Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
566-03-013 ISMRM Abstract

Estimating Brain Age and Identifying SuperAgers Using Bayesian Neural Networks

Primary: Neuro - Aging
Secondary: Analysis Methods - Classification and Prediction
566-03-013 · Radiomics Potpourri · Wednesday, 13 May, 1:40 PM–2:35 PM · Digital Posters Row G
Keywords: Cortical thickness Brain Age Estimation Volumetry Machine learning (ML) SuperAgers
Accepted
Carlos Leandro Silva dos Prazeres1, Alessandra C Goulart2,3, Claudia C Leite1,4, Alexandre Chiavegatto Filho2, Claudia K Suemoto5, Isabela Benseñor3,5, Paulo A Lotufo3,5, Maria Garcia Otaduy 1
1LIM44-Instituto de Radiologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, Brazil
2Department of Epidemiology, School of Public Health, Universidade de São Paulo, São Paulo, Brazil
3Center for Clinical and Epidemiological Research, Hospital Universitario da Universidade de São Paulo, São Paulo, Brazil
4Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, Brazil
5Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
Presenting Author: Maria Garcia Otaduy

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References

1. Niu, X., Zhang, F., Kounios, J., & Liang, H. (2020). Improved prediction of brain age using multimodal neuroimaging data. Human Brain Mapping, 41(6), 1626–1643. https://doi.org/10.1002/hbm.24899 [doi]
2. Passos, V. M. de A., Caramelli, P., Benseñor, I., Giatti, L., & Barreto, S. M. (2014). Methods of cognitive function investigation in the Longitudinal Study on Adult Health (ELSA-Brasil). Sao Paulo Medical Journal, 132(3), 170–177. https://doi.org/10.1590/1516-3180.2014.1323646 [doi]
3. Fischl, B. (2012). FreeSurfer. NeuroImage, 62(2), 774–781. https://doi.org/10.1016/j.neuroimage.2012.01.021 [doi]
4. Chatterjee, S. (2019). A new coefficient of correlation. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.1909.10140 [doi]
5. Fong, T. G., Fearing, M. A., Jones, R. N., Shi, P., Marcantonio, E. R., Rudolph, J. L., Yang, F. M., Dan Kiely, K., & Inouye, S. K. (2009). Telephone Interview for Cognitive Status: Creating a crosswalk with the Mini-Mental State Examination. Alzheimer’s & Dementia, 5(6), 492–497. https://doi.org/10.1016/j.jalz.2009.02.007 [doi]
6. Bishop, C. M. (1997). Bayesian Neural Networks. Journal of the Brazilian Computer Society, 4(1). https://doi.org/10.1590/s0104-65001997000200006 [doi]
7. Lundberg, S., & Lee, S.-I. (2017, November 24). A Unified Approach to Interpreting Model Predictions. ArXiv.org. https://doi.org/10.48550/arXiv.1705.07874 [doi]

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http://echo.ismrm.org/p/ISMRM2026/566-03-013