Estimation of Active Tension in Cardiac Microtissues by Solving a PDE-Constrained Optimization Problem.

Area of Science:

• Biomedical Engineering
• Cardiovascular Research
• Stem Cell Technology

Background:

• Microphysiological systems (MPS) enable controlled testing of human-induced pluripotent stem cell-based cardiac microtissues.
• Optical measurements in MPS can assess mechanical features like motion and velocity.
• Quantifying active tension in cardiac microtissues remains a significant challenge.

Purpose of the Study:

• To develop and validate a computational framework for spatiotemporal quantification of active tension in cardiac microtissues.
• To apply this framework to assess drug effects on cardiac microtissue mechanics.

Main Methods:

• Formulated a partial differential equation (PDE)-constrained optimization problem to solve an inverse problem in cardiac mechanics.
• Developed a mechanical model for 2D cardiac microtissue representations.
• Utilized synthetic and experimental data for validation and drug escalation studies.

Main Results:

• The computational framework successfully predicted active tension and fiber direction distribution.
• Drug escalation studies with omecamtiv mecarbil and Bay K8644 showed increased displacement, strain, and active strain.
• Estimated active tension was highest centrally, with fiber alignment along the longitudinal axis.

Conclusions:

• The presented computational framework enables spatiotemporal estimation of active tension in cardiac microtissues from optical measurements.
• This methodology shows promise as a valuable tool for drug development and cardiac disease modeling.