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Abstract Details

Deep Learning Derived Visceral Abdominal Fat Predicts Brain Atrophy at Midlife in 7507 Individuals
Aging, Dementia, Cognitive, and Behavioral Neurology
P6 - Poster Session 6 (5:30 PM-6:30 PM)
2-004

Visceral abdominal fat can predict health outcomes with potential applications on brain health and dementia prevention. Deep learning of efficient whole body MR scans can amplify the success of these objectives.

To apply deep learning to an investigation of body fat on brain atrophy.

A total of 7507 healthy participants from 4 sites were scanned on 1.5T MRI with a rapid whole-body imaging. Sequences included whole body coronal T1 and brain MPRAGE. Deep learning with FastSurfer trained 134 participants aged 27-66 and segmented 96 brain regions. Deep learning also segmented abdominal visceral fat from the scan. Partial correlations of visceral abdominal fat volume and brain volumes were controlled for age, sex, and total intracranial volume. Multiple comparisons were accounted for using the Benjamini-Hochberg False Discovery Rate of 5% Logistic regression models determined risk of brain total gray and white matter atrophy based upon the highest quartile of visceral fat and lowest quartile of total gray and white matter.

Average age was 52.90 ± 13.04 years, spanning 15-97 years with 52.4% men and 47.6% women. Mean visceral abdominal fat was 2981.37 ± 2167.27 ml, ranging from 94.63 to 14005.22 ml. Visceral abdominal fat predicted brain atrophy in: gray and white matter volumes (Partial R= -.24, p= 7.01e-97), hippocampus (Partial R= -.09, p= 3.34e-14), temporal lobes (Partial R= -.23, 4.64e-90), parietal lobes (Partial R= -.11, p=5.84e-25), and right precuneus (Partial R= -.05, p= 2.15e-5). Visceral fat predicted increased risk for lower total gray matter (age 20-39: OR = 3.33; age 40-59, OR = 3; 60-80, OR = 2.85) and white matter atrophy age 20-39: OR = 1.26; age 40-59, OR = 2.05; 60-80, OR = 2.87).

Deep learning determined increased visceral abdominal fat volume predicts brain volume loss, representing a novel modifiable factor in determining brain health.

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, Other (Prenuvo) Mr. Garg has received personal compensation for serving as an employee of Prenuvo.
Nasrin Akbari, Other (Prenuvo) Ms. Akbari has received personal compensation for serving as an employee of VoxelWise Imaging Technology Inc.
Ahmed Gouda, Other (Prenuvo) Mr. Gouda has received personal compensation for serving as an employee of Prenuvo.
Yosef Chodakiewitz, MD (Prenuvo) Dr. Chodakiewitz has received personal compensation for serving as an employee of Prenuvo . Dr. Chodakiewitz has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Aidoc.
Thanh Duc Nguyen, Sr., PhD (Prenuvo) Dr. Nguyen has nothing to disclose.
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.