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    Quantitative texture analysis of T2- weighted MR images in polymyositis and dermatomyositis patients

    Xie, Yuan
    : https://etd.library.vanderbilt.edu/etd-08102017-110606
    http://hdl.handle.net/1803/13868
    : 2017-08-11

    Abstract

    Dermatomyositis (DM) and polymyositis (PM) patients experience intramuscular inflammation and necrosis, eventually progressing to fat infiltration. The gold standard for MRI assessment of fat tissue infiltration is quantitative fat-water MRI. Fat tissue is also detectable using standard contrast-based clinical MRI sequences; however, typical analyses of these data are qualitative. Texture analysis is a quantitative method for analyzing signal variations in contrast-based images. The goals of this study were to determine which MRI and tissue parameters explain variations in texture parameters and to use texture analysis of contrast-based MR images to predict the fat fraction (Ffat), as determined by quantitative fat-water MRI. Fat signal-suppressed (FS) T1 and T2 maps, Ffat maps, and T2-weighted MR images were acquired from 5 DM patients, 8 PM patients, and 13 control subjects. Images were acquired at mid-thigh. The Grey Level Co-occurrence Matrix (GLCM) and Grey Level Run-length Matrix (GLRM) were calculated and used to derive 11 texture features. Regression analysis focused on the log(Energy) parameter, derived from the GLCM, and the High Gray-level Run-length Emphasis (HGRE), derived from the GLRM. 57.4% of the variance in log(Energy) was explained by Ffat variations. For HGRE, 68.6% of its variance was explained by Ffat variations. Finally, using HGRE, Low Gray level run emphasis, and Homogeneity as predictors, we were able to explain 70.3% of the variance in Ffat. These data show that HGRE primarily reflects fat tissue infiltration. Also, texture analysis can be used to predict Ffat from T2-weighted clinical MR images.
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