Abstract Details

Title Vigorous Physical Activity Predicts Deep Learning Derived Brain Volumes in 8823 Individuals

Topic Aging, Dementia, and Behavioral Neurology

Presentation(s) P6 - Poster Session 6 (5:30 PM-6:30 PM)

Poster/Presentation
Number 2-006

Objective We explored relationship between vigorous physical activity and deep learning determined brain volumes.

Background

Physical activity reduces dementia risk and brain volume loss on MRI is an important biomarker for neurodegeneration. It is unknown if vigorous physical activity relates to improved brain structure and neuroprotection.

Design/Methods

Overall, 8823 healthy participants across 4 sites were scanned on 1.5T MR with a short whole-body MR imaging protocol: whole body coronal T1, STIR from vertex to feet, whole-body axial DWI from vertex to proximal-thighs and axial T2 TSE without fat suppression from skull base to pelvis. Brain sequences were sagittal isotropic MP-RAGE and 2D FLAIR. Deep learning with FastSurfer trained 134 participants aged 27-66 segmented 96 brain regions. Partial correlations modeled vigorous physical activity, defined as sports, fitness and recreational activities that increased respiration and pulse rate for at least 10 continuous minutes, with brain volumes. Analyses controlled for age, sex, and total intracranial volume. Benjamini-Hochberg False Discovery Rate of 5% accounted for multiple comparisons.

Results This cohort had an average age of 52.90 ± 13.06 years ranging from 23-84 years with 52.5% men and 47.5% women. Overall, 4269 individuals (48.3%) reported vigorous physical activity at least once per week with 1140 (27%) engaging for 3 days per week. Persons with vigorous activity were younger (mean age 52.08 versus 54.6 for non-vigorous physical activity (p < .00001) and 51.6% men versus 48.3% women undertook vigorous physical activity. After accounting for co-variates and multiple comparisons, vigorous physical activity predicted larger volumes in multiple regions including: gray and white matter volumes (Partial R=.11, p=1.01e-22), hippocampus (Partial R=.07, p= 9.31e-11), frontal cortex (Partial R=.08, p=6.84e-12) temporal lobes (Partial R=.11, 9.72e-22), left entorhinal cortex (Partial R=.07, p=1.62e-9).

Conclusions

Vigorous physical activity predicted larger deep learning segmented brain volumes, including those relevant for cognition and vulnerable to neurodegeneration.

Authors/Disclosures
Cyrus A. Raji, MD, PhD (Washington University in St Louis) PRESENTER	Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Brainreader ApS. Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Apollo Health . Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Neurevolution Medicine.
Somayeh Meysami, MD (Pacific Neuroscience Institute, Providence Saint Johns Health Center)	Dr. Meysami has nothing to disclose.
Sam Hashemi (Prenuvo)	Mr. Hashemi has received personal compensation for serving as an employee of Prenuvo.
Saurabh Garg (Prenuvo)	No disclosure on file
Nasrin Akbari (Prenuvo)	No disclosure on file
Thanh Nguyen (Prenuvo)	No disclosure on file
	No disclosure on file
Yosef Chodakiewitz (Prenuvo)	No disclosure on file
Raj Attariwala, MD, PhD	Dr. Attariwala has received personal compensation in the range of $50,000-$99,999 for serving as a Consultant for Prenuvo. Dr. Attariwala has stock in Prenuvo. Dr. Attariwala has received research support from Voxelwise Imaging Technology. Dr. Attariwala has received personal compensation in the range of $100,000-$499,999 for serving as a Radiologist reading cases and helping build in house software tools with Prenuvo.

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