Purpose To determine the accuracy, reproducibility, and intra- and interobserver agreement of a computer-based quantitative method to measure liver surface nodularity (LSN) from routine computed tomographic (CT) images as a biomarker for detection and evaluation of cirrhosis. Materials and Methods For this institutional review board-approved HIPAA-compliant retrospective study, adult patients with healthy livers (n = 24) or various stages of hepatitis C virus-induced chronic liver disease (n = 70) with routine nonenhanced and portal venous phase contrast agent-enhanced liver CT imaging with thick-section (5.0 mm) and thin-section (1.25-1.50 mm) axial images obtained between January 1, 2006, and March 31, 2011, were identified from the electronic medical records. A computer algorithm was developed to measure LSN and derive a score. LSN scores, splenic volume, and the ratio of left lateral segment (LLS) to total liver volume (TLV) were measured from the same multiphasic liver CT examinations. Accuracy for differentiating cirrhotic from noncirrhotic livers was assessed by area under the receiver operating characteristic curve. Intra- and interobserver agreement was assessed by intraclass correlation coefficient. Results Median LSN scores from nonenhanced thick-section CT images in cirrhotic livers (3.16; 56 livers) were significantly higher than in noncirrhotic livers (2.11; 38 livers; P < .001). LSN scores from the four CT imaging types (94 patients for each type) were very strongly correlated (range of Spearman r, 0.929-0.960). LSN scores from portal venous phase contrast-enhanced thick-section CT images had significantly higher accuracy (area under the receiver operating characteristic curve, 0.929) than splenic volume (area under the receiver operating characteristic curve, 0.835) or LLS-to-TLV ratio measurements (area under the receiver operating characteristic curve, 0.753) for differentiating cirrhotic from noncirrhotic livers (P = .038 and .003, respectively; n = 94). Intra- and interobserver agreements that used nonenhanced thick CT images were very good (intraclass correlation coefficient, 0.963 and 0.899, respectively). Conclusion Quantitative measurement of LSN on routine CT images accurately differentiated cirrhotic from noncirrhotic livers and was highly reproducible. (©) RSNA, 2016 Online supplemental material is available for this article.

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.

Purpose To determine the accuracy and the effect of possible subject-based confounders of magnitude-based magnetic resonance imaging (MRI) for estimating hepatic proton density fat fraction (PDFF) for different numbers of echoes in adults with known or suspected nonalcoholic fatty liver disease, using MR spectroscopy (MRS) as a reference. Materials and Methods In this retrospective analysis of 506 adults, hepatic PDFF was estimated by unenhanced 3.0T MRI, using right-lobe MRS as reference. Regions of interest placed on source images and on six-echo parametric PDFF maps were colocalized to MRS voxel location. Accuracy using different numbers of echoes was assessed by regression and Bland–Altman analysis; slope, intercept, average bias, and R2 were calculated. The effect of age, sex, and body mass index (BMI) on hepatic PDFF accuracy was investigated using multivariate linear regression analyses. Results MRI closely agreed with MRS for all tested methods. For three- to six-echo methods, slope, regression intercept, average bias, and R2 were 1.01–0.99, 0.11–0.62%, 0.24–0.56%, and 0.981–0.982, respectively. Slope was closest to unity for the five-echo method. The two-echo method was least accurate, underestimating PDFF by an average of 2.93%, compared to an average of 0.23–0.69% for the other methods. Statistically significant but clinically nonmeaningful effects on PDFF error were found for subject BMI (P range: 0.0016 to 0.0783), male sex (P range: 0.015 to 0.037), and no statistically significant effect was found for subject age (P range: 0.18–0.24). Conclusion Hepatic magnitude-based MRI PDFF estimates using three, four, five, and six echoes, and six-echo parametric maps are accurate compared to reference MRS values, and that accuracy is not meaningfully confounded by age, sex, or BMI.

Purpose To assess accuracy of magnitude-based magnetic resonance imaging (M-MRI) in children to estimate hepatic proton density fat fraction (PDFF) using two to six echoes, with magnetic resonance spectroscopy (MRS)-measured PDFF as a reference standard. Materials and Methods This was an IRB-approved, HIPAA-compliant, single-center, cross-sectional, retrospective analysis of data collected prospectively between 2008 and 2013 in children with known or suspected non-alcoholic fatty liver disease (NAFLD). Two hundred and eighty-six children (8 – 20 [mean 14.2 ± 2.5] yrs; 182 boys) underwent same-day MRS and M-MRI. Unenhanced two-dimensional axial spoiled gradient-recalled-echo images at six echo times were obtained at 3T after a single low-flip-angle (10°) excitation with ≥ 120-ms recovery time. Hepatic PDFF was estimated using the first two, three, four, five, and all six echoes. For each number of echoes, accuracy of M-MRI to estimate PDFF was assessed by linear regression with MRS-PDFF as reference standard. Accuracy metrics were regression intercept, slope, average bias, and R2. Results MRS-PDFF ranged from 0.2 – 40.4% (mean 13.1 ± 9.8%). Using three to six echoes, regression intercept, slope, and average bias were 0.46 – 0.96%, 0.99 – 1.01, and 0.57 – 0.89%, respectively. Using two echoes, these values were 2.98%, 0.97, and 2.72%, respectively. R2 ranged 0.98 – 0.99 for all methods. Conclusion Using three to six echoes, M-MRI has high accuracy for hepatic PDFF estimation in children.

The software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability.

Transarterial radioembolization using yttrium-90 microspheres is an established and effective treatment for liver malignancies. Determining response to this treatment is difficult due to the radical changes that occur in tissue as a response to radiation. Though accurate assessment of treatment response is paramount for proper patient disposition, there is currently no standardized assessment protocol. Current methods of assessment often consider changes in size, necrosis, vascularity, fluorodeoxyglucose-positron emission tomography FDG-PET metabolic activity, and diffusion using diffusion-weighted magnetic resonance imaging (DWI). Current methods of assessment require a lag time of one to two months post-treatment to determine treatment effectiveness. This delay is a hindrance to obtaining better patient outcomes, giving rise to a need to identify markers for faster determination of treatment efficacy.

In patients undergoing Gx-enhanced MR exams, PDFF estimation accuracy of MRI-M can be improved by using high-FA on post-contrast images.

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