Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI

Abstract

Purpose To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Materials and Methods Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws? features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Results Histogram features demonstrated very weak to moderate correlations (r=-0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r=-0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r=-0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r=-0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws? features L6 and L7 (r=0.58). Conclusion This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis.