title: fMRI-based hierarchical SVM model for the classification and grading of liver fibrosis.
abstract: We present a novel method for the automatic classification and grading of liver fibrosis based on hepatic hemodynamic changes measured noninvasively from functional MRI (fMRI) scans combined with hypercapnia and hyperoxia. The supervised learning method automatically creates a classification and grading model for liver fibrosis grade from training datasets. It constructs a statistical model of liver fibrosis by evaluating the signal intensity time course and local variance in T2(*)-W fMRI scans acquired during the breathing of air, air-carbon dioxide, and carbogen with a hierarchical multiclass binary-based support vector machine (SVM) classifier. Two experimental studies on 162 slices from 34 mice with the hierarchical multiclass binary-based SVM classifier yield 96.9% separation accuracy between healthy and histological-based fibrosis graded subjects, and an overall accuracy of 75.3% for healthy, fibrotic, and cirrhotic subjects. These results outperform existing image-based methods that can discriminate between healthy and mild-grade fibrosis subjects.
authors.affiliation: School of Engineering and Computer Science, The Hebrew University of Jerusalem, Jerusalem 91904, Israel. yonsela@gmail.com
authors.forename: Yehonatan
authors.initials: Y
authors.lastname: Sela
authors.forename: Moti
authors.initials: M
authors.lastname: Freiman
authors.forename: Elia
authors.initials: E
authors.lastname: Dery
authors.forename: Yifat
authors.initials: Y
authors.lastname: Edrei
authors.forename: Rifaat
authors.initials: R
authors.lastname: Safadi
authors.forename: Orit
authors.initials: O
authors.lastname: Pappo
authors.forename: Leo
authors.initials: L
authors.lastname: Joskowicz
authors.forename: Rinat
authors.initials: R
authors.lastname: Abramovitch
mesh_terms: D000818:Animals; D016208:Databases, Factual; D004195:Disease Models, Animal; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008103:Liver Cirrhosis / Q000145:classification / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D051379:Mice; D012372:ROC Curve; D015203:Reproducibility of Results; D060388:Support Vector Machine