Seidel T, Edelmann J-C, Sachse F B
Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, 95 South 2000 East, Salt Lake City, UT 84112-5000, USA.
Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany.
Ann Biomed Eng. 2016 May;44(5):1436-1448. doi: 10.1007/s10439-015-1465-6. Epub 2015 Sep 23.
Microstructural characterization of cardiac tissue and its remodeling in disease is a crucial step in many basic research projects. We present a comprehensive approach for three-dimensional characterization of cardiac tissue at the submicrometer scale. We developed a compression-free mounting method as well as labeling and imaging protocols that facilitate acquisition of three-dimensional image stacks with scanning confocal microscopy. We evaluated the approach with normal and infarcted ventricular tissue. We used the acquired image stacks for segmentation, quantitative analysis and visualization of important tissue components. In contrast to conventional mounting, compression-free mounting preserved cell shapes, capillary lumens and extracellular laminas. Furthermore, the new approach and imaging protocols resulted in high signal-to-noise ratios at depths up to 60 µm. This allowed extensive analyzes revealing major differences in volume fractions and distribution of cardiomyocytes, blood vessels, fibroblasts, myofibroblasts and extracellular space in control vs. infarct border zone. Our results show that the developed approach yields comprehensive data on microstructure of cardiac tissue and its remodeling in disease. In contrast to other approaches, it allows quantitative assessment of all major tissue components. Furthermore, we suggest that the approach will provide important data for physiological models of cardiac tissue at the submicrometer scale.
心脏组织的微观结构表征及其在疾病中的重塑是许多基础研究项目中的关键步骤。我们提出了一种在亚微米尺度上对心脏组织进行三维表征的综合方法。我们开发了一种无压缩固定方法以及标记和成像方案,便于通过扫描共聚焦显微镜获取三维图像堆栈。我们用正常和梗死的心室组织评估了该方法。我们将获取的图像堆栈用于重要组织成分的分割、定量分析和可视化。与传统固定方法相比,无压缩固定保留了细胞形状、毛细血管腔和细胞外板层。此外,新方法和成像方案在深度达60 µm时产生了高信噪比。这使得能够进行广泛分析,揭示对照与梗死边缘区中心肌细胞、血管、成纤维细胞、肌成纤维细胞和细胞外空间的体积分数和分布的主要差异。我们的结果表明,所开发的方法产生了关于心脏组织微观结构及其在疾病中重塑的全面数据。与其他方法相比,它允许对所有主要组织成分进行定量评估。此外,我们认为该方法将为亚微米尺度上的心脏组织生理模型提供重要数据。