Liver Surface Nodularity Score Allows Prediction of Cirrhosis Decompensation and Death

Abstract

Purpose To determine whether use of the liver surface nodularity (LSN) score, a quantitative biomarker derived from routine computed tomographic (CT) images, allows prediction of cirrhosis decompensation and death. Materials and Methods For this institutional review board-approved HIPAA-compliant retrospective study, adult patients with cirrhosis and Model for End-Stage Liver Disease (MELD) score within 3 months of initial liver CT imaging between January 3, 2006, and May 30, 2012, were identified from electronic medical records (n = 830). The LSN score was measured by using CT images and quantitative software. Competing risk regression was used to determine the association of the LSN score with hepatic decompensation and overall survival. A risk model combining LSN scores (<3 or ≥3) and MELD scores (<10 or ≥10) was created for predicting liver-related events. Results In patients with compensated cirrhosis, 40% (129 of 326) experienced decompensation during a median follow-up period of 4.22 years. After adjustment for competing risks including MELD score, LSN score (hazard ratio, 1.38; 95% confidence interval: 1.06, 1.79) was found to be independently predictive of hepatic decompensation. Median times to decompensation of patients at high (1.76 years, n = 48), intermediate (3.79 years, n = 126), and low (6.14 years, n = 152) risk of hepatic decompensation were significantly different (P < .001). Among the full cohort with compensated or decompensated cirrhosis, 61% (504 of 830) died during the median follow-up period of 2.26 years. After adjustment for competing risks, LSN score (hazard ratio, 1.22; 95% confidence interval: 1.11, 1.33) and MELD score (hazard ratio, 1.08; 95% confidence interval: 1.06, 1.11) were found to be independent predictors of death. Median times to death of patients at high (0.94 years, n = 315), intermediate (2.79 years, n = 312), and low (4.69 years, n = 203) risk were significantly different (P < .001). Conclusion The LSN score derived from routine CT images allows prediction of cirrhosis decompensation and death. RSNA, 2016 Online supplemental material is available for this article.

Detection of liver fibrosis using qualitative and quantitative MR elastography compared to liver surface nodularity measurement, gadoxetic acid uptake, and serum markers

“…Despite these promising results, only a few studies have compared the diagnostic performance of mpMRI for liver fibrosis staging, showing greater performance of MRE against morphologic criteria 4,5 and DCE-MRI and DWI, 6,7 with improved detection of liver fibrosis and cirrhosis when using a multiparametric approach. 10 This LSN software has shown promising results for the detection of liver fibrosis 10,11 and prediction of hepatic decompensation, 12 mostly using computed tomography (CT). 4,5 A recent study introduced a novel noninvasive method of objectively quantifying liver surface nodularity (LSN) by applying semiautomated software.…”

“…4,5 A recent study introduced a novel noninvasive method of objectively quantifying liver surface nodularity (LSN) by applying semiautomated software. 10 This LSN software has shown promising results for the detection of liver fibrosis 10,11 and prediction of hepatic decompensation, 12 mostly using computed tomography (CT).…”

Multidetector computed tomography for assessment of hepatic fibrosis

“…Mean LSN scores were significantly higher in patients with cirrhosis than in control patients, with an ROC AUC of 0.93 for identifying cirrhosis. In a follow‐up study, LSN was found to be an independent predictor of decompensation and death in patients with cirrhosis . In addition, LSN has shown utility in identifying patients with intermediate stages of fibrosis.…”

“…In a follow-up study, LSN was found to be an independent predictor of decompensation and death in patients with cirrhosis. 16 In addition, LSN has shown utility in identifying patients with intermediate stages of fibrosis. LSN scores increase with increasing stage of fibrosis, and for discriminating significant fibrosis (F2), advanced fibrosis (F3) and cirrhosis demonstrated ROC AUCs of 0.90, 0.93, and 0.96, respectively, in one study.…”

Relevance of liver surface nodularity for preoperative risk assessment in patients with resectable hepatocellular carcinoma

“…Quantification of liver surface nodularity (LSN) is a novel simple and reproducible non‐invasive CT‐based method, which measures irregularities on the liver surface on CT images. In previous investigations, LSN measurement allowed accurate differentiation between cirrhotic and non‐cirrhotic livers, and detection of CSPH in patients with cirrhosis. As LSN measurement may detect minimal to significant architectural changes to the parenchyma it could capture non‐cirrhotic (mild fibrosis, steatohepatitis) and cirrhotic parenchymal changes frequently observed in patients with HCC.…”