Comparison of automated and visual texture analysis in MRI: Characterization of normal and diseased skeletal muscle

Abstract

Automated magnetic resonance imaging (MRI) texture analysis was compared with visual MRI analysis for the diagnosis of skeletal muscle dystrophy in 14 healthy and 17 diseased subjects. MRI texture analysis was performed on 8 muscle regions of interest (ROI) using four statistical methods (histogram, co-occurrence matrix, gradient matrix, runlength matrix) and one structural (mathematical morphology) method. Nine senior radiologists assessed full leg transverse slice images and proposed a diagnosis. The 59 extracted texture parameters for each ROI were statistically analyzed by Correspondence Factorial Analysis. Non-parametric tests were used to compare diagnoses based on automated texture analysis and visual analysis. Texture analysis methods discriminated between healthy volunteers and patients with a sensitivity of 70%, and a specificity of 86%. Comparison with visual analysis of MR images suggests that texture analysis can provide useful information contributing to the diagnosis of skeletal muscle disease.