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

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.