TY  - JOUR
AU  - Nemali, A.
AU  - Bernal, J.
AU  - Yakupov, R.
AU  - Singh, Devesh
AU  - Dyrba, M.
AU  - Incesoy, E. I.
AU  - Mukherjee, S.
AU  - Peters, O.
AU  - Ersözlü, E.
AU  - Hellmann-Regen, J.
AU  - Preis, Lukas
AU  - Priller, J.
AU  - Spruth, Eike Jakob
AU  - Altenstein, S.
AU  - Lohse, A.
AU  - Schneider, Anja
AU  - Fliessbach, K.
AU  - Kimmich, O.
AU  - Wiltfang, J.
AU  - Hansen, N.
AU  - Schott, B.
AU  - Rostamzadeh, A.
AU  - Glanz, W.
AU  - Butryn, M.
AU  - Buerger, K.
AU  - Janowitz, Daniel
AU  - Ewers, Michael
AU  - Perneczky, R.
AU  - Rauchmann, Boris Stephan
AU  - Teipel, S.
AU  - Kilimann, I.
AU  - Goerss, D.
AU  - Laske, C.
AU  - Sodenkamp, S.
AU  - Spottke, A.
AU  - Coenjaerts, M.
AU  - Brosseron, F.
AU  - Lüsebrink, F.
AU  - Dechent, P.
AU  - Scheffler, K.
AU  - Hetzer, S.
AU  - Kleineidam, L.
AU  - Stark, M.
AU  - Jessen, F.
AU  - Duzel, E.
AU  - Ziegler, G.
TI  - SMAS: Structural MRI-based AD Score using Bayesian supervised VAE.
JO  - Computers in biology and medicine
VL  - 196
IS  - Pt C
SN  - 0010-4825
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - DZNE-2025-01044
SP  - 110829
PY  - 2025
AB  - This study introduces the Structural MRI-based Alzheimer's Disease Score (SMAS), a novel index intended to quantify Alzheimer's Disease (AD)-related morphometric patterns using a deep learning Bayesian-supervised Variational Autoencoder (Bayesian-SVAE). The SMAS index was constructed using baseline structural MRI data from the DELCODE study and evaluated longitudinally in two independent cohorts: DELCODE (n=415) and ADNI (n=190). Our findings indicate that SMAS has strong associations with cognitive performance (DELCODE: r=-0.83; ADNI: r=-0.62), age (DELCODE: r=0.50; ADNI: r=0.28), hippocampal volume (DELCODE: r=-0.44; ADNI: r=-0.66), and total gray matter volume (DELCODE: r=-0.42; ADNI: r=-0.47), suggesting its potential as a biomarker for AD-related brain atrophy. Moreover, our longitudinal studies indicated that SMAS may be useful for the early identification and tracking of AD. The model demonstrated significant predictive accuracy in distinguishing cognitively healthy individuals from those with AD (DELCODE: AUC=0.971 at baseline, 0.833 at 36 months; ADNI: AUC=0.817 at baseline, improving to 0.903 at 24 months). Notably, over 36 months, the SMAS index outperformed existing measures such as SPARE-AD and hippocampal volume. The relevance map analysis revealed significant morphological changes in key AD-related brain regions, including the hippocampus, posterior cingulate cortex, precuneus, and lateral parietal cortex, highlighting that SMAS is a sensitive and interpretable biomarker of brain atrophy, suitable for early AD detection and longitudinal monitoring of disease progression.
KW  - Alzheimer’s disease (Other)
KW  - Bayesian Supervised Variational Autoencoder (Other)
KW  - Bayesian inference (Other)
KW  - Brain morphology indices (Other)
KW  - Cognitive decline (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:40818206
DO  - DOI:10.1016/j.compbiomed.2025.110829
UR  - https://pub.dzne.de/record/280962
ER  -