SMAS: Structural MRI-based AD Score using Bayesian supervised VAE.
Authors
Affiliations (29)
Affiliations (29)
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University (OVGU), Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. Electronic address: [email protected].
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University (OVGU), Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
- DZNE, Rostock, Germany.
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University (OVGU), Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Department for Psychiatry and Psychotherapy, University Clinic Magdeburg, Germany.
- University of Bonn, Germany; University of Cambridge, Cambridge, UK; DZNE, Bonn, Germany.
- DZNE, Berlin, Germany; Charité - Universitätsmedizin Berlin, Institute of Psychiatry and Psychotherapy, Berlin, Germany.
- Charité - Universitätsmedizin Berlin, Institute of Psychiatry and Psychotherapy, Berlin, Germany.
- DZNE, Berlin, Germany; Charité - Universitätsmedizin Berlin, Institute of Psychiatry and Psychotherapy, Berlin, Germany; Technical University of Munich, Department of Psychiatry and Psychotherapy, Munich, Germany; University of Edinburgh, UK.
- DZNE, Bonn, Germany; Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn and University of Bonn, Germany.
- DZNE, Bonn, Germany.
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Germany; DZNE, Goettingen, Germany; Institute of Biomedicine (iBiMED), University of Aveiro, Portugal.
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Germany.
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Germany; DZNE, Goettingen, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany.
- Department of Psychiatry, University of Cologne, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Department for Neurology, University Clinic Magdeburg, Germany.
- DZNE, Munich, Germany; Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.
- DZNE, Munich, Germany; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Ageing Epidemiology Research Unit (AGE), Imperial College London, UK.
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, UK; Department of Neuroradiology, University Hospital, LMU Munich, Germany.
- DZNE, Rostock, Germany; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany.
- DZNE, Tübingen, Germany; Section for Dementia Research, Hertie Institute for Clinical Brain Research, Germany; Department of Psychiatry and Psychotherapy, University of Tübingen, Germany.
- DZNE, Tübingen, Germany; Department of Psychiatry and Psychotherapy, University of Tübingen, Germany.
- DZNE, Bonn, Germany; Department of Neurology, University of Bonn, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Goettingen, Germany.
- Department for Biomedical Magnetic Resonance, University of Tübingen, Germany.
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Germany.
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn and University of Bonn, Germany.
- DZNE, Bonn, Germany; Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Germany; Department of Psychiatry, University of Cologne, Medical Faculty, Germany.
Abstract
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.