Liver Surface Nodularity Score Allows Prediction of Cirrhosis Decompensation and Death.
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.
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Andrew D
AD
Smith
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Kevin A
KA
Zand
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Edward
E
Florez
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Reza
R
Sirous
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Darya
D
Shlapak
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Frederico
F
Souza
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Manohar
M
Roda
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Jason
J
Bryan
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Amit
A
Vasanji
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Michael
M
Griswold
From the Departments of Radiology (A.D.S., K.A.Z., E.F., R.S., D.S., F.S., M.R.) and Data Science (M.G., S.T.L.), University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216; and ImageIQ, Cleveland, Ohio (J.B., A.V.).
Seth T
ST
Lirette
D005260:Female; D006801:Humans; D008099:Liver / Q000000981:diagnostic imaging* / Q000473:pathology; D008103:Liver Cirrhosis / Q000150:complications / Q000000981:diagnostic imaging* / Q000401:mortality* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed