Validation of a Semiautomatic Image Analysis Software for the Quantification of Musculoskeletal Tissues

Mahdi Imani, Ebrahim Bani Hassan, Sara Vogrin, Aaron Samuel Tze Nor Ch’Ng, Nancy E. Lane, Jane A. Cauley, Gustavo Duque

Research output: Contribution to journalArticlepeer-review

Abstract

Accurate quantification of bone, muscle, and their components is still an unmet need in the musculoskeletal field. Current methods to quantify tissue volumes in 3D images are expensive, labor-intensive, and time-consuming; thus, a reliable, valid, and quick application is highly needed. Tissue Compass is a standalone software for semiautomatic segmentation and automatic quantification of musculoskeletal organs. To validate the software, cross-sectional micro-CT scans images of rat femur (n = 19), and CT images of hip and abdomen (n = 100) from the Osteoporotic Fractures in Men (MrOS) Study were used to quantify bone, hematopoietic marrow (HBM), and marrow adipose tissue (MAT) using commercial manual software as a comparator. Also, abdominal CT scans (n = 100) were used to quantify psoas muscle volumes and intermuscular adipose tissue (IMAT) using the same software. We calculated Pearson’s correlation coefficients, individual intra-class correlation coefficients (ICC), and Bland–Altman limits of agreement together with Bland–Altman plots to show the inter- and intra-observer agreement between Tissue Compass and commercially available software. In the animal study, the agreement between Tissue Compass and commercial software was r > 0.93 and ICC > 0.93 for rat femur measurements. Bland–Altman limits of agreement was − 720.89 (− 1.5e+04, 13,074.00) for MAT, 4421.11 (− 1.8e+04, 27,149.73) for HBM and − 6073.32 (− 2.9e+04, 16,388.37) for bone. The inter-observer agreement for QCT human study between two observers was r > 0.99 and ICC > 0.99. Bland–Altman limits of agreement was 0.01 (− 0.07, 0.10) for MAT in hip, 0.02 (− 0.08, 0.12) for HBM in hip, 0.05 (− 0.15, 0.25) for bone in hip, 0.02 (− 0.18, 0.22) for MAT in L1, 0.00 (− 0.16, 0.16) for HBM in L1, and 0.02 (− 0.23, 0.27) for bone in L1. The intra-observer agreement for QCT human study between the two applications was r > 0.997 and ICC > 0.99. Bland–Altman limits of agreement was 0.03 (− 0.13, 0.20) for MAT in hip, 0.05 (− 0.08, 0.18) for HBM in hip, 0.05 (− 0.24, 0.34) for bone in hip, − 0.02 (− 0.34, 0.31) for MAT in L1, − 0.14 (− 0.44, 0.17) for HBM in L1, − 0.29 (− 0.62, 0.05) for bone in L1, 0.03 (− 0.08, 0.15) for IMAT in psoas, and 0.02 (− 0.35, 0.38) for muscle in psoas. Compared to a conventional application, Tissue Compass demonstrated high accuracy and non-inferiority while also facilitating easier analyses. Tissue Compass could become the tool of choice to diagnose tissue loss/gain syndromes in the future by requiring a small number of CT sections to detect tissue volumes and fat infiltration.

Original languageEnglish (US)
JournalCalcified Tissue International
DOIs
StateAccepted/In press - 2021

Keywords

  • Image processing
  • Intramuscular fat
  • Marrow adipose tissue
  • Osteoporosis
  • Osteosarcopenia
  • Sarcopenia

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Orthopedics and Sports Medicine
  • Endocrinology

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