Ruben P Dörfel, Brice Ozenne, Melanie Ganz, Jonas E Svensson, Pontus Plavén-Sigray
{"title":"Prediction of brain age using structural magnetic resonance imaging: A comparison of clinical validity of publicly available software packages.","authors":"Ruben P Dörfel, Brice Ozenne, Melanie Ganz, Jonas E Svensson, Pontus Plavén-Sigray","doi":"10.1101/2025.03.13.25323902","DOIUrl":null,"url":null,"abstract":"<p><p>Brain age estimated from structural magnetic resonance images is commonly used as a biomarker of biological aging and brain health. Ideally, as a clinically valid biomarker, brain age should indicate the current state of health and be predictive of future disease onset and detrimental changes in brain biology. In this preregistered study, we evaluated and compared the clinical validity, i.e., diagnostic and prognostic performance, of six publicly available brain age prediction packages using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Baseline brain age differed significantly between groups consisting of individuals with normal cognitive function, mild cognitive impairment, and Alzheimer's disease for all packages, but with comparable performance to estimates of gray matter volume. Further, brain age estimates were not centered around zero for cognitively normal subjects and showed considerable variation between packages. Finally, brain age was only weakly correlated with disease onset, memory decline, and gray matter atrophy within four years from baseline in individuals without neurodegenerative disease. The systematic discrepancy between chronological age and brain age among healthy subjects, combined with the weak associations between brain age and longitudinal changes in memory performance or gray matter volume, suggests that the current brain age estimates have limited clinical validity as a biomarker for biological aging.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204421/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv : the preprint server for health sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2025.03.13.25323902","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Brain age estimated from structural magnetic resonance images is commonly used as a biomarker of biological aging and brain health. Ideally, as a clinically valid biomarker, brain age should indicate the current state of health and be predictive of future disease onset and detrimental changes in brain biology. In this preregistered study, we evaluated and compared the clinical validity, i.e., diagnostic and prognostic performance, of six publicly available brain age prediction packages using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Baseline brain age differed significantly between groups consisting of individuals with normal cognitive function, mild cognitive impairment, and Alzheimer's disease for all packages, but with comparable performance to estimates of gray matter volume. Further, brain age estimates were not centered around zero for cognitively normal subjects and showed considerable variation between packages. Finally, brain age was only weakly correlated with disease onset, memory decline, and gray matter atrophy within four years from baseline in individuals without neurodegenerative disease. The systematic discrepancy between chronological age and brain age among healthy subjects, combined with the weak associations between brain age and longitudinal changes in memory performance or gray matter volume, suggests that the current brain age estimates have limited clinical validity as a biomarker for biological aging.