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The Pallidal Index in Patients with Acute-on-Chronic Liver Disease: Is It a Predictor of Severe Hepatic Encephalopathy?

  • Lee, Dong Hyun (Department of Radiology, Kyungpook National University Hospital) ;
  • Lee, Hui Joong (Department of Radiology, Kyungpook National University Hospital) ;
  • Hahm, Myong Hun (Department of Radiology, Kyungpook National University Hospital)
  • Received : 2017.08.02
  • Accepted : 2017.09.20
  • Published : 2017.09.30

Abstract

Purpose: To evaluate the clinical significance of T1 high signal intensity on the globus pallidus as a predictor of severe hepatic encephalopathy in patients with acute-on-chronic liver failure (ACLF), which is a distinct syndrome characterized by multi-organ dysfunction including cerebral failure. Materials and Methods: From January 2002 to April 2014, we retrospectively reviewed the magnetic resonance imaging (MRI) findings and clinical and magnetic resonance (MR) features of 74 consecutive patients (44 men and 30 women; mean age, 59.5 years) with liver cirrhosis. The chronic liver failure-sequential organ failure assessment score was used to diagnose ACLF. The pallidal index (PI), calculated by dividing the mean signal intensity of the globus pallidus by that of the subcortical frontal white matter were compared according to ACLF. The PI was compared with the Model for End-Stage Liver Disease (MELD) score in predicting the development of ACLF. Results: Fifteen patients who were diagnosed with ACLF had higher hepatic encephalopathy grades (initial, P = 0.024; follow-up, P = 0.002), MELD scores (P < 0.001), and PI (P = 0.048). In the ACLF group, the mean PI in patients with cerebral failure was significantly higher than that in the patients without cerebral failure (1.33 vs. 1.20, P = 0.039). In patients with ACLF, the area under the curve (AUC) for PI was 0.680 (95% confidence intervals [CI], 0.52-0.85), which was significantly lower than that for the MELD score (AUC, 0.88; 95% CI, 0.77-0.99) (P = 0.04). Conclusion: The PI can be an ancillary biomarker for predicting the development of ACLF and severe hepatic encephalopathy.

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