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

Authors: Ornowski JDziesinski LHess MKrug RFortin MTorres-Espin AMajumdar SPedoia VBonnheim NBBailey JF


Affiliations

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.

Description

Background: Paraspinal 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.

Methods: To 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.

Results: We 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.

Conclusion: We 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.


Links

PubMed: https://pubmed.ncbi.nlm.nih.gov/38222819/

DOI: 10.1002/jsp2.1301