Semiautomated segmentation of lower extremity MRI reveals distinctive subcutaneous adipose tissue in lipedema: a pilot study

Shannon L. Taylor; Paula M. C. Donahue; Michael D. Pridmore; Maria E. Garza; Niral J. Patel; Chelsea A. Custer; Yu Luo; Aaron W. Aday; Joshua A. Beckman; Manus J. Donahue; Rachelle L. Crescenzi

doi:10.1117/1.JMI.10.3.036001

15 May 2023 Semiautomated segmentation of lower extremity MRI reveals distinctive subcutaneous adipose tissue in lipedema: a pilot study

Shannon L. Taylor, Paula M. C. Donahue, Michael D. Pridmore, Maria E. Garza, Niral J. Patel, Chelsea A. Custer, Yu Luo, Aaron W. Aday, Joshua A. Beckman, Manus J. Donahue, Rachelle L. Crescenzi

Author Affiliations +

Journal of Medical Imaging, Vol. 10, Issue 3, 036001 (May 2023). https://doi.org/10.1117/1.JMI.10.3.036001

Abstract

Purpose

Lipedema is a painful subcutaneous adipose tissue (SAT) disease involving disproportionate SAT accumulation in the lower extremities that is frequently misdiagnosed as obesity. We developed a semiautomatic segmentation pipeline to quantify the unique lower-extremity SAT quantity in lipedema from multislice chemical-shift-encoded (CSE) magnetic resonance imaging (MRI).

Approach

Patients with lipedema (n = 15) and controls (n = 13) matched for age and body mass index (BMI) underwent CSE-MRI acquired from the thighs to ankles. Images were segmented to partition SAT and skeletal muscle with a semiautomated algorithm incorporating classical image processing techniques (thresholding, active contours, Boolean operations, and morphological operations). The Dice similarity coefficient (DSC) was computed for SAT and muscle automated versus ground truth segmentations in the calf and thigh. SAT and muscle volumes and the SAT-to-muscle volume ratio were calculated across slices for decades containing 10% of total slices per participant. The effect size was calculated, and Mann–Whitney U test applied to compare metrics in each decade between groups (significance: two-sided P < 0.05).

Results

Mean DSC for SAT segmentations was 0.96 in the calf and 0.98 in the thigh, and for muscle was 0.97 in the calf and 0.97 in the thigh. In all decades, mean SAT volume was significantly elevated in participants with versus without lipedema (P < 0.01), whereas muscle volume did not differ. Mean SAT-to-muscle volume ratio was significantly elevated (P < 0.001) in all decades, where the greatest effect size for distinguishing lipedema was in the seventh decade approximately midthigh (r = 0.76).

Conclusions

The semiautomated segmentation of lower-extremity SAT and muscle from CSE-MRI could enable fast multislice analysis of SAT deposition throughout the legs relevant to distinguishing patients with lipedema from females with similar BMI but without SAT disease.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Shannon L. Taylor, Paula M. C. Donahue, Michael D. Pridmore, Maria E. Garza, Niral J. Patel, Chelsea A. Custer, Yu Luo, Aaron W. Aday, Joshua A. Beckman, Manus J. Donahue, and Rachelle L. Crescenzi "Semiautomated segmentation of lower extremity MRI reveals distinctive subcutaneous adipose tissue in lipedema: a pilot study," Journal of Medical Imaging 10(3), 036001 (15 May 2023). https://doi.org/10.1117/1.JMI.10.3.036001

Received: 19 September 2022; Accepted: 24 April 2023; Published: 15 May 2023

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