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

IF 5.8 2区 医学 Q1 CLINICAL NEUROLOGY Brain Pathology Pub Date : 2024-08-23 DOI:10.1111/bpa.13301
Gemma Solé-Guardia, Matthijs Luijten, Esther Janssen, Ruben Visch, Bram Geenen, Benno Küsters, Jurgen A H R Claassen, Geert Litjens, Frank-Erik de Leeuw, Maximilian Wiesmann, Amanda J Kiliaan
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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.

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基于深度学习的磁共振成像-(免疫)组织学检查正常外观白质和白质高密度中的髓鞘和轴突损伤的分割。
痴呆症的主要血管性病因是脑小血管病(SVD)。其诊断依赖于影像学特征,如白质高密度(WMH)。WMH 呈异质性病理,包括髓鞘和轴索缺失。然而,这些可能只是 "冰山一角"。成像模式表明,微结构改变是外观正常的白质(NAWM)转变为 WMH 之前的基础。遗憾的是,对这些影响 WMH(尤其是 NAWM)中有髓轴索纤维的微结构改变的直接病理特征描述仍然缺失。鉴于目前还没有能明显减少 WMH 进展的治疗方法,我们有必要进一步了解 NAWM 中可能已经发生的病理过程。用卢克索快速蓝对髓鞘进行染色虽然很有价值,但却无法评估白质微观结构的细微变化。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结构损伤。为了研究从室管膜周围NAWM到WMH中心的(早期)微结构损伤程度,我们改进了当前的分析技术,利用深度学习来定义更小的白质片段,捕捉不断增加的液体衰减反转恢复信号。将(免疫)组织化学和 PLI 与高血压患者和正常血压对照组的脑部死后成像相结合,可以对整个脑室周围 WMH 和 NAWM 的病理学进行体素评估。髓鞘缺失、轴突完整性和白质微结构损伤并不局限于WMH,在NAWM中也有发生。值得注意的是,我们发现高血压患者的轴突损伤程度更高,尤其是在 NAWM 中。这些发现凸显了高级分割技术的附加价值,它可以观察到 WMH 之前 NAWM 中已经发生的微妙变化。通过使用定量 MRI 和先进的弥散 MRI,未来的研究可能会阐明这些导致神经变性的早期机制,这些机制最终会导致 NAWM 转化为 WMH。
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来源期刊
Brain Pathology
Brain Pathology 医学-病理学
CiteScore
13.20
自引率
3.10%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Brain Pathology is the journal of choice for biomedical scientists investigating diseases of the nervous system. The official journal of the International Society of Neuropathology, Brain Pathology is a peer-reviewed quarterly publication that includes original research, review articles and symposia focuses on the pathogenesis of neurological disease.
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