Microheterogeneity-induced conduction slowing and wavefront collisions govern macroscopic conduction behavior: A computational and experimental study

<div><p>The incidence of cardiac arrhythmias is known to be associated with tissue heterogeneities including fibrosis. However, the impact of microscopic structural heterogeneities on conduction in excitable tissues remains poorly understood. In this study, we investigated how acellular microheterogeneities affect macroscopic conduction under conditions of normal and reduced excitability by utilizing a novel platform of paired <i>in vitro</i> and <i>in silico</i> studies to examine the mechanisms of conduction. Regular patterns of nonconductive micro-obstacles were created in confluent monolayers of the previously described engineered-excitable Ex293 cell line. Increasing the relative ratio of obstacle size to intra-obstacle strand width resulted in significant conduction slowing up to 23.6% and a significant increase in wavefront curvature anisotropy, a measure of spatial variation in wavefront shape. Changes in bulk electrical conductivity and in path tortuosity were insufficient to explain these observed macroscopic changes. Rather, microscale behaviors including local conduction slowing due to microscale branching, and conduction acceleration due to wavefront merging were shown to contribute to macroscopic phenomena. Conditions of reduced excitability led to further conduction slowing and a reversal of wavefront curvature anisotropy due to spatially non-uniform effects on microscopic slowing and acceleration. This unique experimental and computation platform provided critical mechanistic insights in the impact of microscopic heterogeneities on macroscopic conduction, pertinent to settings of fibrotic heart disease.</p></div

Path tortuosity does not fully explain heterogeneity-induced conduction slowing.

<p>(a-b) The automata model, which considers only conduction path length and does not reflect microscopic conduction variation, approximately captures macroscopic conduction velocity (a; mean ± se) but exhibits substantially more curvature anisotropy compared to experimental monolayers and the biophysical model (b; mean ± sd). (c) Activation isochrones are overlaid to highlight the difference in shape between the biophysical model (red) and the automata model (blue). (d). Error in the automata model, compared to the biophysical model, is highest along the principal axes of conductions (black arrows), and lowest along the bisecting diagonal (red arrow), suggesting spatial variation in microscale conduction velocity.</p

Micropatterning via photolithography resulted in cultured monolayers of Ex293 cells around acellular regions that varied in size and spacing.

<p>(a) Homogenous monolayer; obstacle-to-strand ratio: 0; (b) 150 μm x 150 μm obstacles, separated by 100 μm strands; obstacle-to-strand ratio: 1.5; (c) 700 μm x 700 μm obstacles, separated by 100 μm strands; obstacle-to-strand ratio: 7.0 (scale bar = 150 μm); (d) Schematic depiction of tissue obstacle structure; (e) Obstacle and strand widths, and obstacle percent density, for each degree of heterogeneity.</p

Effects of microscopic heterogeneity on macroscopic conduction.

<p>(a) Increasing degree of heterogeneity, as characterized by the obstacle width to strand width ratio, leads to slowing of macroscopic conduction (mean ± se; n = 13–68 monolayers; F(6,217) = 11.53. p < 0.0001; Asterisk indicates significant difference from homogenous case, p < 0.05; values represent average CV across each individual monolayer). (b). Shortening of action potential duration is observed at high obstacle-to-strand ratios (mean ± se; F(6, 217) = 42.7. p < 0.001). (c-e) Macroscopic activation maps becomes increasingly anisotropic as obstacle-to-strand ratio increases from 0 (c) to 1.5 (d) to 7.0 (e). Directional conduction velocities are as indicated. Average conduction velocities across these representative monolayers are 21.28 cm/s (c), 18.56 cm/s (d) and 16.79 cm/s (e). Scale bar = 5 mm; Activation isochrone lines at 8 ms spacing. (f) Quantified anisotropy of 1 indicates isotropic conduction while √2/2 indicates a diamond shape isochrone (mean ± sd; n = 10–15 monolayers; F(6,72) = 42.5. p < 0.001; * and # indicate significant difference from all lower obstacle-to-strand ratios, p < 0.05).</p

Conduction acceleration due to wavefront collision.

<p>(a) At intersection points along the diagonal axes, the simultaneous arrival of two wavefronts leads to a non-annihilating wavefront collision that causes a local increase in conduction velocity. This local speeding, up to 67.3% In tissues with an obstacle-to-strand ratio of 5, leads to an acceleration of activation across the intersection site. (b) The magnitude of acceleration is approximately 0.15 ms for all obstacle-to-strand ratios above 1.5. (c) The safety factor of conduction rises sharply at the site of wavefront collision at the center of the intersection; reduced safety factor is observed near the corners of the intersection.</p

Conduction during reduced excitability.

<p>(a) Reduction of excitability via sodium channel blockade with TTX in experimental monolayer results in a significant reduction in conduction velocity (n = 3–6 monolayers; mean ± se; main effect of TTX: F(1,46) = 24.02. p < 0.001; main effect of ratio: F(6,46) = 3.58. p = 0.007; interaction effect: F(6,46) = 0.38. p > 0.1). Conduction could not be reliably sustained at an obstacle-to-strand ratio of 7 and was meandering and irregular with numerous wavebreaks at an obstacle-to-strand ratio of 5. Simulated conduction with reduced excitability replicates experimental behavior at obstacle-to-strand ratios of up to 1.5, but exhibits conduction block at a ratio of 3.0 (n = 10 simulated monolayers per case; mean ± se) (b) Reduced excitability resulted in a reversal of the isochrones flattening observed at large obstacle-to-strand ratios. (n = 3–10 monolayers; mean ± sd; main effect of TTX: F(1,82) = 2.77. p = 0.101; main effect of ratio: F(4,82) = 5.21. p = 0.001; interaction effect: F(4,82) = 4.75. p < 0.002; * indicates significant difference between experimental control and experimental TTX, p < 0.05). Qualitatively similar changes in wavefront curvature are observed in simulations. (c-e). These changes can be attributed to globally reduced strand conduction velocity (c), in conjunction with increased activation delay at branch points along the principal axes (d) and minimal change in collision-induced acceleration along the diagonal (e).</p

Endocardial collagen layer masks RF-induced damage to atrial muscle below.

<p>A. Left: a cartoon of RF catheter ablating atrial endocardial surface. Right: an example of ablated human left atrium after TTC-staining. By peeling off the collagen layer, RF damage to the muscle below can be readily seen (ablated tissue shows as pale areas devoid of red triphenylformazan dye). B. Unstained endocardial surface of human left atrium with multiple RF lesions under either room light or UV illumination. Note the limited contrast between lesion sites and unablated, healthy tissue. C. Histology of left atrial wall shows layers of atrial muscle sandwiched between endocardial collagen layer and epicardial fat. A close-up of endocardial layers reveals interwoven fibers of collagen (pink) and elastin (black).</p

HSI vs histological assessment of lesion size.

<p>A. A string of four RF lesions shown as both composite and component HSI image. To the right is the same tissue (before TTC-staining) cross-sectioned through the centers of the lesions. B. Top left panel shows grayscale HSI lesion component image. Bottom left panel is a cross-section of the same lesions after TTC-staining. Dotted lines show measurements of the lesion diameters. C. Graph illustrates the correlation between lesion diameter values derived from histology and HSI lesion component images. D. The intensity plot of HSI lesion component image taken across dotted blue line shown in B.</p

Spectral shift vs lesion depth.

<p>This set of experiments was conducted in freshly excised bovine left atria. Several ROIs were selected across each lesion to extract their spectral profiles from HSI hyperstack. Lesion depth at each ROI was then measured. Graph on the right shows the relationship between spectral shift at 580nm and the depth of the lesion (56 ROIs from 8 different lesions, each lesion represented by a different color).</p

Seeing the Invisible: Revealing Atrial Ablation Lesions Using Hyperspectral Imaging Approach

<div><p>Background</p><p>Currently, there are limited means for high-resolution monitoring of tissue injury during radiofrequency ablation procedures.</p><p>Objective</p><p>To develop the next generation of visualization catheters that can reveal irreversible atrial muscle damage caused by ablation and identify viability gaps between the lesions.</p><p>Methods</p><p>Radiofrequency lesions were placed on the endocardial surfaces of excised human and bovine atria and left ventricles of blood perfused rat hearts. Tissue was illuminated with 365nm light and a series of images were acquired from individual spectral bands within 420-720nm range. By extracting spectral profiles of individual pixels and spectral unmixing, the relative contribution of ablated and unablated spectra to each pixel was then displayed. Results of spectral unmixing were compared to lesion pathology.</p><p>Results</p><p>RF ablation caused significant changes in the tissue autofluorescence profile. The magnitude of these spectral changes in human left atrium was relatively small (< 10% of peak fluorescence value), yet highly significant. Spectral unmixing of hyperspectral datasets enabled high spatial resolution, in-situ delineation of radiofrequency lesion boundaries without the need for exogenous markers. Lesion dimensions derived from hyperspectral imaging approach strongly correlated with histological outcomes. Presence of blood within the myocardium decreased the amplitude of the autofluorescence spectra while having minimal effect on their overall shapes. As a result, the ability of hyperspectral imaging to delineate ablation lesions in vivo was not affected.</p><p>Conclusions</p><p>Hyperspectral imaging greatly increases the contrast between ablated and unablated tissue enabling visualization of viability gaps at clinically relevant locations. Data supports the possibility for developing percutaneous hyperspectral catheters for high-resolution ablation guidance.</p></div