Aaron Brown

All Publications

• Personalized biventricular mechanics and sensitivity to model morphology. bioRxiv : the preprint server for biology Brown, A. L., Shi, L., Salvador, M., Kong, F., Ennis, D. B., Chen, I., Vedula, V., Marsden, A. L. 2025

  Abstract

  We present a computational framework for constructing patient-specific models of cardiac mechanics based on standard clinical data, including electrocardiogram (ECG), cuff blood pressure, and electrocardiography-gated computed tomography angiography (CTA) imaging. The model is coupled to a closed-loop lumped parameter network (LPN) circulatory model and incorporates rule-based fiber architecture, as well as spatially varying epicardial boundary conditions to approximate surrounding tissue support. Model parameters are personalized through a multistep procedure that sequentially tunes circulatory dynamics, passive mechanics, and active contraction. The resulting personalized BiV model closely matches clinical pressure and volume measurements and reasonably agrees with image-based myocardial deformation. To assess the impact of anatomical model choice, we compare the BiV model to two commonly-used simplifications: a truncated BiV (t-BiV) model cut at the basal plane and a left ventricle-only (LV) model. For these models, we also evaluate their sensitivity to plausible variations in boundary conditions and contractile strength. With all other inputs held fixed, the LV model exhibits similar global pressure/volume behavior, despite moderate differences in regional deformation. In contrast, the t-BiV model produces substantial differences in both global function and local myocardial mechanics. These results suggest that while LV-only models may be sufficient for biomechanical studies, truncation at the basal plane strongly impacts model outputs and should be used with caution.

  View details for DOI 10.64898/2025.12.11.693778

  View details for PubMedID 41446240

  View details for PubMedCentralID PMC12724658

• Mechanically activated snai1b coordinates the initiation of myocardial delamination for trabeculation. Nature communications Wang, J., Brown, A. L., Park, S. K., Zheng, C. Z., Langenbacher, A., Zhu, E., O'Donnell, R., Zhao, P., Hsu, J. J., Yokota, T., Liu, J., Chen, J. N., Marsden, A. L., Hsiai, T. K. 2025; 16 (1): 8363

  Abstract

  During development, myocardial contractile force and intracardiac hemodynamic shear stress coordinate the initiation of trabeculation. While Snail family genes are well-recognized transcription factors of epithelial-to-mesenchymal transition, snai1b-positive cardiomyocytes are sparsely distributed in the ventricle of zebrafish at 4 days post-fertilization. Isoproterenol treatment significantly increases the number of snai1b-positive cardiomyocytes, of which 80% are Notch-negative. CRISPR-activation of snai1b leads to 51.6% cardiomyocytes forming trabeculae, whereas CRISPR-repression reduces trabecular cardiomyocytes to 6.7% under isoproterenol. In addition, 36.7% of snai1b-repressed cardiomyocytes undergo apical delamination. 4-D strain analysis demonstrates that isoproterenol increases the myocardial strain along radial trabecular ridges in alignment with the snai1b expression and Notch-ErbB2-mediated trabeculation. Single-cell and spatial transcriptomics reveal that these snai1b-positive cardiomyocytes are devoid of some epithelial-to-mesenchymal transition-related phenotypes, such as Col1a2 production and induction by ErbB2 or TGF-β. Thus, we uncover snai1b-positive cardiomyocytes that are mechanically activated to initiate delamination for cardiac trabeculation.

  View details for DOI 10.1038/s41467-025-62285-w

  View details for PubMedID 40993149

  View details for PubMedCentralID 4712836

• Cardiac mechanics modeling: recent developments and current challenges. ArXiv Brown, A. L., Liu, J., Ennis, D. B., Marsden, A. L. 2025

  Abstract

  Patient-specific computational models of the heart are powerful tools for cardiovascular research and medicine, with demonstrated applications in treatment planning, device evaluation, and surgical decision-making. Yet constructing such models is inherently difficult, reflecting the extraordinary complexity of the heart itself. Numerous considerations are required, including reconstructing the anatomy from medical images, representing myocardial mesostructure, capturing material behavior, defining model geometry and boundary conditions, coupling multiple physics, and selecting numerical methods. Many of these choices involve a tradeoff between physiological fidelity and modeling complexity. In this review, we summarize recent advances and unresolved questions in each of these areas, with particular emphasis on cardiac tissue mechanics. We argue that clarifying which complexities are essential, and which can be safely simplified, will be key to enabling clinical translation of these models.

  View details for DOI 10.1093/eurheartj/ehae619

  View details for PubMedID 40964080

  View details for PubMedCentralID PMC12440063

• A fluid-structure interaction model of the zebrafish aortic valve. Journal of biomechanics Kaiser, A. D., Wang, J., Brown, A. L., Zhu, E., Hsiai, T., Marsden, A. L. 2025; 190: 112794

  Abstract

  The zebrafish is a valuable model organism for studying cardiac development and diseases due to its many shared aspects of genetics and anatomy with humans and ease of experimental manipulations. Computational fluid-structure interaction (FSI) simulations are an efficient and highly controllable means to study the function of cardiac valves in development and diseases. Due to their small scales, little is known about the mechanical properties of zebrafish cardiac valves, limiting existing computational studies of zebrafish aortic valves and their interaction with blood. To circumvent these limitations, we took a largely first-principles approach called design-based elasticity that allows us to derive valve geometry, fiber orientation and material properties. In FSI simulations of an adult zebrafish aortic valve, these models produce realistic flow rates when driven by physiological pressures and demonstrate the spatiotemporal dynamics of valvular mechanical properties. These models can be used for future studies of zebrafish cardiac hemodynamics, development, and disease.

  View details for DOI 10.1016/j.jbiomech.2025.112794

  View details for PubMedID 40773901

• A software benchmark for cardiac elastodynamics COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING Arostica, R., Nolte, D., Brown, A., Gebauer, A., Karabelas, E., Jilberto, J., Salvador, M., Bucelli, M., Piersanti, R., Osouli, K., Augustin, C., Finsberg, H., Shi, L., Hirschvogel, M., Pfaller, M., Africa, P., Gsell, M., Marsden, A., Nordsletten, D., Regazzoni, F., Plank, G., Sundnes, J., Dede', L., Peirlinck, M., Vedula, V., Wall, W., Bertoglio, C. 2025; 435

  View details for DOI 10.1016/j.cma.2024.117485

  View details for Web of Science ID 001396055500001

• A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics. Computer methods in applied mechanics and engineering Brown, A. L., Salvador, M., Shi, L., Pfaller, M. R., Hu, Z., Harold, K. E., Hsiai, T., Vedula, V., Marsden, A. L. 2024; 421

  Abstract

  In numerical simulations of cardiac mechanics, coupling the heart to a model of the circulatory system is essential for capturing physiological cardiac behavior. A popular and efficient technique is to use an electrical circuit analogy, known as a lumped parameter network or zero-dimensional (0D) fluid model, to represent blood flow throughout the cardiovascular system. Due to the strong physical interaction between the heart and the blood circulation, developing accurate and efficient numerical coupling methods remains an active area of research. In this work, we present a modular framework for implicitly coupling three-dimensional (3D) finite element simulations of cardiac mechanics to 0D models of blood circulation. The framework is modular in that the circulation model can be modified independently of the 3D finite element solver, and vice versa. The numerical scheme builds upon a previous work that combines 3D blood flow models with 0D circulation models (3D fluid - 0D fluid). Here, we extend it to couple 3D cardiac tissue mechanics models with 0D circulation models (3D structure - 0D fluid), showing that both mathematical problems can be solved within a unified coupling scheme. The effectiveness, temporal convergence, and computational cost of the algorithm are assessed through multiple examples relevant to the cardiovascular modeling community. Importantly, in an idealized left ventricle example, we show that the coupled model yields physiological pressure-volume loops and naturally recapitulates the isovolumic contraction and relaxation phases of the cardiac cycle without any additional numerical techniques. Furthermore, we provide a new derivation of the scheme inspired by the Approximate Newton Method of Chan (1985), explaining how the proposed numerical scheme combines the stability of monolithic approaches with the modularity and flexibility of partitioned approaches.

  View details for DOI 10.1016/j.cma.2024.116764

  View details for PubMedID 38523716

  View details for PubMedCentralID PMC10956732

• Computational approaches for mechanobiology in cardiovascular development and diseases. Current topics in developmental biology Brown, A. L., Sexton, Z. A., Hu, Z., Yang, W., Marsden, A. L. 2024; 156: 19-50

  Abstract

  The cardiovascular development in vertebrates evolves in response to genetic and mechanical cues. The dynamic interplay among mechanics, cell biology, and anatomy continually shapes the hydraulic networks, characterized by complex, non-linear changes in anatomical structure and blood flow dynamics. To better understand this interplay, a diverse set of molecular and computational tools has been used to comprehensively study cardiovascular mechanobiology. With the continual advancement of computational capacity and numerical techniques, cardiovascular simulation is increasingly vital in both basic science research for understanding developmental mechanisms and disease etiologies, as well as in clinical studies aimed at enhancing treatment outcomes. This review provides an overview of computational cardiovascular modeling. Beginning with the fundamental concepts of computational cardiovascular modeling, it navigates through the applications of computational modeling in investigating mechanobiology during cardiac development. Second, the article illustrates the utility of computational hemodynamic modeling in the context of treatment planning for congenital heart diseases. It then delves into the predictive potential of computational models for elucidating tissue growth and remodeling processes. In closing, we outline prevailing challenges and future prospects, underscoring the transformative impact of computational cardiovascular modeling in reshaping cardiovascular science and clinical practice.

  View details for DOI 10.1016/bs.ctdb.2024.01.006

  View details for PubMedID 38556423

• Recent advances in quantifying the mechanobiology of cardiac development via computational modeling. Current opinion in biomedical engineering Brown, A. L., Gerosa, F. M., Wang, J., Hsiai, T., Marsden, A. L. 2023; 25

  Abstract

  Mechanical forces are essential for coordinating cardiac morphogenesis, but much remains to be discovered about the interactions between mechanical forces and the mechanotransduction pathways they activate. Due to the elaborate and fundamentally multi-physics and multi-scale nature of cardiac mechanobiology, a complete understanding requires multiple experimental and analytical techniques. We identify three fundamental tools used in the field to probe these interactions: high resolution imaging, genetic and molecular analysis, and computational modeling. In this review, we focus on computational modeling and present recent studies employing this tool to investigate the mechanobiological pathways involved with cardiac development. These works demonstrate that understanding the detailed spatial and temporal patterns of biomechanical forces is crucial to building a comprehensive understanding of mechanobiology during cardiac development, and that computational modeling is an effective and efficient tool for obtaining such detail. In this context, multidisciplinary studies combining all three tools present the most compelling results.

  View details for DOI 10.1016/j.cobme.2022.100428

  View details for PubMedID 36583220

  View details for PubMedCentralID PMC9794182