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肥厚性心肌病三维微结构重构的深度学习分析
作者:小柯机器人 发布时间:2026/1/16 14:08:10


哈佛医学院Jonathan G. Seidman小组研制了肥厚性心肌病三维微结构重构的深度学习分析。相关论文发表在2026年1月15日出版的《科学》杂志上。

课题组人员开发了CaMVIA-3D,这是一种深度学习容积成像和分析管道,用于表征心脏微结构。对HCM心脏组织的分析显示,心肌细胞体积、形态和细胞外体积的基因型特异性差异,致病变异表现出更大的同心细胞肥大和紊乱,变异阴性病例表现出主要的纤维化。猪HCM模型的纵向分析显示心肌细胞肥大之前早发性纤维化。整合转录组学和形态学变化,课题组研究人员确定了与细胞和细胞外重塑相关的基因。这些发现定义了HCM中基因型特异性的微观结构差异,为改进诊断和靶向治疗提供了见解。

据介绍,肥厚性心肌病(HCM)是一种遗传性心脏病,其定义为原因不明的心壁增厚,是世界范围内猝死的主要原因。然而,左心室肥厚背后的心脏组织的三维组织仍然知之甚少。

附:英文原文

Title: Deep-learning analysis of 3D microarchitectural remodeling in hypertrophic cardiomyopathy

Author: Eric Q. Wei, Martin Beyer, Kemar J. Brown, Alexander J. Bansbach, Joshua M. Gorham, Barbara McDonough, Huachen Chen, Mobin Khoramjoo, Anran Zhang, Brian Bishop, Ferhaan Ahmad, Carlos del Rio, Ching-Pin Chang, David M. Ryba, Sharlene M. Day, Diane Fatkin, Gavin Y. Oudit, Christine E. Seidman, Jonathan G. Seidman

Issue&Volume: 2026-01-15

Abstract: Hypertrophic cardiomyopathy (HCM), a genetic heart disease defined by unexplained cardiac wall thickening, is a leading cause of sudden death worldwide. However, the three-dimensional organization of cardiac tissue underlying left ventricular hypertrophy remains poorly understood. We developed CaMVIA-3D, a deep-learning volumetric imaging and analysis pipeline to characterize cardiac microarchitecture. Analysis of tissues from HCM hearts revealed genotype-specific differences in cardiomyocyte volume, morphology, and extracellular volume, with pathogenic variants exhibiting greater concentric cellular hypertrophy and disarray and variant-negative cases showing predominant fibrosis. Longitudinal profiling of a pig HCM model revealed early-onset fibrosis preceding cardiomyocyte hypertrophy. Integrating transcriptomic and morphologic changes, we identified genes associated with cellular and extracellular remodeling. These findings define genotype-specific microstructural differences in HCM, offering insights to improve diagnostics and targeted therapies.

DOI: ady6443

Source: https://www.science.org/doi/10.1126/science.ady6443

 

期刊信息
Science:《科学》,创刊于1880年。隶属于美国科学促进会,最新IF:63.714