MicroBundlePillarTrack

MicroBundlePillarTrack automates segmentation, tracking, and analysis of pillar deflection in cardiac microbundles to quantify contractility metrics and enable reproducible cross-platform comparisons.

Key Features:

• Automated Pillar Segmentation: Automatically segments pillars in brightfield movies of cardiac microbundles without manual intervention.
• Optical Flow-Based Tracking: Tracks pillar displacements using optical flow methods to measure tissue contractility.
• Contractility Metric Extraction: Outputs time-dependent metrics including beating amplitude, beating rate, contractile force, and tissue stress.
• Cross-Platform Compatibility: Supports analysis of microbundles grown on two different pillar designs (Type 1 and Type 2 design).
• High-Throughput Analysis: Enables automated processing of large datasets for faster and more reproducible analyses.

Scientific Applications:

• Cardiac Tissue Contractility Analysis: Quantifies contractile properties of human induced pluripotent stem cell-derived engineered cardiac tissue microbundles.
• Cross-Platform Comparison: Enables direct quantitative comparisons across multiple in vitro experimental platforms for cardiac tissue fabrication.
• Structural and Functional Maturity Assessment: Extracts data about structural and functional maturity from movies of engineered cardiac tissues.
• Inter-Laboratory Reproducibility: Facilitates quantitative comparisons across labs through standardized automated analysis.

Methodology:

MicroBundlePillarTrack uses optical flow-based tracking in Python to segment pillars and track their displacements in brightfield movies, with validation performed on a dataset of 1,540 brightfield example movies of hiPSC-derived engineered cardiac tissue microbundles.