Multi-compartment mesenchymal tissue segmentation in pelvic MRI examinations of women: Anthropomorphic and clinical correlations

Raamis Khwaja, Riham Dessouky, Michael A. Heffler, Yin Xi, Ian J Neeland, Avneesh Chhabra

Research output: Contribution to journalArticle

Abstract

Aim: To investigate the reliability of multicompartmental volumetric mesenchymal segmentations on MRI and their correlations with anthropomorphic and clinical parameters. Materials and methods: A consecutive series of middle-age (35–50 year old) female volunteers with variable body mass index (BMI) and MRI scans performed as a part of the Dallas Heart Study were included. A semi-automatic segmentation tool was used to partition different mesenchymal tissues- fat, muscle, and bone on MRI of pelvis. Total volumes of each compartment were calculated and compared between overweight/obese (BMI> = 25 kg/m2) and non-obese (BMI < 25 kg/m2) groups, and with physical performance measurements, i.e. mean activity counts per minute (MVPA) and cardiorespiratory fitness (CRF) estimated by submaximal treadmill test (TT). Kruskal Wallis, Mann-Whitney U test, intraclass correlation coefficient (ICC) and Spearman correlations were used. P value <0.05 was considered statistically significant. Results: There were statistically significant positive correlations between fat volume and BMI (p < 0.0001), muscle volume and height (p = 0.03), and bone volume and height (p < 0.0001). Significant inverse correlations were found between bone volume and BMI (p = 0.002). Fair to good interobserver reliability was seen with muscle and fat volumes (ICC = 0.43–0.64) and excellent reliability was seen with bone volumes (ICC = 0.78–0.79). Statistically significant inverse correlations were found between MVPA and age (p = 0.01), and TT with BMI and weight (p = 0.01, 0.03). Conclusion: Multi-compartment mesenchymal tissue volume quantification on pelvic MRI is reliable in females. Inverse correlation of bone volume with BMI has potential implications for future risk of fracture.

Original languageEnglish (US)
Pages (from-to)37-43
Number of pages7
JournalEuropean Journal of Radiology
Volume112
DOIs
StatePublished - Mar 1 2019

Keywords

  • Bone
  • Fat
  • MRI
  • Muscle
  • Obesity
  • Segmentation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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