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.

翻译：明场延时成像在心脏组织工程中被广泛应用，但缺乏标准化、可解释的分析框架限制了其可重复性和跨平台比较。我们提出了一种开放、可扩展的计算流程，用于量化人诱导多能干细胞来源心脏微束在显微镜视频中的时空收缩动力学。基于我们开源工具"MicroBundleCompute"和"MicroBundlePillarTrack"，我们定义了16个可解释的结构、功能和时空度量指标，以捕捉组织形变、同步性和异质性。该框架在全场位移追踪、应变重建、空间配准、降维和基于拓扑的向量场分析基础上，整合为统一工作流程。应用于涵盖20种实验条件的670个心脏微束数据集后，该流程揭示了收缩表型的连续变化（而非离散的条件特异性聚类），且同一条件内变异常超过条件间差异。冗余分析识别出一个精简的核心度量集（10个指标），在保留大部分信息内容的同时最小化了多重共线性。对去噪位移场的分析表明，收缩由全局各向同性模式主导，局部鞍型形变模式存在于约半数样本中。所有软件和工作流程均已公开，以实现动态组织力学的可重复、可扩展分析。