局部自由水扩散与神经炎症的关系比与神经退行性变的关系更为密切。

Regional free-water diffusion is more strongly related to neuroinflammation than neurodegeneration.

作者信息

Sumra Vishaal, Hadian Mohsen, Dilliott Allison A, Farhan Sali M K, Frank Andrew R, Lang Anthony E, Roberts Angela C, Troyer Angela, Arnott Stephen R, Marras Connie, Tang-Wai David F, Finger Elizabeth, Rogaeva Ekaterina, Orange Joseph B, Ramirez Joel, Zinman Lorne, Binns Malcolm, Borrie Michael, Freedman Morris, Ozzoude Miracle, Bartha Robert, Swartz Richard H, Munoz David, Masellis Mario, Black Sandra E, Dixon Roger A, Dowlatshahi Dar, Grimes David, Hassan Ayman, Hegele Robert A, Kumar Sanjeev, Pasternak Stephen, Pollock Bruce, Rajji Tarek, Sahlas Demetrios, Saposnik Gustavo, Tartaglia Maria Carmela

机构信息

Institute of Medical Science, University of Toronto, Medical Sciences Building, 1 King's College Cir Suite 2374, Toronto, ON, M5S 1A8, Canada.

Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Medical Sciences Building, 1 King's College Cir Suite 2374, Toronto, ON, M5S 1A8, Canada.

出版信息

J Neurol. 2025 Jun 25;272(7):478. doi: 10.1007/s00415-025-13201-1.

DOI:10.1007/s00415-025-13201-1

PMID:40560468

Abstract

INTRODUCTION

Recent research has suggested that neuroinflammation may be important in the pathogenesis of neurodegenerative diseases. Free-water diffusion (FWD) has been proposed as a non-invasive neuroimaging-based biomarker for neuroinflammation.

METHODS

Free-water maps were generated using diffusion MRI data in 367 patients from the Ontario Neurodegenerative Disease Research Initiative (108 Alzheimer's Disease/Mild Cognitive Impairment, 42 Frontotemporal Dementia, 37 Amyotrophic Lateral Sclerosis, 123 Parkinson's Disease, and 58 vascular disease-related Cognitive Impairment). The ability of FWD to predict neuroinflammation and neurodegeneration from biofluids was estimated using plasma glial fibrillary-associated protein (GFAP) and neurofilament light chain (NfL), respectively.

RESULTS

Recursive Feature Elimination (RFE) performed the strongest out of all feature selection algorithms used and revealed regional specificity for areas that are the most important features for predicting GFAP over NfL concentration. Deep learning models using selected features and demographic information revealed better prediction of GFAP over NfL.

DISCUSSION

Based on feature selection and deep learning methods, FWD was found to be more strongly related to GFAP concentration (measure of astrogliosis) over NfL (measure of neuro-axonal damage), across neurodegenerative disease groups, in terms of predictive performance. Non-invasive markers of neurodegeneration such as MRI structural imaging that can reveal neurodegeneration already exist, while non-invasive markers of neuroinflammation are not available. Our results support the use of FWD as a non-invasive neuroimaging-based biomarker for neuroinflammation.

摘要

引言

近期研究表明，神经炎症可能在神经退行性疾病的发病机制中起重要作用。自由水扩散（FWD）已被提议作为一种基于神经影像学的非侵入性神经炎症生物标志物。

方法

利用来自安大略神经退行性疾病研究倡议的367例患者的扩散磁共振成像数据生成自由水图（108例阿尔茨海默病/轻度认知障碍、42例额颞叶痴呆、37例肌萎缩侧索硬化、123例帕金森病和58例血管疾病相关认知障碍）。分别使用血浆胶质纤维酸性蛋白（GFAP）和神经丝轻链（NfL）评估FWD预测生物流体中神经炎症和神经退行性变的能力。

结果

在所有使用的特征选择算法中，递归特征消除（RFE）表现最强，并揭示了预测GFAP浓度高于NfL浓度时最重要特征所在区域的特异性。使用选定特征和人口统计学信息的深度学习模型显示，对GFAP的预测优于NfL。

讨论

基于特征选择和深度学习方法，就预测性能而言，发现在神经退行性疾病组中，FWD与GFAP浓度（星形胶质细胞增生的指标）的相关性比与NfL（神经轴突损伤的指标）更强。已经存在可以揭示神经退行性变的神经退行性变非侵入性标志物，如MRI结构成像，而神经炎症的非侵入性标志物尚不存在。我们的结果支持将FWD用作基于神经影像学的非侵入性神经炎症生物标志物。