Hiba Kobeissi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Hiba Kobeissi has a total of 22 co-authors. Here are the top co-authors by number of shared publications:
- Brendon M. Baker
University of Michigan
3 shared publications - David Nordsletten
Department of Biomedical Engineering, University of Michigan, MI, USA; Department of Cardiac Surgery, University of Michigan, MI, USA; Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
3 shared publications - Javiera Jilberto
Department of Biomedical Engineering, University of Michigan, MI, USA
3 shared publications - Samuel J. DePalma
Department of Biomedical Engineering, University of Michigan, MI, USA
3 shared publications Emma Lejeune
Department of Mechanical Engineering, Boston University, MA, USA
2 shared publications- Emma Lejeune
Department of Mechanical Engineering, Boston University, Boston, USA
2 shared publications
Latest Publications
- Open Access
- 20 July 2026
- Published by Public Library of Science (PLoS) in PLOS Computational Biology
- Vol. 22 (7) , e1014522
Quantifying the spatiotemporal mechanical dynamics of engineered cardiac microbundles
Brightfield time-lapse imaging is widely used in cardiac tissue engineering, yet the absence of standardized, interpretable analytical frameworks limits reproducibility and cross-platform comparison. We present an open, scalable computational pipeline for quantifying spatiotemporal contractile dynamics in microscopy videos of human induced pluripotent stem cell-derived cardiac microbundles. Building on our open-source tools “MicroBundleCompute” and “MicroBundlePillarTrack,” we define a suite of 16 interpretable structural, functional, and spatiotemporal metrics that capture tissue deformation, synchrony, and heterogeneity. The framework integrates full-field displacement tracking, strain reconstruction, spatial registration, dimensionality reduction, and topology-based vector-field analysis within a unified workflow. Applied to a dataset of 670 cardiac microbundles spanning 20 experimental conditions, the pipeline reveals continuous variation in contractile phenotypes rather than discrete condition-specific clustering, with intra-condition variability often exceeding inter-condition differences. Redundancy analysis identifies a reduced core set of 10 metrics that retain most informational content while minimizing multicollinearity. Analysis of denoised displacement fields shows that contraction is dominated by a global isotropic mode, with localized saddle-type deformation patterns present in approximately half of the samples. All software and workflows are released openly to enable reproducible, scalable analysis of dynamic tissue mechanics.
- 20 July 2026
- Published by Public Library of Science (PLoS) in PLOS Computational Biology
- Vol. 22 (7) , e1014522
Open AccessQuantifying the spatiotemporal mechanical dynamics of engineered cardiac microbundles
Brightfield time-lapse imaging is widely used in cardiac tissue engineering, yet the absence of standardized, interpretable analytical frameworks limits reproducibility and cross-platform comparison. We present an open, scalable computational pipeline for quantifying spatiotemporal contractile dynamics in microscopy videos of human induced pluripotent stem cell-derived cardiac microbundles. Building on our open-source tools “MicroBundleCompute” and “MicroBundlePillarTrack,” we define a suite of 16 interpretable structural, functional, and spatiotemporal metrics that capture tissue deformation, synchrony, and heterogeneity. The framework integrates full-field displacement tracking, strain reconstruction, spatial registration, dimensionality reduction, and topology-based vector-field analysis within a unified workflow. Applied to a dataset of 670 cardiac microbundles spanning 20 experimental conditions, the pipeline reveals continuous variation in contractile phenotypes rather than discrete condition-specific clustering, with intra-condition variability often exceeding inter-condition differences. Redundancy analysis identifies a reduced core set of 10 metrics that retain most informational content while minimizing multicollinearity. Analysis of denoised displacement fields shows that contraction is dominated by a global isotropic mode, with localized saddle-type deformation patterns present in approximately half of the samples. All software and workflows are released openly to enable reproducible, scalable analysis of dynamic tissue mechanics.
- Open Access
- 12 May 2026
- Published by Elsevier in Acta Biomaterialia
- Vol. 217, 424-442
Evaluating constrained and unconstrained mixture frameworks for predicting engineered heart tissue mechanics
- 12 May 2026
- Published by Elsevier in Acta Biomaterialia
- Vol. 217, 424-442
Open AccessEvaluating constrained and unconstrained mixture frameworks for predicting engineered heart tissue mechanics
- Open Access
- 18 November 2024
- Published by Wiley in Advanced Science
- Vol. 11 (47) , e2309740
Matrix Architecture and Mechanics Regulate Myofibril Organization, Costamere Assembly, and Contractility in Engineered Myocardial Microtissues
The mechanical function of the myocardium is defined by cardiomyocyte contractility and the biomechanics of the extracellular matrix (ECM). Understanding this relationship remains an important unmet challenge due to limitations in existing approaches for engineering myocardial tissue. Here, they established arrays of cardiac microtissues with tunable mechanics and architecture by integrating ECM‐mimetic synthetic, fiber matrices, and induced pluripotent stem cell‐derived cardiomyocytes (iPSC‐CMs), enabling real‐time contractility readouts, in‐depth structural assessment, and tissue‐specific computational modeling. They found that the stiffness and alignment of matrix fibers distinctly affect the structural development and contractile function of pure iPSC‐CM tissues. Further examination into the impact of fibrous matrix stiffness enabled by computational models and quantitative immunofluorescence implicates cell‐ECM interactions in myofibril assembly, myofibril maturation, and notably costamere assembly, which correlates with improved contractile function of tissues. These results highlight how iPSC‐CM tissue models with controllable architecture and mechanics can elucidate mechanisms of tissue maturation and disease.
- 18 November 2024
- Published by Wiley in Advanced Science
- Vol. 11 (47) , e2309740
Open AccessMatrix Architecture and Mechanics Regulate Myofibril Organization, Costamere Assembly, and Contractility in Engineered Myocardial Microtissues
The mechanical function of the myocardium is defined by cardiomyocyte contractility and the biomechanics of the extracellular matrix (ECM). Understanding this relationship remains an important unmet challenge due to limitations in existing approaches for engineering myocardial tissue. Here, they established arrays of cardiac microtissues with tunable mechanics and architecture by integrating ECM‐mimetic synthetic, fiber matrices, and induced pluripotent stem cell‐derived cardiomyocytes (iPSC‐CMs), enabling real‐time contractility readouts, in‐depth structural assessment, and tissue‐specific computational modeling. They found that the stiffness and alignment of matrix fibers distinctly affect the structural development and contractile function of pure iPSC‐CM tissues. Further examination into the impact of fibrous matrix stiffness enabled by computational models and quantitative immunofluorescence implicates cell‐ECM interactions in myofibril assembly, myofibril maturation, and notably costamere assembly, which correlates with improved contractile function of tissues. These results highlight how iPSC‐CM tissue models with controllable architecture and mechanics can elucidate mechanisms of tissue maturation and disease.
- 23 October 2023
- Published by Elsevier in Acta Biomaterialia
- Vol. 172, 123-134
A data-driven computational model for engineered cardiac microtissues
- 23 October 2023
- Published by Elsevier in Acta Biomaterialia
- Vol. 172, 123-134
A data-driven computational model for engineered cardiac microtissues