Quantitative descriptions of extended volume cardiac tissue architecture from multiple large hearts Background The arrangement of cardiac cells into strand and sheet-like structures within the heart wall, confers important electrical properties onto heart tissue. Unraveling cardiomyocyte architecture in both healthy and diseased hearts is fundamental to understanding the mechanisms generating normal rhythm and arrhythmia. We present multiple quantitative measures of tissue architecture that give a deeper understanding of cardiac structures and their spatial variation than previously possible. Mark L. Trew, Bryan J. Caldwell, Bruce H. Smaill, The University of Auckland, New Zealand Methods • Extended volume serial imaging (Fig 1). Five normal pig hearts were fixed, wax embedded and serially block face imaged with Toluidine blue stain. Resolution was 8.332 m2 in plane. • Correcting processing artifact (Fig 1). Non-linear corrections matched 3D MRI and serial image fudicial markers. • Post processing and segmentation of tissue/non-tissue (Figs 1, 2). Piecewise image histogram equalization algorithm was used. Segmentation to tissue/non-tissue masks used piecewise thresholding with parameters trained on key images (Figs 1F, 1G). • Myofiber orientations. Eigen-analysis of structure tensor computed with 1D FFT. • Laminar cleft skeletonization (Fig 3). 2D FE templates matched on sub-images (Fig 1H). • Tissue connectivity descriptions (Fig 4). Custom shell weight summation filter was applied to segmented images (Fig 1H) with 1D FFT. Results & Discussion • Transmural image dimension: 1900±283 pixels; other dimensions: 2325±222 pixels; volumes: 7.6-12.6 cm3. • Subregions of segmented corrected images (Fig 1G) were rendered for visualization (Fig 5). • Laminar cleft skeletonization (Fig 1H) were rendered in subregions of 3 hearts and showed differing distributions of small, moderate and large clefts (Fig 6). • Myofiber orientations from 3D corrected intensity images (Fig 1F) showed expected transmural fiber rotation, but heart-to-heart variability (Fig 7). • Over all tissue samples, structural measure such as laminar cleft area, laminar cleft angle of attack (1 is orthogonal to epicardium and 0 is parallel) and tissue connectivity varied smoothly across the heart wall (Fig 8). • These data were used to construct one comprehensive model of electrical activation in pig heart tissue sample (Fig 9). Model showed impact of structural features on the spread of electrical activation. • These are the first comprehensive quantitative digital descriptions of myocardial architecture in extended LV tissue segments from multiple large hearts. • Analysis tools are designed to work with very large image sets. • These data and descriptions are paired with experimental recordings for function-structure analysis. • The analysis tools described here can also be applied to other imaging modalities used to build 3D image sets. Other modalities include: high-field MRI, extended volume confocal microscopy and CT. • Future work includes completing descriptions of intramural vessel structures. Conclusion Cardiac tissue images can be quantitatively analyzed for structures that affect the development of electrical activation and, hence, the behavior of the heart. Variation in structural measures can be used to interpret experimental observations and inform computer activation models. A B C A B C D E A B 1.3 0 C Figure 2 (left). Correcting for image to image intensity variations. A. Sub-image stacks through the principle imaging stack were piecewise histogram corrected. B. Sub-images overlapped and were linearly recombined. C. Key images with the largest local intensity variation provided target histograms for piecewise intensity equalization through the image stack. Figure 3 (left). Laminar cleft skeletonization. A. 3D rendered mask of cleft space – 8x1x1 mm3. The left end lies toward the epicardium. B. Cleft space skeletonized as 2D finite elements. C. Cleft spa