ABSTRACT
Cardiac optical mapping, also known as optocardiography, employs parameter-sensitive fluorescence dye(s) to image cardiac tissue and resolve the electrical and calcium oscillations that underly cardiac function. This technique is increasingly being used in conjunction with, or even as a replacement for, traditional electrocardiography. Over the last several decades, optical mapping has matured into a "gold standard" for cardiac research applications, yet the analysis of optical signals can be challenging. Despite the refinement of software tools and algorithms, significant programming expertise is often required to analyze large optical data sets, and data analysis can be laborious and time-consuming. To address this challenge, we developed an accessible, open-source software script that is untethered from any subscription-based programming language. The described software, written in python, is aptly named "KairoSight" in reference to the Greek word for "opportune time" (Kairos) and the ability to "see" voltage and calcium signals acquired from cardiac tissue. To demonstrate analysis features and highlight species differences, we employed experimental datasets collected from mammalian hearts (Langendorff-perfused rat, guinea pig, and swine) dyed with RH237 (transmembrane voltage) and Rhod-2, AM (intracellular calcium), as well as human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) dyed with FluoVolt (membrane potential), and Fluo-4, AM (calcium indicator). We also demonstrate cardiac responsiveness to ryanodine (ryanodine receptor modulator) and isoproterenol (beta-adrenergic agonist) and highlight regional differences after an ablation injury. KairoSight can be employed by both basic and clinical scientists to analyze complex cardiac optical mapping datasets without requiring dedicated computer science expertise or proprietary software.
ABSTRACT
AIMS: The duration and morphology of the T wave predict risk for ventricular fibrillation. A transmural gradient in action potential duration (APD) in the ventricular wall has been suggested to underlie the T wave in humans. We hypothesize that the transmural gradient in APD compensates for the normal endocardium-to-epicardium activation sequence and synchronizes repolarization in the human ventricular wall. METHODS AND RESULTS: We made left ventricular wedge preparations from 10 human donor hearts and measured transmural activation and repolarization patterns by optical mapping, while simultaneously recording a pseudo-ECG. We also studied the relation between local timings of repolarization with the T wave in silico. During endocardial pacing (1 Hz), APD was longer at the subendocardium than at the subepicardium (360 ± 17 vs. 317 ± 20 ms, P < 0.05). The transmural activation time was 32 ± 4 ms and resulted in final repolarization of the subepicardium at 349 ± 18 ms. The overall transmural dispersion in repolarization time was smaller than that of APD. During epicardial pacing, the dispersion in repolarization time increased, whereas that of APD remained similar. The morphology of the T wave did not differ between endocardial and epicardial stimulation. Simulations explained the constant T wave morphology without transmural APD gradients. CONCLUSION: The intrinsic transmural difference in APD compensates for the normal cardiac activation sequence, resulting in more homogeneous repolarization of the left ventricular wall. Our data suggest that the transmural repolarization differences do not fully explain the genesis of the T wave.
