Special Issue: Spotlight on the Future of Cardiovascular Engineering:Frontiers and Challenges in Cardiovascular Biomechanics
Year: 2016
Type: article
Abstract: This special issue of JBME highlights frontiers and challenges in cardiovascular biomechanics. Nine young investigators have contributed to this special issue [1–9]. Experimental work ranges from individual smooth muscle cells to engineered cardiac tissue to whole arteries. Modeling work ranges from predicting cardiomyocyte responses to optogenetic stimuli to patient-specific ventricular mechanics. In this commentary, we both summarize the work showcased in this issue and discuss some of the current frontiers and challenges in the field. We highlight significant advances in growth and remodeling (G&R) and patient-specific computational models, as well as technical and economic considerations for the future utility of such models. We discuss experimental models that move beyond cell culture and the relevance of tissue biomechanics, especially when tissue-specific mechanics can be readily altered with genetic engineering. Finally, we touch on changes in the funding landscape for cardiovascular biomechanics.Two decades ago, Rodriguez et al. introduced their volumetric finite growth framework, providing a convenient way to account for the effects of the growth or atrophy of solid tissues and organs on residual stress [10]. A decade later, Humphrey and Rajagopal introduced their constrained mixture formulation, which allows for turnover of multiple tissue constituents—each with its own evolving reference configuration—that together determine the mechanical properties of a remodeling tissue [11,12]. Building largely on these landmark papers, modeling growth and remodeling (G&R) has become one of the most exciting and rapidly growing areas in cardiovascular biomechanics. There is good reason for the excitement. Traditional finite-element models are invaluable in designing cardiovascular devices and therapies, allowing designers to predict how deploying a stent or inserting a prosthetic valve will alter blood flow, heart function, and other critical variables. Yet the body adapts to any intervention, so predicting the initial response to a therapy is only the beginning. G&R models represent a fundamentally new capability to predict the single thing that matters most to doctors and patients: long-term outcomes.The field is now moving beyond a focus on simply formulating quantitative models of growth and beginning to apply these models to answer interesting questions and develop new treatments. For example, G&R models have been used to evaluate the effects of surgical removal [13] or reinforcement [14] of a myocardial infarct, to simulate venous adaptation to elevated pressures as occurs following coronary artery bypass grafting (CABG) [15] and to predict the maturation of tissue-engineered blood vessels in a bioreactor [16]. In this special issue, Hald et al. combined a G&R model with experimental measures of vascular smooth muscle cell contractility to investigate the effects of amyloid beta on cerebrovascular function [4]. They found that amyloid beta reduces smooth muscle cell contractility, and their G&R model predicts that the subsequent amyloid beta-dependent remodeling decreases vasodilatory capacity of the cerebrovascular vessels, which could play a role in neurodegeneration in Alzheimer's disease.One challenge that will arise as growth models come into widespread use is to develop validation methods that can adequately test these models. At a superficial level, predictions of changes in mass or composition appear fairly easy to verify in animal studies where tissue can be harvested. Yet the mass of most tissues and constituents reflects a continuing balance between deposition and degradation; thus, many different combinations of deposition and degradation rates could yield the same change in mass. This simple idea can have important consequences when designing therapies. For example, trying to block a change in collagen content by inhibiting matrix metalloproteinases (MMPs) will be ineffective if that change arises primarily through decreased deposition rather than through increased degradation.Measuring deposition and degradation rates of individual tissue components directly may thus be an important step in validating G&R models. To the best of our knowledge, there is relatively little published work in this area in the cardiovascular system. However, recent studies in tendon illustrate methods that may prove useful as well as the potential complexity of understanding turnover of even a single constituent in a single tissue. Langberg et al. used microdialysis to sample interstitial fluid from the region surrounding the Achilles tendon and found that the concentration of peptides generated during collagen assembly (PICP, carboxy-terminal propeptide of type I collagen) and degradation (ICTP, type I collagen carboxy-terminal telopeptide) increased significantly 72 h after a single 3 h distance run [17]. Several years later, the same group used an alternate method—measuring incorporation of amino acids labeled with stable isotopes—and found that 24 h after a single bout of intense exercise, the fractional collagen synthesis rate in patellar tendons increased from 1%/day to nearly 2%/day [18]. Both of these methods suggested high levels of collagen turnover in tendon, with dynamic responses to exercise. Yet in 2013, the same group assayed the levels of radioactive carbon generated during nuclear tests in the 1950 s and 1960 s in tendon tissue obtained at autopsy and found that there is essentially no turnover of carbon atoms in adult tendon after age 17, even over decades of adult life [19]. These apparently contradictory results may indicate that there are multiple pools of collagen in tendon that turn over at very different rates, and measurements of component turnover in cardiovascular tissues may reveal similar complexity.Another exciting area for potential development is imaging changes in tissue volume, composition, and constituent turnover in vivo. For example, some groups have used high-speed X-ray of implanted metal markers—a decades-old technique for measuring beat-to-beat tissue mechanics in the heart—to quantify transmural gradients in tissue remodeling following myocardial infarction or imposition of hemodynamic overload in animals [20–22]. Because it can provide real-time, coupled data on regional mechanics and G&R at multiple locations and time points, this approach could be very valuable in validating and calibrating growth models. Changes in residual stress and in the reference state of individual components predicted by G&R models are more difficult to validate, especially if the goal is to image these changes in intact tissues. Yet systems that integrate ex vivo loading of intact tissues with X-ray diffraction, second-harmonic generation (SHG), or other imaging methods could provide this information. For example, Liao et al. used small angle X-ray scattering to measure rotation and recruitment of collagen fibers during planar biaxial testing [23]; such studies could also reveal changes in collagen fiber reference state with remodeling. Similarly, Wang et al. used SHG to image collagen fiber uncrimping and rotation during inflation of carotid arteries [24]. SHG has also been used to image extracellular matrix (ECM) changes during G&R, including cardiac fibrosis following pressure overload [25] and collagen fiber remodeling in stented pulmonary arteries [26]. Pursell et al. used SHG in this special issue to relate structural changes in collagen fibers to mechanical changes in the pulmonary artery with induced hypertension [6]. They found that the structural and mechanical changes are different in the left and right pulmonary arteries and also different in the axial and circumferential directions, highlighting the complexity of ECM changes during G&R.Patient-specific modeling is another exciting and potentially high-impact frontier in cardiovascular biomechanics. To date, much of the attention surrounding personalized medicine has focused on identifying factors such as genetic variations that affect the efficacy of different drugs available to treat a particular condition such as high blood pressure. Patient-specific modeling could offer analogous benefits in customizing surgical, interventional, and device-based therapies. For example, cardiac resynchronization therapy (CRT) uses electrical pulses delivered from pacemaker leads implanted in multiple locations to improve contractile performance in patients with heart failure. Cardiologists already use measures of electrical and mechanical synchrony to decide which patients are likely to benefit from CRT; however, many patients who meet the selection criteria do not respond, and many others achieve suboptimal results. A method to customize lead placement and pacemaker settings to individual patients; patient-specific modeling has the potential to provide exactly this information.Reflecting the excitement surrounding this area, two of the nine papers in this special issue employ customized models of individual animals or patients. Wang et al. used animal-specific finite-element models to investigate the in vivo distribution of myocardial contractile forces across the left ventricular wall [8]. They found that models with transmural gradients in contractility provide the best fit to in vivo data and suggest that changes in the transmural contractility gradient may be an important consideration in evaluating left ventricular function in heart disease. Xi et al. used patient-specific computational models to investigate the effects of pulmonary hypertension on left ventricular mechanics and curvature [9]. They found that curvature changes, which can easily be measured in clinical images, may be useful in quantifying transseptal pressure gradients.Constructing models of individual patients or animals has many important research applications. Among other advantages, such models help reveal the sources and implications of individual variability, something that until recently most researchers all but ignored. Yet as we seek to move patient-specific models (PSMs) into the clinic, there are important, systemic questions that must be thoughtfully addressed by the biomechanics community. Some of these are already under active discussion. For example, simulation run times are frequently reported, although concerns about whether long run times are practical for clinical application are frequently dismissed with a cursory assertion that computers will keep getting faster. Other issues, such as the parameter identifiability concerns that arise when models with many parameters are fitted to relatively sparse clinical data, are receiving more substantive attention [27,28]. The cardiovascular fluid biomechanics community has also organized an intriguing series of computational challenges that highlight the challenges of standardizing the construction and application of PSMs [29–31].However, in our view, one of the biggest practical limitations to clinical translation of patient-specific models is receiving far too little attention. Put bluntly, in the American medical system, time is quite literally money. In addition to the costs of obtaining the medical images and other datasets that provide inputs to PSMs, the time required to extract this information and customize and verify the model for each individual patient is an important factor in determining clinical viability. For pilot studies, this work is often done by graduate students funded by research grants; in routine clinical practice, it is unclear who would conduct this analysis, and who would pay for it. One way to avoid this dilemma is to only incorporate information into PSMs that can be obtained through fully automated analyses; this approach seems overly restrictive and neglects the fact that at a minimum some quality control of automated analyses will likely be required. A more interesting approach, that may have broader implications for bioengineering as a profession, might be to introduce a new category of clinical engineer, trained in imaging and modeling, who works closely with clinicians to construct and run PSMs while also providing critical quality control and the ability to troubleshoot and adapt the PSM as needed for individual cases. In the long term, the utility and impact of PSM will depend not only on the technical quality of the models but also on these broader economic questions. Thus, an important step we can take as a community is to provide the information needed to evaluate the economic viability of these models, by rigorously documenting the time and expense required to obtain each input to our PSMs, as well as the relative value of each specific input for model accuracy.When contemplating the future of PSMs, one cardiovascular biomechanics success story that is currently unfolding provides both inspiration and potential lessons. Over the past decade, Taylor and colleagues developed methods for using PSMs of the coronary vasculature derived from computed tomography (CT) to predict fractional flow reserve (FFR), a measure of the degree to which a stenosis reduces maximal flow in response to infusion of a vasodilator during an invasive coronary catheterization procedure [32,33]. The model-predicted metric FFRCT performed well in clinical trials and is now approved for clinical use in the U.S. [34–37]. Replacing an invasive procedure with a PSM in routine clinical practice is a major step forward for the field. In addition to hard work and technical quality, this success reflects smart choices that may inform other work: FFRCT relies primarily on patient-specific differences in coronary anatomy that can be determined accurately from imaging and requires very little patient-specific fitting of other model parameters [33].Cell culture studies are an important tool in biology and bioengineering. It is widely recognized that one trade-off inherent in primary cell culture is that disrupting the physical and biochemical connections between cells and the surrounding ECM makes them easier to study but also fundamentally changes their biology. However, for those who work in cardiovascular biomechanics, the mechanical aspects of this trade-off present additional concerns. Removing cells that are normally subjected to cyclic stretch, pulsatile flow, and other dynamic mechanical stimuli and plating them on static surfaces raises major questions about how to interpret any subsequent measurement. As one example, isolated neonatal myocytes completely disassemble their sarcomeric structure and stop beating, then gradually reassemble it in a different geometry and begin beating again over the first couple of days. Does the response to stretch or shear of cells that have been cultured statically for days or weeks provide useful information on mechanotransduction, or simply reflect a return toward baseline from a severely artificial state? The demonstrated importance of ECM attachments and cytoskeletal tension to mechanotransduction certainly gives pause when interpreting experiments where both these factors have been altered.Accordingly, the maturation of the field of tissue engineering has also made an important contribution to cardiovascular cell mechanics, by providing a greater range of model systems for studying cell behavior in 3D environments, incorporating relevant features such as cell alignment and ECM contacts. Recently, Shamir and Ewald reviewed 3D cell culture and discussed considerations for cell types, ECM material, and culture geometry for a variety of tissue types and diseases [38]. In this special issue, Rayner and Zheng reviewed engineered microvessels as a 3D platform to study human disease [7]. The microvessel platform allows precise control of factors such as ECM material, cell types, flow rates, pressures, and biochemical environment to study endothelial–blood interactions, endothelial–perivascular interactions, angiogenesis, and tumor biology. Also in this special issue, Drew et al. used engineered cardiac tissue to investigate self-assembly and force development in cardiomyocytes [3]. They found that self-assembly and force generation are optimized under similar conditions and that the organizational structure of various cytoskeletal elements is tightly correlated.To replace, treat, or model cardiovascular tissue, the in vivo loading conditions and resulting deformations must be fully characterized. In complex geometries, such as the heart valves, in vitro experimental approaches have evolved to better reproduce the in vivo state. Early testing of heart valve mechanics involved removing the valves and individually evaluating mechanical behavior of the leaflets and chordae tendinae [39]. Later testing approaches involved keeping the valves intact, but rigidly restricting the valve annulus for mounting in the test system [40]. In this special issue, Amini Khoiy et al. measured surface strains on the tricuspid valve septal leaflets in an intact beating heart [2]. Their experimental setup provides a platform for testing the effects of valve lesions, valve repair procedures, and validating combined valve/ventricle computational models.In vitro testing of cardiovascular tissues requires physiologic flow and pressure waveforms that are often difficult to reproduce in benchtop experiments. 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DOI: 10.1115/1.4034873
Authors: Jeffrey W. Holmes, Jessica E. Wagenseil
Institutions: University of Virginia, Washington University in St. Louis
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2544089263