Predicting dementia risk using neuroimaging and cognitive assessment
Importantly, the study demonstrates that a compact, multimodal approaching standard MRI scans with brief cognitive tests-can generate individualized risk profiles suitable for clinical use. This method offers a scalable path to early intervention, trial enrollment, and personalized care planning. Future work will focus on validating these models in more diverse populations and integrating fluid biomarkers to enhance precision. Ultimately, this research supports the development of practical tools for forecasting dementia risk and advancing preventive strategies in aging populations.
Authors
- Ankit Patel (ORCID: https://orcid.org/0000-0001-9678-496X)
- Dinesh Pal Mudaranthakam (ORCID: https://orcid.org/0000-0001-9767-1158)
- William Guiler (ORCID: https://orcid.org/0000-0001-8696-0392)
- Sam Pepper (ORCID: https://orcid.org/0000-0003-0696-3820)
- Robyn A. Honea (ORCID: https://orcid.org/0000-0002-4661-2024)
- Isuru Panduka Ratnayake (ORCID: https://orcid.org/0000-0001-9596-781X)
- Yu Wang (ORCID: https://orcid.org/0000-0001-6108-5157)
- Nithmi Walpitage
Institutions
- University of Kansas Medical Center (US)
Publication Details
- Journal
- Journal of Aging Research and Lifestyle
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.jarlif.2025.100040
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00