Fluorescence optical imaging techniques have revolutionized the field of cardiac electrophysiology and advanced our understanding of complex electrical activities such as arrhythmias. However, traditional monocular optical mapping systems, despite having high spatial resolution, are restricted to a two-dimensional (2D) field of view. Consequently, tracking complex three-dimensional (3D) electrical waves such as during ventricular fibrillation is challenging as the waves rapidly move in and out of the field of view. This problem has been solved by panoramic imaging which uses multiple cameras to measure the electrical activity from the entire epicardial surface. However, the diverse engineering skill set and substantial resource cost required to design and implement this solution have made it largely inaccessible to the biomedical research community at large. To address this barrier to entry, we present an open source toolkit for building panoramic optical mapping systems which includes the 3D printing of perfusion and imaging hardware, as well as software for data processing and analysis. In this paper, we describe the toolkit and demonstrate it on different mammalian hearts: mouse, rat, and rabbit.

Since the 1970s fluorescence imaging has become a leading tool in the discovery of mechanisms of cardiac function and arrhythmias. Gradual improvements in fluorescent probes and multi-camera technology have increased the power of optical mapping and made a major impact on the field of cardiac electrophysiology. Tandem-lens optical mapping systems facilitated simultaneous recording of multiple parameters characterizing cardiac function. However, high cost and technological complexity restricted its proliferation to the wider biological community. We present here, an open-source solution for multiple-camera tandem-lens optical systems for multiparametric mapping of transmembrane potential, intracellular calcium dynamics and other parameters in intact mouse hearts and in rat heart slices. This 3D-printable hardware and Matlab-based RHYTHM 1.2 analysis software are distributed under an MIT open-source license. Rapid prototyping permits the development of inexpensive, customized systems with broad functionality, allowing wider application of this technology outside biomedical engineering laboratories.

We present a novel modification of genetic algorithm (GA) which determines personalized parameters of cardiomyocyte electrophysiology model based on set of experimental human action potential (AP) recorded at different heart rates. In order to find the steady state solution, the optimized algorithm performs simultaneous search in the parametric and slow variables spaces. We demonstrate that several GA modifications are required for effective convergence. Firstly, we used Cauchy mutation along a random direction in the parametric space. Secondly, relatively large number of elite organisms (6-10% of the population passed on to new generation) was required for effective convergence. Test runs with synthetic AP as input data indicate that algorithm error is low for high amplitude ionic currents (1.6±1.6% for IKr, 3.2±3.5% for IK1, 3.9±3.5% for INa, 8.2±6.3% for ICaL). Experimental signal-to-noise ratio above 28 dB was required for high quality GA performance. GA was validated against optical mapping recordings of human ventricular AP and mRNA expression profile of donor hearts. In particular, GA output parameters were rescaled proportionally to mRNA levels ratio between patients. We have demonstrated that mRNA-based models predict the AP waveform dependence on heart rate with high precision. The latter also provides a novel technique of model personalization that makes it possible to map gene expression profile to cardiac function.

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In this work we present a one-dimensional (1D) mathematical model of the coronary circulation and use it to study the effects of arrhythmias on coronary blood flow (CBF). Hydrodynamical models are rarely used to study arrhythmias’ effects on CBF. Our model accounts for action potential duration, which updates the length of systole depending on the heart rate. It also includes dependency of stroke volume on heart rate, which is based on clinical data. We apply the new methodology to the computational evaluation of CBF during interventricular asynchrony due to cardiac pacing and some types of arrhythmias including tachycardia, bradycardia, long QT syndrome and premature ventricular contraction (bigeminy, trigeminy, quadrigeminy). We find that CBF can be significantly affected by arrhythmias. CBF at rest (60 bpm) is 26% lower in LCA and 22% lower in RCA for long QT syndrome. During bigeminy, trigeminy and quadrigeminy, respectively, CBF decreases by 28%, 19% and 14% with respect to a healthy case.

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We have simulated 3D propagation of the action potential in the sinoatrial node to study the dynamics of the heart rhythm initiation. We have found that the leading center inside the sinoatrial node is formed by a group of cells, appears spontaneously under normal conditions, and migrates as acetylcholine is applied. The leading center drifts toward the center of the sinoatrial node, if we consider the effect of the surrounding atrial tissue. Abnormal electrical activity, rotating waves of action potential are observed in the sinoatrial node.

While the sinoatrial node (SAN) is structurally heterogeneous, most computer simulations of electrical activity take into account SAN pacemaker cells only. Our aim was to investigate how fibroblasts affect the SAN activity. We simulated the rabbit sinoatrial node accounting for differences between central and peripheral pacemaker cells, and for fibroblast-myocyte electrical coupling. We have observed that only if fibroblast-myocyte coupling is taken into account, (1) action potential is initiated in the central part of the SAN (within 1.2 mm of the center of simulated tissue); otherwise, leading centers are located on the periphery; (2) few (1 to 6) leading centers initiate action potential in the SAN; otherwise, we observed more than 8 leading centers; (3) acetylcholine superfusion results in a shift of leading centers toward the SAN periphery; and (4) sinus pauses up to 1.9 second follow acetylcholine superfusion. We observed negligible effect of fibroblast-myocyte coupling on the period of SAN activation. We conclude that fibroblast-myocyte coupling may explain action potential initiation and propagation from the center of the SAN observed in experimental studies, while atrial load on the peripheral SAN fails to explain this fact.