TY - JOUR
T1 - Prediction of brain age using structural magnetic resonance imaging
T2 - a comparison of clinical utility of publicly available software packages
AU - Dörfel, Ruben P.
AU - Ozenne, Brice
AU - Ganz, Melanie
AU - Svensson, Jonas E.
AU - Plavén-Sigray, Pontus
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2026/1
Y1 - 2026/1
N2 - Background: Brain age estimated from structural magnetic resonance images is commonly used as a biomarker of biological ageing and brain health. Ideally, as a clinically useful biomarker, brain age should indicate the current state of health and be predictive of future disease onset and detrimental changes in brain biology. Methods: In this preregistered study, we evaluated and compared the clinical utility, i.e., diagnostic and prognostic performance, of six publicly available brain age prediction packages using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Findings: 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 grey matter volume. Further, brain age estimates were not centred around zero for participants with normal cognition and showed considerable variation between packages. Finally, brain age was only weakly correlated with disease onset, memory decline, and grey matter atrophy within four years from baseline in individuals without neurodegenerative disease. Interpretation: 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 grey matter volume, suggests that the current brain age estimates have limited clinical utility as a biomarker for biological ageing. Funding: This work was supported by a Longevity Impetus Grant from the Norn Group, the Karolinska Institutet Loo och Hans Ostermans Stiftelse, Gun och Bertil Stohnes Stiftelse, Stiftelsen Gamla Tjänarinnor, Stiftelsen Söderström - Königska and Åhlén-stiftelsen (243016). PPS was supported by a grant from the Swedish Brain Foundation (PD2024-0444) and the Åke Wibergs Stiftelse (M24-0117).
AB - Background: Brain age estimated from structural magnetic resonance images is commonly used as a biomarker of biological ageing and brain health. Ideally, as a clinically useful biomarker, brain age should indicate the current state of health and be predictive of future disease onset and detrimental changes in brain biology. Methods: In this preregistered study, we evaluated and compared the clinical utility, i.e., diagnostic and prognostic performance, of six publicly available brain age prediction packages using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Findings: 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 grey matter volume. Further, brain age estimates were not centred around zero for participants with normal cognition and showed considerable variation between packages. Finally, brain age was only weakly correlated with disease onset, memory decline, and grey matter atrophy within four years from baseline in individuals without neurodegenerative disease. Interpretation: 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 grey matter volume, suggests that the current brain age estimates have limited clinical utility as a biomarker for biological ageing. Funding: This work was supported by a Longevity Impetus Grant from the Norn Group, the Karolinska Institutet Loo och Hans Ostermans Stiftelse, Gun och Bertil Stohnes Stiftelse, Stiftelsen Gamla Tjänarinnor, Stiftelsen Söderström - Königska and Åhlén-stiftelsen (243016). PPS was supported by a grant from the Swedish Brain Foundation (PD2024-0444) and the Åke Wibergs Stiftelse (M24-0117).
KW - Biomarker
KW - Brain age
KW - Clinical utility
KW - Machine learning
KW - Predicted age deviation
KW - Structural MRI
UR - http://www.scopus.com/inward/record.url?scp=105027101923&partnerID=8YFLogxK
U2 - 10.1016/j.ebiom.2025.106094
DO - 10.1016/j.ebiom.2025.106094
M3 - Journal article
C2 - 41483685
AN - SCOPUS:105027101923
SN - 2352-3964
VL - 123
JO - EBioMedicine
JF - EBioMedicine
M1 - 106094
ER -