Automated Body Composition Analysis Using DAFS Express on 2D MRI Slices at L3 Vertebral Level
Varun Akella, Razeyeh Bagherinasab, Jia Ming Li, Long Nguyen, Vincent, Tze Yang Chow, Hyunwoo Lee, Karteek Popuri, Mirza Faisal Beg

TL;DR
This study validates an automated MRI segmentation tool, DAFS Express, for rapid, accurate body composition analysis at the L3 vertebral level, showing high agreement with expert manual segmentation in a large cohort.
Contribution
The paper introduces and validates DAFS Express, an automated tool for MRI-based body composition analysis, demonstrating its high accuracy and efficiency compared to manual methods.
Findings
High segmentation accuracy with Jaccard scores over 95%.
Strong reliability indicated by ICCs above 0.99.
Automated analysis takes approximately 18 seconds per scan.
Abstract
Body composition analysis is vital in assessing health conditions such as obesity, sarcopenia, and metabolic syndromes. MRI provides detailed images of skeletal muscle (SKM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), but their manual segmentation is labor-intensive and limits clinical applicability. This study validates an automated tool for MRI-based 2D body composition analysis- (Data Analysis Facilitation Suite (DAFS) Express), comparing its automated measurements with expert manual segmentations using UK Biobank data. A cohort of 399 participants from the UK Biobank dataset was selected, yielding 423 single L3 slices for analysis. DAFS Express performed automated segmentations of SKM, VAT, and SAT, which were then manually corrected by expert raters for validation. Evaluation metrics included Jaccard coefficients, Dice scores, Intraclass Correlation…
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Taxonomy
TopicsBody Composition Measurement Techniques
