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The reliability of a segmentation methodology for assessing intramuscular adipose tissue and other soft-tissue compartments of lower leg MRI images

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Abstract

Objective

Determine the reliability of a magnetic resonance (MR) image segmentation protocol for quantifying intramuscular adipose tissue (IntraMAT), subcutaneous adipose tissue, total muscle and intermuscular adipose tissue (InterMAT) of the lower leg.

Materials and methods

Ten axial lower leg MRI slices were obtained from 21 postmenopausal women using a 1 Tesla peripheral MRI system. Images were analyzed using sliceOmatic™ software. The average cross-sectional areas of the tissues were computed for the ten slices. Intra-rater and inter-rater reliability were determined and expressed as the standard error of measurement (SEM) (absolute reliability) and intraclass coefficient (ICC) (relative reliability).

Results

Intra-rater and inter-rater reliability for IntraMAT were 0.991 (95 % confidence interval [CI] 0.978–0.996, p < 0.05) and 0.983 (95 % CI 0.958–9.993, p < 0.05), respectively. For the other soft tissue compartments, the ICCs were all >0.90 (p < 0.05). The absolute intra-rater and inter-rater reliability (expressed as SEM) for segmenting IntraMAT were 22.19 mm2 (95 % CI 16.97–32.04) and 78.89 mm2 (95 % CI 60.36–113.92), respectively.

Conclusion

This is a reliable segmentation protocol for quantifying IntraMAT and other soft-tissue compartments of the lower leg. A standard operating procedure manual is provided to assist users, and SEM values can be used to estimate sample size and determine confidence in repeated measurements in future research.

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Acknowledgments

We would like to acknowledge the late Dr. Colin Webber for his passionate insight and guidance on this topic. We thank the study participants and staff at Hamilton Health Sciences Well-Health Centre and McMaster University Medical Centre Diabetes Outpatient Clinic who assisted with the study. In particular, Dr. Hertzel Gerstein and Dr. Zubin Punthakee were instrumental in assisting with participant recruitment. We would also like to thank Professor Paul Stratford for reviewing and providing feedback on the manuscript, Dr. Dean Inglis for developing the MRI imaging protocol, Yves Martel (Tomovision), Amanda Lorbergs and Mike Davison for reviewing the manual. JP was funded as a post-doctoral fellow by the Hamilton Health Sciences Foundation to complete this work.

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Authors and Affiliations

  1. Department of Medicine, McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada

    Sarah Karampatos, Alexandra Papaioannou, Karen A. Beattie, Jonathan D. Adachi & Janet M. Pritchard

  2. Juravinski Research Centre, Geriatric Education and Research in the Aging Sciences (GERAS) Centre, 88 Maplewood Avenue, Hamilton, ON, L8M 1W9, Canada

    Sarah Karampatos, Alexandra Papaioannou & Janet M. Pritchard

  3. Department of Rehabilitation Sciences, McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada

    Sarah Karampatos & Monica R. Maly

  4. Department of Biostatistics and Epidemiology, McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada

    Alexandra Papaioannou

  5. Faculty of Health Sciences, McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada

    Adrian Chan

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  1. Sarah Karampatos
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Correspondence to Sarah Karampatos.

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Conflict of interest

S. Karampatos, K. A. Beattie, M. Maly, A. Chan, J. M. Pritchard have no conflict of interest. A. Papaioannou has received grants, research support and/or honoraria from Amgen, Eli Lilly, Novartis, Warner Chilcott and Merck Canada. J. D. Adachi has received grants, research support and/or honoraria from Amgen, Eli Lilly, Novartis, Warner Chilcott and Merck Canada.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee (The Hamilton Integrated Research Ethics Board).

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The Hamilton Integrated Research Ethics Board approved the study. Informed consent was obtained from all individual participants included in the study.

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Karampatos, S., Papaioannou, A., Beattie, K.A. et al. The reliability of a segmentation methodology for assessing intramuscular adipose tissue and other soft-tissue compartments of lower leg MRI images. Magn Reson Mater Phy 29, 237–244 (2016). https://doi.org/10.1007/s10334-015-0510-7

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