期刊
IEEE TRANSACTIONS ON MEDICAL IMAGING
卷 32, 期 5, 页码 862-872出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2013.2240693
关键词
Computational analysis of cardiac tissue; confocal microscopy; fibroblasts; gap junctions; myocardial infarction
类别
资金
- Richard A. and Nora Eccles Fund for Cardiovascular Research
- Nora Eccles Treadwell Foundation
- National Institutes of Health [R01 HL094464, R01 HL70828]
- German National Academic Foundation
- German Academic Exchange Service
Electrophysiological modeling of cardiac tissue is commonly based on functional and structural properties measured in experiments. Our knowledge of these properties is incomplete, in particular their remodeling in disease. Here, we introduce a methodology for quantitative tissue characterization based on fluorescent labeling, 3-D scanning confocal microscopy, image processing and reconstruction of tissue micro-structure at sub-micrometer resolution. We applied this methodology to normal rabbit ventricular tissue and tissue from hearts with myocardial infarction. Our analysis revealed that the volume fraction of fibroblasts increased from 4.83 +/- 0.42% (mean +/- standard deviation) in normal tissue up to 6.51 +/- 0.38% in myocardium from infarcted hearts. The myocyte volume fraction decreased from 76.20 +/- 9.89% in normal to 73.48 +/- 8.02% adjacent to the infarct. Numerical field calculations on 3-D reconstructions of the extracellular space yielded an extracellular longitudinal conductivity of 0.264 +/- 0.082 S/m with an anisotropy ratio of 2.095 +/- 1.11 in normal tissue. Adjacent to the infarct, the longitudinal conductivity increased up to 0.400 +/- 0.051 S/m, but the anisotropy ratio decreased to 1.295 +/- 0.09. Our study indicates an increased density of gap junctions proximal to both fibroblasts and myocytes in infarcted versus normal tissue, supporting previous hypotheses of electrical coupling of fibroblasts and myocytes in infarcted hearts. We suggest that the presented methodology provides an important contribution to modeling normal and diseased tissue. Applications of the methodology include the clinical characterization of disease-associated remodeling.
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