Athalye Chinmayee, Bahena Alejandra, Khandelwal Pulkit, Emrani Sheina, Trotman Winifred, Levorse Lisa M, Khodakarami Zahra, Ohm Daniel T, Teunissen-Bermeo Eric, Capp Noah, Sadaghiani Shokufeh, Arezoumandan Sanaz, Lim Sydney A, Prabhakaran Karthik, Ittyerah Ranjit, Robinson John L, Schuck Theresa, Lee Edward B, Tisdall M Dylan, Das Sandhitsu R, Wolk David A, Irwin David J, Yushkevich Paul A
Department of Bioengineering, University of Pennsylvania, Philadelphia, USA.
Department of Neurology, University of Pennsylvania, Philadelphia, USA.
Acta Neuropathol Commun. 2025 May 28;13(1):120. doi: 10.1186/s40478-025-02030-y.
Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling that may miss critical areas affected by Alzheimer's disease and related disorders. Ultra-high resolution postmortem MRI can help identify regions that fall outside the diagnostic sampling criteria for additional histopathologic evaluation. However, there are no standardized guidelines for integrating histology and MRI in a traditional brain bank. We developed a comprehensive protocol for whole hemisphere postmortem 7T MRI-guided histopathological sampling with whole-slide digital imaging and histopathological analysis, providing a reliable pipeline for high-volume brain banking in heterogeneous brain tissue. Our method uses patient-specific 3D printed molds built from postmortem MRI, allowing standardized tissue processing with a permanent spatial reference frame. To facilitate pathology-MRI association studies, we created a semi-automated MRI to histology registration pipeline and developed a quantitative pathology scoring system using weakly supervised deep learning. We validated this protocol on a cohort of 29 brains with diagnosis on the AD spectrum that revealed correlations between cortical thickness and phosphorylated tau accumulation. This pipeline has broad applicability across neuropathological research and brain banking, facilitating large-scale studies that integrate histology with neuroimaging. The innovations presented here provide a scalable and reproducible approach to studying postmortem brain pathology, with implications for advancing diagnostic and therapeutic strategies for Alzheimer's disease and related disorders.
尸检神经病理学检查虽是诊断神经退行性疾病的金标准，但往往依赖有限的区域采样，这可能会遗漏受阿尔茨海默病及相关疾病影响的关键区域。超高分辨率尸检MRI有助于识别超出诊断采样标准的区域，以便进行额外的组织病理学评估。然而，在传统脑库中，尚无将组织学与MRI相结合的标准化指南。我们开发了一种全面的方案，用于在7T尸检MRI引导下对全脑半球进行组织病理学采样，并进行全玻片数字成像和组织病理学分析，为异质性脑组织的大容量脑库提供了可靠的流程。我们的方法使用根据尸检MRI构建的患者特异性3D打印模具，实现了具有永久空间参考框架的标准化组织处理。为促进病理学与MRI关联研究，我们创建了一个半自动的MRI到组织学配准流程，并使用弱监督深度学习开发了一种定量病理学评分系统。我们在一组29个经阿尔茨海默病谱系诊断的大脑上验证了该方案，结果揭示了皮质厚度与磷酸化tau蛋白积累之间的相关性。该流程在神经病理学研究和脑库中具有广泛的适用性，有助于将组织学与神经影像学相结合的大规模研究。本文介绍的创新成果提供了一种可扩展且可重复的方法来研究尸检脑病理学，对推进阿尔茨海默病及相关疾病的诊断和治疗策略具有重要意义。
