Nakano Yuka, Tanaka Kenji F, Abe Yoshifumi
Division of Brain Sciences, Institute for Advanced Medical Research, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, 160-8582, Japan.
Anat Sci Int. 2025 Jun 30. doi: 10.1007/s12565-025-00862-1.
Identifying disease-relevant and therapy-related brain regions remains a major challenge in studies using animal models of psychiatric disorders. Conventional hypothesis-driven approaches often result in limited or subjective identification of brain regions. In this study, we propose an integrative method combining unbiased whole-brain structural magnetic resonance imaging (MRI) screening and detailed histological analysis. Our methodology uses structural MRI to systematically detect volumetric changes across the entire brain, enabling the identification of target regions without relying on predefined hypotheses. Once brain regions are identified, super-resolution microscopy (SRM) is employed to determine microstructural alterations at the cellular level, focusing on neurons and glial cells within those regions. To exemplify the utility of this method, we applied it to a mouse model treated with electroconvulsive therapy (ECT), an intervention which is known to increase hippocampal volume. Our demonstration highlights the potential of this approach to systematically search for brain regions of interest, providing valuable insights and guiding future studies toward a more focused exploration of key aspects of psychiatric disorder research, both in terms of pathophysiology and therapeutic action.
在使用精神疾病动物模型的研究中，识别与疾病相关和治疗相关的脑区仍然是一项重大挑战。传统的假设驱动方法往往导致对脑区的识别有限或主观。在本研究中，我们提出了一种综合方法，将无偏全脑结构磁共振成像（MRI）筛查与详细的组织学分析相结合。我们的方法使用结构MRI系统地检测全脑的体积变化，从而能够在不依赖预定义假设的情况下识别目标区域。一旦识别出脑区，就采用超分辨率显微镜（SRM）来确定细胞水平的微观结构改变，重点关注这些区域内的神经元和胶质细胞。为了举例说明这种方法的实用性，我们将其应用于接受电休克治疗（ECT）的小鼠模型，已知这种干预会增加海马体体积。我们的演示突出了这种方法系统搜索感兴趣脑区的潜力，为精神疾病研究的关键方面提供了有价值的见解，并在病理生理学和治疗作用方面指导未来的研究进行更有针对性的探索。
