Automatic quantification of fat infiltration in paraspinal muscles using T2-weighted images: An OsiriX application

Abstract
Fat infiltration of paraspinal muscles has been related with low back pain and quantified using T2w MR images and manual segmentation techniques. This methodology is time consuming and has low reproducibility. Moreover, the accuracy of T2w images to quantify fat has not been validated. This paper presents the development and validation of an OsiriX application to semi-automatically segment infiltrated fat on T2w images. This software was also utilized to validate the quantification of muscle fat infiltration with T2w images, considering Dixon fat images assessments as a gold standard.
Two databases have been considered: 1)T2w images of 37 patients for comparison between manual and semi-automatic segmentations; 2)T2w and Dixon fat images of 10 healthy volunteers and 10 patients to validate the use of T2w images. The OsiriX application was based on automatic thresholding techniques. The fat infiltration fraction was measured in 4 muscle groups (erector spinae and multifidus) and in 5 cross-sectional areas (from L1-L2 to L5-S1) for both databases. From the 37 patients, we randomly selected 15 patients to assess reproducibility of the measurements.
Manual and automatic fat quantifications using T2w images showed a correlation of 0.86, no statistical differences, bias of 0.05 % of the muscle area, and limits of agreement of [-12.52, 12.63]% of muscle area. Fat quantifications using Dixon and T2w images showed correlation of 0.94, no statistical differences, bias of 0.38 % of the muscle area, and limits of agreement of [-8.64, 9.41]% of the muscle area.
T2w images segmented with this new OsiriX application are reliable and accurate for quantifying fat infiltration in paraspinal muscles. (C) 2019 Published by Elsevier Ltd.
Description
Keywords
T2w images, Dixon methods, Fat segmentation, Low back pain, Paraspinal muscles, OsiriX application, LOW-BACK-PAIN, CROSS-SECTIONAL AREA, GOUTALLIER CLASSIFICATION, DEGENERATION, RELIABILITY, SOFTWARE
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