title: Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.
abstract: OBJECTIVE
  To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis.
  
  
  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).
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Radiology, Boston University Medical Center, Boston, Massachusetts, USA.
authors.forename: HeiShun
authors.initials: H
authors.lastname: Yu
authors.affiliation: Department of Radiology, Boston University Medical Center, Boston, Massachusetts, USA.
authors.forename: Karen
authors.initials: K
authors.lastname: Buch
authors.affiliation: Department of Radiology, Boston University Medical Center, Boston, Massachusetts, USA.
authors.forename: Baojun
authors.initials: B
authors.lastname: Li
authors.affiliation: Department of Pathology and Laboratory Medicine, Boston University Medical Center, Boston, Massachusetts, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: O'Brien
authors.affiliation: Department of Radiology, Boston University Medical Center, Boston, Massachusetts, USA.
authors.forename: Jorge
authors.initials: J
authors.lastname: Soto
authors.affiliation: Department of Radiology, Boston University Medical Center, Boston, Massachusetts, USA.
authors.forename: Hernan
authors.initials: H
authors.lastname: Jara
authors.affiliation: Department of Radiology, Boston University Medical Center, Boston, Massachusetts, USA.
authors.forename: Stephan W
authors.initials: SW
authors.lastname: Anderson
mesh_terms: D000465:Algorithms; D000818:Animals; D004195:Disease Models, Animal; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000473:pathology; D008103:Liver Cirrhosis / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D011522:Protons; D015203:Reproducibility of Results
chemical_list: D011522:Protons
keywords: cirrhosis; hepatic fibrosis; proton density; texture analysis