Rationale: There are several methods to measure cardiomyocyte (CM) and muscle contraction but these require customized hardware, expensive apparatus and advanced informatics or can only be used in single experimental models. Consequently, data and techniques have been difficult to reproduce across models and laboratories, analysis is time consuming and only specialist researchers can quantify data. Objective: Here we describe and validate an automated, open source software tool (MUSCLEMOTION) adaptable for use with standard laboratory- and clinical imaging equipment that enables quantitative analysis of normal cardiac contraction, disease phenotypes and pharmacological responses. Methods and Results: MUSCLEMOTION allowed rapid and easy measurement of movement from high-speed movies in: (i) 1-dimensional in vitro models such as isolated adult and human pluripotent stem cell-derived CMs (hPSC-CMs); (ii) 2-dimensional in vitro models, such as beating CM monolayers or small clusters of hPSC-CMs; (iii) 3-dimensional multicellular in vitro or in vivo contractile tissues such as cardiac "organoids", engineered heart tissues (EHT), zebrafish- and human hearts. MUSCLEMOTION was effective under different recording conditions (bright field microscopy with simultaneous patch clamp recording, phase contrast microscopy and traction force microscopy). Outcomes were virtually identical to the current gold standards for contraction measurement such as optical flow, pole deflection, edge-detection systems or manual analyses. Finally, we used the algorithm to quantify contraction in in vitro and in vivo arrhythmia models and to measure pharmacological responses. Conclusions: Using a single open source method for processing video recordings, we obtained reliable pharmacological data and measures of cardiac disease phenotype in experimental cell-, animal- and human models.

To evaluate multi-detector row computed tomographic (CT) depiction of pulmonary veins to provide a road map for radiofrequency catheter ablation. For patients, institutional review board (IRB) approval was not required, and consent was obtained for treatment. Control subjects were part of an IRB-approved research protocol at the institution, in which they had consented to participate. Multi-detector row CT was performed in 23 patients (17 men, six women; mean age, 48 years +/- 11 [standard deviation]) with atrial fibrillation who were admitted for isolation of pulmonary veins by means of radiofrequency catheter ablation. Pulmonary vein anatomy was evaluated, and diameters of pulmonary vein ostia were measured. To determine the shape of ostia, a venous ostium index was calculated for all veins by dividing anterior-posterior measurements by superior-inferior measurements. Results were compared with those in a control group of 11 patients (eight men, three women; mean age, 56 years +/- 11) without atrial fibrillation. Images were evaluated by two observers in consensus. Pulmonary veins additional to the four main veins were found in seven (30%) of 23 patients. Common ostia of left and right pulmonary veins were detected in 19 (83%) and nine (39%) patients, respectively. Early branching occurred more often with right than with left veins (19 [83%] vs three [13%] cases, P <.05) in both patients and control subjects. Anterior-posterior diameter of ostia was 12.8 mm +/- 3.3 for left veins, 16.2 mm +/- 3.8 for right veins, and 18.8 mm +/- 7.7 and 28.7 mm +/- 5.1 for left and right common ostia, respectively. Ostia of right pulmonary veins were more round than were ostia of left pulmonary veins (venous ostium index in patients, 0.91 +/- 0.21 vs 0.75 +/- 0.17, P <.05; in control subjects, 0.93 +/- 0.12 vs 0.82 +/- 0.17, P <.05). The CT data were used to determine ablation strategy and guide catheters during radiofrequency ablation. Multi-detector row CT provides a valuable road map for pulmonary vein anatomy prior to radiofrequency catheter ablation. Variations in number and insertion of pulmonary veins were observed in a considerable number of patients and control subjects.