title: Identification of minimal hepatic encephalopathy in patients with cirrhosis based on white matter imaging and Bayesian data mining.
abstract: OBJECTIVE
  White matter abnormalities have been demonstrated to play an important role in minimal hepatic encephalopathy. In this study, we aimed to evaluate whether WM diffusion tensor imaging can be used to identify minimal hepatic encephalopathy among patients with cirrhosis.
  
  
  METHODS
  Our study included 65 patients with cirrhosis with covert hepatic encephalopathy (29 with minimal hepatic encephalopathy and 36 without hepatic encephalopathy). Participants underwent DTI, from which we generated mean diffusivity and fractional anisotropy maps. We used a Bayesian machine-learning technique, called Graphical-Model-based Multivariate Analysis, to determine WM regions that characterize group differences. To further test the clinical significance of these potential biomarkers, we performed Cox regression analysis to assess the potential of these WM regions in predicting survival.
  
  
  RESULTS
  In mean diffusivity or fractional anisotropy maps, 2 spatially distributed WM regions (predominantly located in the bilateral frontal lobes, corpus callosum, and parietal lobes) were consistently identified as differentiating minimal hepatic encephalopathy from no hepatic encephalopathy and yielded 75.4%-81.5% and 83.1%-92.3% classification accuracy, respectively. We were able to follow 55 of 65 patients (median = 18 months), and 15 of these patients eventually died of liver-related causes. Survival analysis indicated that mean diffusivity and fractional anisotropy values in WM regions were predictive of survival, in addition to the Child-Pugh score.
  
  
  CONCLUSIONS
  Our findings indicate that WM DTI can provide useful biomarkers differentiating minimal hepatic encephalopathy from no hepatic encephalopathy, which would be helpful for minimal hepatic encephalopathy detection and subsequent treatment.
authors.affiliation: From the Jiangsu Key Laboratory of Molecular and Functional Imaging (H.-J.C., M.Y., G.-J.T.), Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China Department of Radiology (H.-J.C.), The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
authors.forename: H-J
authors.initials: HJ
authors.lastname: Chen
authors.affiliation: Department of Diagnostic Radiology and Nuclear Medicine (R.C., E.H.H.), University of Maryland School of Medicine, Baltimore, Maryland.
authors.forename: R
authors.initials: R
authors.lastname: Chen
authors.affiliation: From the Jiangsu Key Laboratory of Molecular and Functional Imaging (H.-J.C., M.Y., G.-J.T.), Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China.
authors.forename: M
authors.initials: M
authors.lastname: Yang
authors.affiliation: From the Jiangsu Key Laboratory of Molecular and Functional Imaging (H.-J.C., M.Y., G.-J.T.), Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China ehh@ieee.org gjteng@vip.sina.com.
authors.forename: G-J
authors.initials: GJ
authors.lastname: Teng
authors.affiliation: Department of Diagnostic Radiology and Nuclear Medicine (R.C., E.H.H.), University of Maryland School of Medicine, Baltimore, Maryland ehh@ieee.org gjteng@vip.sina.com.
authors.forename: E H
authors.initials: EH
authors.lastname: Herskovits
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D015415:Biomarkers; D002648:Child; D015897:Comorbidity; D003337:Corpus Callosum / Q000473:pathology; D057225:Data Mining; D056324:Diffusion Tensor Imaging; D005260:Female; D005625:Frontal Lobe / Q000473:pathology; D006501:Hepatic Encephalopathy / Q000175:diagnosis* / Q000453:epidemiology / Q000473:pathology; D006801:Humans; D008103:Liver Cirrhosis / Q000453:epidemiology / Q000473:pathology; D008297:Male; D008875:Middle Aged; D010296:Parietal Lobe / Q000473:pathology; D066127:White Matter / Q000473:pathology*
chemical_list: D015415:Biomarkers