A Large-Scale Analysis of the Impact of Physical Exercise, BMI, and Lifestyle on Brain Age Predicted from T1-weighted MRI Scans
Motivation: To study the effects of exercise, BMI and lifestyle factors on brain age. Goal(s): Developing a model for predicting brain age based on T1-weighted MRI scans. Approach: T1-weighted MRI scans of 8,770 individuals were examined. Normative brain age curves were generated with over 50,000 volumetric brain MRI scans. Results: Hypertension, type 2 diabetes, and smoking were associated with increased brain age, while exercise significantly decreased it. Pronounced effects of exercise were found in the overweight group, suggesting an increased benefit. The findings emphasize the importance of exercise in preserving brain volumes likely providing neuroprotective effects. Impact: Leveraging a brain age estimation model, we revealed protective effects of exercise on the aging brain, particularly pronounced in overweight individuals. This highlights the potential of brain age as a biomarker for monitoring and developing strategies to enhance brain health.
Authors
- Rajpaul Attariwala
- Thanh-Duc Nguyen
- Madhurima Datta (ORCID: https://orcid.org/0000-0003-1781-3377)
- Nasrin Akbari (ORCID: https://orcid.org/0000-0002-4086-233X)
- Arun Rajendran (ORCID: https://orcid.org/0000-0002-9738-9942)
- Sam Hashemi
- Kellyann Niotis
- Yosef Chodakiewitz (ORCID: https://orcid.org/0000-0002-0268-1060)
- Soo‐Jin Lee (ORCID: https://orcid.org/0000-0002-4938-1700)
- Saurabh K. Garg† (ORCID: https://orcid.org/0000-0003-3510-2464)
- Saqib Basar
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/4714
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00