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基于深度学习的磁共振成像 - (免疫)组织学检查中正常外观白质和白质高信号区域髓鞘和轴突损伤的分割

Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities.

作者信息

Solé-Guardia Gemma, Luijten Matthijs, Janssen Esther, Visch Ruben, Geenen Bram, Küsters Benno, Claassen Jurgen A H R, Litjens Geert, de Leeuw Frank-Erik, Wiesmann Maximilian, Kiliaan Amanda J

机构信息

Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands.

Department of Pathology, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands.

出版信息

Brain Pathol. 2025 Mar;35(2):e13301. doi: 10.1111/bpa.13301. Epub 2024 Aug 23.

Abstract

The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on imaging hallmarks, such as white matter hyperintensities (WMH). WMH present a heterogenous pathology, including myelin and axonal loss. Yet, these might be only the "tip of the iceberg." Imaging modalities imply that microstructural alterations underlie still normal-appearing white matter (NAWM), preceding the conversion to WMH. Unfortunately, direct pathological characterization of these microstructural alterations affecting myelinated axonal fibers in WMH, and especially NAWM, is still missing. Given that there are no treatments to significantly reduce WMH progression, it is important to extend our knowledge on pathological processes that might already be occurring within NAWM. Staining of myelin with Luxol Fast Blue, while valuable, fails to assess subtle alterations in white matter microstructure. Therefore, we aimed to quantify myelin surrounding axonal fibers and axonal- and microstructural damage in detail by combining (immuno)histochemistry with polarized light imaging (PLI). To study the extent (of early) microstructural damage from periventricular NAWM to the center of WMH, we refined current analysis techniques by using deep learning to define smaller segments of white matter, capturing increasing fluid-attenuated inversion recovery signal. Integration of (immuno)histochemistry and PLI with post-mortem imaging of the brains of individuals with hypertension and normotensive controls enables voxel-wise assessment of the pathology throughout periventricular WMH and NAWM. Myelin loss, axonal integrity, and white matter microstructural damage are not limited to WMH but already occur within NAWM. Notably, we found that axonal damage is higher in individuals with hypertension, particularly in NAWM. These findings highlight the added value of advanced segmentation techniques to visualize subtle changes occurring already in NAWM preceding WMH. By using quantitative MRI and advanced diffusion MRI, future studies may elucidate these very early mechanisms leading to neurodegeneration, which ultimately contribute to the conversion of NAWM to WMH.

摘要

痴呆的主要血管病因是脑小血管病(SVD)。其诊断依赖于影像学特征,如白质高信号(WMH)。WMH呈现出异质性病理,包括髓鞘和轴突丢失。然而,这些可能只是“冰山一角”。影像学方法表明,微观结构改变是外观仍正常的白质(NAWM)的基础,且早于其转变为WMH。不幸的是,目前仍缺乏对影响WMH中尤其是NAWM中有髓轴突纤维的这些微观结构改变的直接病理特征描述。鉴于目前尚无显著减少WMH进展的治疗方法,扩展我们对可能已在NAWM中发生的病理过程的认识非常重要。用卢氏固蓝对髓鞘进行染色虽有价值,但无法评估白质微观结构的细微改变。因此,我们旨在通过将(免疫)组织化学与偏振光成像(PLI)相结合,详细量化轴突纤维周围的髓鞘以及轴突和微观结构损伤。为了研究从脑室周围NAWM到WMH中心(早期)微观结构损伤的程度,我们通过使用深度学习来定义更小的白质区域,以捕捉逐渐增加的液体衰减反转恢复信号,从而改进了当前的分析技术。将(免疫)组织化学和PLI与高血压患者及血压正常对照者的脑尸检成像相结合,能够对整个脑室周围WMH和NAWM的病理进行逐体素评估。髓鞘丢失、轴突完整性和白质微观结构损伤不仅限于WMH,在NAWM中就已存在。值得注意的是,我们发现高血压患者的轴突损伤更严重,尤其是在NAWM中。这些发现凸显了先进分割技术在可视化WMH之前NAWM中已发生的细微变化方面的附加价值。通过使用定量MRI和先进的扩散MRI,未来的研究可能会阐明导致神经退行性变的这些非常早期的机制,这些机制最终促成了NAWM向WMH的转变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb8/11835442/51f640632c0f/BPA-35-e13301-g001.jpg

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