Vishaal Sumra, Mohsen Hadian, Allison A Dilliott, Sali M K Farhan, Andrew R Frank, Anthony E Lang, Angela C Roberts, Angela Troyer, Stephen R Arnott, Connie Marras, David F Tang-Wai, Elizabeth Finger, Ekaterina Rogaeva, Joseph B Orange, Joel Ramirez, Lorne Zinman, Malcolm Binns, Michael Borrie, Morris Freedman, Miracle Ozzoude, Robert Bartha, Richard H Swartz, David Munoz, Mario Masellis, Sandra E Black, Roger A Dixon, Dar Dowlatshahi, David Grimes, Ayman Hassan, Robert A Hegele, Sanjeev Kumar, Stephen Pasternak, Bruce Pollock, Tarek Rajji, Demetrios Sahlas, Gustavo Saposnik, Maria Carmela Tartaglia
{"title":"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强。","authors":"Vishaal Sumra, Mohsen Hadian, Allison A Dilliott, Sali M K Farhan, Andrew R Frank, Anthony E Lang, Angela C Roberts, Angela Troyer, Stephen R Arnott, Connie Marras, David F Tang-Wai, Elizabeth Finger, Ekaterina Rogaeva, Joseph B Orange, Joel Ramirez, Lorne Zinman, Malcolm Binns, Michael Borrie, Morris Freedman, Miracle Ozzoude, Robert Bartha, Richard H Swartz, David Munoz, Mario Masellis, Sandra E Black, Roger A Dixon, Dar Dowlatshahi, David Grimes, Ayman Hassan, Robert A Hegele, Sanjeev Kumar, Stephen Pasternak, Bruce Pollock, Tarek Rajji, Demetrios Sahlas, Gustavo Saposnik, Maria Carmela Tartaglia","doi":"10.1007/s00415-025-13201-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion: </strong>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.</p>","PeriodicalId":16558,"journal":{"name":"Journal of Neurology","volume":"272 7","pages":"478"},"PeriodicalIF":4.8000,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Regional free-water diffusion is more strongly related to neuroinflammation than neurodegeneration.\",\"authors\":\"Vishaal Sumra, Mohsen Hadian, Allison A Dilliott, Sali M K Farhan, Andrew R Frank, Anthony E Lang, Angela C Roberts, Angela Troyer, Stephen R Arnott, Connie Marras, David F Tang-Wai, Elizabeth Finger, Ekaterina Rogaeva, Joseph B Orange, Joel Ramirez, Lorne Zinman, Malcolm Binns, Michael Borrie, Morris Freedman, Miracle Ozzoude, Robert Bartha, Richard H Swartz, David Munoz, Mario Masellis, Sandra E Black, Roger A Dixon, Dar Dowlatshahi, David Grimes, Ayman Hassan, Robert A Hegele, Sanjeev Kumar, Stephen Pasternak, Bruce Pollock, Tarek Rajji, Demetrios Sahlas, Gustavo Saposnik, Maria Carmela Tartaglia\",\"doi\":\"10.1007/s00415-025-13201-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion: </strong>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.</p>\",\"PeriodicalId\":16558,\"journal\":{\"name\":\"Journal of Neurology\",\"volume\":\"272 7\",\"pages\":\"478\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2025-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Neurology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00415-025-13201-1\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neurology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00415-025-13201-1","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Regional free-water diffusion is more strongly related to neuroinflammation than neurodegeneration.
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.
期刊介绍:
The Journal of Neurology is an international peer-reviewed journal which provides a source for publishing original communications and reviews on clinical neurology covering the whole field.
In addition, Letters to the Editors serve as a forum for clinical cases and the exchange of ideas which highlight important new findings. A section on Neurological progress serves to summarise the major findings in certain fields of neurology. Commentaries on new developments in clinical neuroscience, which may be commissioned or submitted, are published as editorials.
Every neurologist interested in the current diagnosis and treatment of neurological disorders needs access to the information contained in this valuable journal.