An Automated Workflow for Segmenting Single Adult Cardiac Cells from Large-Volume Serial Block-Face Scanning Electron Microscopy Data

Abstract

This paper presents a new algorithm to automatically segment the myofibrils, mitochondria and nuclei within single adult cardiac cells that are part of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The algorithm only requires a set of manually drawn contours that roughly demarcate the cell boundary at routine slice intervals (every 50 th , for example). The algorithm correctly classified pixels within the single cell with 97% accuracy when compared to manual segmentations. One entire cell and the partial volumes of two cells were segmented. Analysis of segmentations within these cells showed that myofibrils and mitochondria occupied 47.5% and 51.6% on average respectively, while the nuclei occupy 0.7% of the cell for which the entire volume was captured in the SBF-SEM dataset. Mitochondria clustering increased at the periphery of the nucleus region and branching points of the cardiac cell. The segmentations also showed high area fraction of mitochondria (up to 70% of the 2D image slice) in the subsarcolemmal region, whilst it was closer to 50% in the intermyofibrillar space. We finally demonstrate that our segmentations can be turned into 3D finite element meshes for cardiac cell computational physiology studies. We offer our large dataset and MATLAB implementation of the algorithm for research use at www.github.com/CellSMB/sbfsem-cardiac-cell-segmenter/. We anticipate that this timely tool will be of use to cardiac computational and experimental physiologists alike who study cardiac ultrastructure and its role in heart function.

Multiscale cardiac imaging to capture the whole heart and its internal cellular architecture, with applications to congenital heart disease

“…At the ultrastructural level, myocardial cells contain contractile units, the myofibrils, which are supplied with energy (ATP) by the mitochondria surrounding them. In a healthy, mature heart, myocardial nuclei have an ellipsoidal shape aligned with the cell long axis; myofibrils are meticulously aligned and organized along the myocardial cells; and mitochondria are densely packed around the myofibrils 16,29 . Other organelles (such as lipid droplets and glycosomes) are organized around the cell myofibrils, mitochondria and nuclei 31,32 .…”

“…Researchers have used EM techniques, including SEM, for decades to visualize the organization of organelles within cells 20,35 . In the heart, studies using EM have revealed the ultrastructural architecture of mature myocardial cells 16,31 , and elucidated the maturation of myocardial ultrastructure during embryonic development 28,36,37 . A few studies, moreover, have determined changes in ultrastructure due to pathophysiological conditions in the mature heart 13,26,27 .…”

“…While 2D EM images have been invaluable in deciphering ultrastructural features of myocardial cells and tissues, 3D images can unravel more details in the spatial organization of the ultrastructural architecture 16,26 . As an example, segmentation and visualization of the 3D data revealed that myofibril alignment was slightly different between our TOF and control hearts ( Figure 8 ).…”

“…Our multiscale procedure uses micro computed tomography (micro-CT) imaging to capture heart morphology at micrometer resolution, and scanning electron microscopy (SEM) to capture cardiac tissue ultrastructure at nanometer resolution. Current SEM technologies allow for threedimensional (3D) imaging of sub-cellular architecture, enabling reconstruction and quantification of ultrastructural features within a tissue volume 14–16 . Among 3D SEM methods, we have selected serial block-face SEM (SBF-SEM) for ultrastructural imaging, as it allows 3D imaging of relatively large volumes (sample size 40×60×40 μm 3 ).…”

Dynamic-ultrastructural cell volume (3D) correlative microscopy facilitated by intracellular fluorescent nanodiamonds as multi-modal probes

“…Considering the complex 3D organization of a cell, most of the critical 3D cellular information, especially in the z-direction, is generally under-explored. Therefore, 2D CLEM methods could be improved by employing instruments capable of performing 3D imaging (14,(23)(24)(25)(26)(27)(28)(29)(30) enabling CLEM methods correlating 3D information from both LM and EM. Combining 3D fluorescence microscopy with 3D EM would significantly improve the technical possibilities for investigating complex cellular processes across the full volume of a cell.…”