age-associated changes in the arterial wall and their contributions to both central and peripheral vascular abnormalities associated with ageing. Therapeutics that specially target the different aspects of arterial remodelling are expected to be more effective than the traditional medications, particularly for the treatment and management of vascular ageing-related diseases.published_or_final_versio

Mathematical modeling of collagen turnover in biological tissue

The final publication is available at Springer via http://dx.doi.org/10.1007/s00285-012-0613-yWe present a theoretical and computational model for collagen turnover in soft biological tissues. Driven by alterations in the mechanical environment, collagen fiber bundles may undergo important chronic changes, characterized primarily by alterations in collagen synthesis and degradation rates. In particular, hypertension triggers an increase in tropocollagen synthesis and a decrease in collagen degradation, which lead to the well-documented overall increase in collagen content. These changes are the result of a cascade of events, initiated mainly by the endothelial and smooth muscle cells. Here, we represent these events collectively in terms of two internal variables, the concentration of growth factor TGF-$\beta$ and tissue inhibitors of metalloproteinases TIMP. The upregulation of TGF-$\beta$ increases the collagen density. The upregulation of TIMP also increases the collagen density through decreasing matrix metalloproteinase MMP. We establish a mathematical theory for mechanically-induced collagen turnover and introduce a computational algorithm for its robust and efficient solution. We demonstrate that our model can accurately predict the experimentally observed collagen increase in response to hypertension reported in literature. Ultimately, the model can serve as a valuable tool to predict the chronic adaptation of collagen content to restore the homeostatic equilibrium state in vessels with arbitrary micro-structure and geometry.Peer ReviewedPostprint (author's final draft

Theoretical and computational study of the mechano-biology in hypertension disease

The present work deals with the development of a theoretical and computational framework of the mechano-biology happening in the arterial tissue during hypertension disease. Biological tissue adapts actively to different mechanical and chemical stimuli where the underlying mechanical properties of the tissue play an important role. The mechanical stimuli that trigger these changes is the increase of blood pressure experienced in hypertensive patients. There are also changes in the blood flow. This work is divided in four aspects of the adaptation of different components of the tissue to hypertension. Firsts, we focus on the mechanical properties of the arterial tissue and we particularly look at the behavior of a real human carotid artery. We obtain a finite element model of the carotid artery to apply all the models developed during this work. Two of them are related with the growth and remodeling of the collagen and smooth muscle cells within the arterial wall. Its thermodynamic description fall into the description of open systems where mass is allowed to gain or loss via changes of volume, density of both. The characteristic thickening of the arterial wall is describe by means of a volumetric growth model. The stiffening of the arterial tissue, which is due to the increase of the collagen content, is formulated within a density growth model. Both of these approaches are described theoretically and are later included computationally in a finite element framework. The last part of this dissertation aims at deriving a model of endothelial cell orientation and morphological adaptation to the blood flow

Paradoxical aortic stiffening and subsequent cardiac dysfunction in Hutchinson-Gilford progeria syndrome

[EN] Hutchinson-Gilford progeria syndrome (HGPS) is an ultra-rare disorder with devastating sequelae resulting in early death, presently thought to stem primarily from cardiovascular events. We analyse novel longitudinal cardiovascular data from a mouse model of HGPS (Lmna(G609G/G609G)) using allometric scaling, biomechanical phenotyping, and advanced computational modelling and show that late-stage diastolic dysfunction, with preserved systolic function, emerges with an increase in the pulse wave velocity and an associated loss of aortic function, independent of sex. Specifically, there is a dramatic late-stage loss of smooth muscle function and cells and an excessive accumulation of proteoglycans along the aorta, which result in a loss of biomechanical function (contractility and elastic energy storage) and a marked structural stiffening despite a distinctly low intrinsic material stiffness that is consistent with the lack of functional lamin A. Importantly, the vascular function appears to arise normally from the low-stress environment of development, only to succumb progressively to pressure-related effects of the lamin A mutation and become extreme in the peri-morbid period. Because the dramatic life-threatening aortic phenotype manifests during the last third of life there may be a therapeutic window in maturity that could alleviate concerns with therapies administered during early periods of arterial development.This work was supported, in part, by grants from the US National Institutes of Health: R01 HL105297 (J.D.H.) and P01 HL134605 (Dan Rifkin) and R01 AG047632 and R33 ES025636 (G.S.S.)Murtada, SI.; Kawamura, Y.; Caulk, AW.; Ahmadzadeh, H.; Mikush, N.; Zimmerman, K.; Kavanagh, D.... (2020). Paradoxical aortic stiffening and subsequent cardiac dysfunction in Hutchinson-Gilford progeria syndrome. Journal of The Royal Society Interface. 17(166):1-12. https://doi.org/10.1098/rsif.2020.00661121716

Microstructural Characterisation of Resistance Artery Remodelling in Diabetes Mellitus

This is the final version. Available on open access from Karger Publishers via the DOI in this recordIntroduction: Microvascular remodelling is a symptom of cardiovascular disease. Despite the mechanical environment being recognised as a major contributor to the remodelling process, it is currently only understood in a rudimentary way. Objective: Amorphological and mechanicalevaluation of the resistance vasculature in health and diabetes mellitus.Methods: The cells and extracellular matrix of human subcutaneous resistance arteriesfrom abdominal fat biopsieswere imagedusing two-photon fluorescence and second harmonic generationat varying transmural pressure.The results informed a two-layer mechanical model.Results: Diabetic resistance arteries reducedin wall area as pressure was increased. This was attributed to the presence of thick, straight collagen fibre bundles that bracedthe outer wall.The abnormal mechanical environment caused theinternal elastic lamina and endothelial and vascular smooth muscle cellarrangementsto twist. Conclusions: Our resultssuggest diabetic microvascular remodelling is likely to be stress-driven, comprisingat least two stages: 1. Laying down of adventitial bracing fibres that limit outward distension, and 2. Deposition of additional collagen in the media, likely due to the significantly altered mechanical environment. This work represents a step towards elucidating the local stress environment of cells, which iscrucial to build accurate models of mechanotransduction in disease.British Heart FoundationMedical Research Council (MRC)National Institute for Health Research (NIHR

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

From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling

[EN] Tissue-level biomechanical properties and function derive from underlying cell signaling, which regulates mass deposition, organization, and removal. Here, we couple two existing modeling frameworks to capture associated multiscale interactions¿one for vessel-level growth and remodeling and one for cell-level signaling¿and illustrate utility by simulating aortic remodeling. At the vessel level, we employ a constrained mixture model describing turnover of individual wall constituents (elastin, intramural cells, and collagen), which has proven useful in predicting diverse adaptations as well as disease progression using phenomenological constitutive relations. Nevertheless, we now seek an improved mechanistic understanding of these processes; we replace phenomenological relations in the mixture model with a logic-based signaling model, which yields a system of ordinary differential equations predicting changes in collagen synthesis, matrix metalloproteinases, and cell proliferation in response to altered intramural stress, wall shear stress, and exogenous angiotensin II. This coupled approach promises improved understanding of the role of cell signaling in achieving tissue homeostasis and allows us to model feedback between vessel mechanics and cell signaling. We verify our model predictions against data from the hypertensive murine infrarenal abdominal aorta as well as results from validated phenomenological models, and consider effects of noisy signaling and heterogeneous cell populations.This work was supported by Grants from the US NIH (R01 HL105297, P01 HL134605, R01 HL139796, U01 HL142518, R01 HL146723)Irons, L.; Latorre, M.; Humphrey, JD. (2021). From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling. Annals of Biomedical Engineering. 48(7):1701-1715. https://doi.org/10.1007/s10439-020-02713-81701171548

The Virtual Physiological Human: Ten Years After

Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype–phenotype interaction and by a “systemic” nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible—the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done