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

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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.

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Acknowledgements

The Osteoporotic Fractures in Men (MrOS) Study is supported by National Institutes of Health funding. The following institutes provide support: the National Institute on Aging (NIA), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Center for Advancing Translational Sciences (NCATS), and NIH Roadmap for Medical Research under the following Grant Numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128.’

Funding

This study was funded via a Seed Grant from the Australian Institute for Musculoskeletal Science (AIMSS). EB was supported by the Australian Medical Research Frontiers Fund fellowship (MRFF; Melbourne Academic Centre for Health: MACH-RART scheme, 2019).

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Authors and Affiliations

  1. Australian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St. Albans, VIC, 3021, Australia

    Mahdi Imani, Ebrahim Bani Hassan, Sara Vogrin, Aaron Samuel Tze Nor Ch’Ng & Gustavo Duque

  2. Department of Medicine-Western Health, The University of Melbourne, St. Albans, VIC, 3021, Australia

    Mahdi Imani, Ebrahim Bani Hassan, Sara Vogrin, Aaron Samuel Tze Nor Ch’Ng & Gustavo Duque

  3. Center for Musculoskeletal Health, University of California at Davis School of Medicine, 4625 2nd Avenue Suite 2000, Sacramento, CA, 95817, USA

    Nancy E. Lane

  4. Department of Epidemiology Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Jane A. Cauley

Authors
  1. Mahdi Imani
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  2. Ebrahim Bani Hassan
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  4. Aaron Samuel Tze Nor Ch’Ng
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Contributions

MI, EBH, and GD contributed to the study design. MI, EBH, ASTNC, SV, and GD contributed to the collection and interpretation of data. All authors contributed to the drafting and critical appraisal of the manuscript and approved the final version.

Corresponding author

Correspondence to Gustavo Duque.

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Conflict of interest

Mahdi Imani, Ebrahim Bani Hassan, Sara Vogrin, Aaron Samuel Tze Nor Ch’Ng, Nancy E. Lane, Jane A. Cauley and Gustavo Duque have no conflict of interest to declare.

Human and Animal Rights

All human and animal studies have been approved by the appropriate ethics committee and have therefore been performed following the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Informed Consent

Informed consent was obtained from all patients for being included in the study.

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Supplementary Information

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Supplemental video 1 (MP4 26580 kb)

Supplemental video 2 (MP4 67888 kb)

223_2021_914_MOESM3_ESM.tiff

Supplemental Figure 1 – Comparison between Tissue Compass (on the left) and SliceOmatic’s (on the right) user interface. (TIFF 1364 kb)

223_2021_914_MOESM4_ESM.tiff

Supplemental Figure 2 – Agreement between methods (SliceOmatic vs. Tissue Compass) for a) MAT, b) HBM, and c) bone volume in micro-CT scan of the rat femur bone. The difference in the plots is the difference between Tissue Compass and SliceOmatic. Dashed lines represent mean difference, and gray area shows ±1.96 standard deviation below and above mean difference. (TIFF 335 kb)

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Imani, M., Bani Hassan, E., Vogrin, S. et al. Validation of a Semiautomatic Image Analysis Software for the Quantification of Musculoskeletal Tissues. Calcif Tissue Int 110, 294–302 (2022). https://doi.org/10.1007/s00223-021-00914-4

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