Computational modeling is an important tool to advance our knowledge on cardiac diseases and their underlying mechanisms. Computational models of conduction in cardiac tissues require identification of parameters. Our knowledge on these parameters is limited, especially for diseased tissues. Here, we assessed and quantified parameters for computational modeling of conduction in cardiac tissues. We used a rabbit model of myocardial infarction (MI) and an imaging-based approach to derive the parameters. Left ventricular tissue samples were obtained from fixed control hearts (animals: 5) and infarcted hearts (animals: 6) within 200 μm (region 1), 250–750 μm (region 2) and 1,000–1,250 μm (region 3) of the MI border. We assessed extracellular space, fibroblasts, smooth muscle cells, nuclei and gap junctions by a multi-label staining protocol. With confocal microscopy we acquired three-dimensional (3D) image stacks with a voxel size of 200 × 200 × 200 nm. Image segmentation yielded 3D reconstructions of tissue microstructure, which were used to numerically derive extracellular conductivity tensors. Volume fractions of myocyte, extracellular, interlaminar cleft, vessel and fibroblast domains in control were (in %) 65.03 ± 3.60, 24.68 ± 3.05, 3.95 ± 4.84, 7.71 ± 2.15, and 2.48 ± 1.11, respectively. Volume fractions in regions 1 and 2 were different for myocyte, myofibroblast, vessel, and extracellular domains. Fibrosis, defined as increase in fibrotic tissue constituents, was (in %) 21.21 ± 1.73, 16.90 ± 9.86, and 3.58 ± 8.64 in MI regions 1, 2, and 3, respectively. For control tissues, image-based computation of longitudinal, transverse and normal extracellular conductivity yielded (in S/m) 0.36 ± 0.11, 0.17 ± 0.07, and 0.1 ± 0.06, respectively. Conductivities were markedly increased in regions 1 (+75, +171, and +100%), 2 (+53, +165, and +80%), and 3 (+42, +141, and +60%). Volume fractions of the extracellular space including interlaminar clefts strongly correlated with conductivities in control and MI hearts. Our study provides novel quantitative data for computational modeling of conduction in normal and MI hearts. Notably, our study introduces comprehensive statistical information on tissue composition and extracellular conductivities on a microscopic scale in the MI border zone. We suggest that the presented data fill a significant gap in modeling parameters and extend our foundation for computational modeling of cardiac conduction.

The transverse tubular system (t-system) of ventricular cardiomyocytes is essential for efficient excitation-contraction coupling. In cardiac diseases, such as heart failure, remodeling of the t-system contributes to reduced cardiac contractility. However, mechanisms of t-system remodeling are incompletely understood. Prior studies suggested an association with altered cardiac biomechanics and gene expression in disease. Since fibrosis may alter tissue biomechanics, we investigated the local microscopic association of t-system remodeling with fibrosis in a rabbit model of myocardial infarction (MI). Biopsies were taken from the MI border zone of 6 infarcted hearts and from 6 control hearts. Using confocal microscopy and automated image analysis, we quantified t-system integrity (ITT) and the local fraction of extracellular matrix (fECM). In control, fECM was 18±0.3%. ITT was high and homogeneous (0.07±0.006), and did not correlate with fECM (R2=0.05±0.02). The MI border zone exhibited increased fECM within 3mm from the infarct scar (30±3.5%, p<0.01 vs control), indicating fibrosis. Myocytes in the MI border zone exhibited significant t-system remodeling, with dilated, sheet-like components, resulting in low ITT (0.03±0.008, p<0.001 vs control). While both fECM and t-system remodeling decreased with infarct distance, ITT correlated better with decreasing fECM (R2=0.44) than with infarct distance (R2=0.24, p<0.05). Our results show that t-system remodeling in the rabbit MI border zone resembles a phenotype previously described in human heart failure. T-system remodeling correlated with the amount of local fibrosis, which is known to stiffen cardiac tissue, but was not found in regions without fibrosis. Thus, locally altered tissue mechanics may contribute to t-system remodeling.

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In mammalian ventricular cardiomyocytes, invaginations of the surface membrane form the transverse tubular system (T-system), which consists of transverse tubules (TTs) that align with sarcomeres and Z-lines as well as longitudinal tubules (LTs) that are present between Z-lines in some species. In many cardiac disease etiologies, the T-system is perturbed, which is believed to promote spatially heterogeneous, dyssynchronous Ca 2þ release and inefficient contraction. In general, T-system characterization approaches have been directed primarily at isolated cells and do not detect subcellular T-system heterogeneity. Here, we present MatchedMyo, a matched-filter-based algorithm for subcellular T-system characterization in isolated cardiomyocytes and millimeter-scale myocardial sections. The algorithm utilizes ''filters'' representative of TTs, LTs, and T-system absence. Application of the algorithm to cardiomyocytes isolated from rat disease models of myocardial infarction (MI), dilated cardiomyopathy induced via aortic banding, and sham surgery confirmed and quantified heterogeneous T-system structure and remodeling. Cardiomyocytes from post-MI hearts exhibited increasing T-system disarray as proximity to the infarct increased. We found significant (p < 0.05, Welch's t-test) increases in LT density within cardiomyocytes proximal to the infarct (12 5 3%, data reported as mean 5 SD, n ¼ 3) versus sham (4 5 2%, n ¼ 5), but not distal to the infarct (7 5 1%, n ¼ 3). The algorithm also detected decreases in TTs within 5 of the myocyte minor axis for isolated aortic banding (36 5 9%, n ¼ 3) and MI cardiomyocytes located intermediate (37 5 4%, n ¼ 3) and proximal (34 5 4%, n ¼ 3) to the infarct versus sham (57 5 12%, n ¼ 5). Application of bootstrapping to rabbit MI tissue revealed distal sections comprised 18.9 5 1.0% TTs, whereas proximal sections comprised 10.1 5 0.8% TTs (p < 0.05), a 46.6% decrease. The matched-filter approach therefore provides a robust and scalable technique for T-system characterization from isolated cells through millimeter-scale myocardial sections.

In healthy tissue of various mammals, transverse tubules (TTs) are found in a strongly conserved, striated pattern that aligns with the sarcomere network at the z-lines. In a variety of etiologies, this network is perturbed, which is believed to correlate with ineffective, dyssynchronous Ca 2+ release and subsequent contraction. Confocal microscopy has become the de facto standard for characterization of TT networks, for which several algorithms for detecting and classifying these subcellular structures have emerged. However, to our knowledge, such algorithms are irrespective of subcellular variations in TT angle and are restricted in application to single isolated myocytes. Here we present a matched filter-based algorithm to characterize TT structure at a subcellular-level, in single cardiomyocytes through millimeter-scale tissue preparations. The algorithm utilizes 'filters' representative of intact TT structure, longitudinal remodeling, and TT absence. Application of the algorithm to cardiomyocytes isolated from SHAM, myocardial infarction (MI), and thoracic aortic banding (TAB) animal models confirm and quantify locally-heterogeneous TT structure and structural remodeling. We find significant (p < 0.05) increases in longitudinal remodeling within myocytes intermediate and proximal to an infarct (10 ± 2% and 12 ± 3% compared to 4 ± 2% in SHAM) as well as decreases in tubule striations within 5• of myocyte minor axis for TAB (36 ± 9%), intermediate (37 ± 4%), and proximal (34 ± 4%) MI myocytes compared to SHAM myocytes (57 ± 12%). Given the reliance of the matched filter approach on images representative of subcellular features, we anticipate the algorithm is generalizable to wide-ranging imaging applications.