Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI

Author:

Ornowski Jessica1ORCID,Dziesinski Lucas1,Hess Madeline2ORCID,Krug Roland2,Fortin Maryse3,Torres‐Espin Abel456,Majumdar Sharmila2,Pedoia Valentina2,Bonnheim Noah B.1ORCID,Bailey Jeannie F.1

Affiliation:

1. Department of Orthopaedic Surgery University of California San Francisco California USA

2. Department of Radiology and Biomedical Imaging University of California San Francisco California USA

3. Department of Health, Kinesiology, and Applied Physiology Concordia University Montreal Québec Canada

4. School of Public Health Sciences Faculty of Health University of Waterloo Waterloo Ontario Canada

5. Department of Physical Therapy University of Alberta Edmonton Alberta Canada

6. Department of Neurological Surgery University of California San Francisco California USA

Abstract

AbstractBackgroundParaspinal muscle fat infiltration is associated with spinal degeneration and low back pain, however, quantifying muscle fat using clinical magnetic resonance imaging (MRI) techniques continues to be a challenge. Advanced MRI techniques, including chemical‐shift encoding (CSE) based water–fat MRI, enable accurate measurement of muscle fat, but such techniques are not widely available in routine clinical practice.MethodsTo facilitate assessment of paraspinal muscle fat using clinical imaging, we compared four thresholding approaches for estimating muscle fat fraction (FF) using T1‐ and T2‐weighted images, with measurements from water–fat MRI as the ground truth: Gaussian thresholding, Otsu's method, K‐mean clustering, and quadratic discriminant analysis. Pearson's correlation coefficients (r), mean absolute errors, and mean bias errors were calculated for FF estimates from T1‐ and T2‐weighted MRI with water–fat MRI for the lumbar multifidus (MF), erector spinae (ES), quadratus lumborum (QL), and psoas (PS), and for all muscles combined.ResultsWe found that for all muscles combined, FF measurements from T1‐ and T2‐weighted images were strongly positively correlated with measurements from the water–fat images for all thresholding techniques (r = 0.70–0.86, p < 0.0001) and that variations in inter‐muscle correlation strength were much greater than variations in inter‐method correlation strength.ConclusionWe conclude that muscle FF can be quantified using thresholded T1‐ and T2‐weighted MRI images with relatively low bias and absolute error in relation to water–fat MRI, particularly in the MF and ES, and the choice of thresholding technique should depend on the muscle and clinical MRI sequence of interest.

Funder

National Institute of Arthritis and Musculoskeletal and Skin Diseases

Publisher

Wiley

Subject

Orthopedics and Sports Medicine

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