Liver Surface Nodularity Score Research Articles

Reproducibility of MRI-derived liver surface nodularity score: analysis of patients with repeated MRI in various scanners.

To assess trans-regional differences, reproducibility across different MRI scanners, and interobserver agreement of liver surface nodularity (LSN) score from routine liver MRI and to evaluate the correlation between LSN score and liver stiffness (LS) value on MR elastography. Ninety patients who underwent gadoxetic acid-enhanced liver MRI twice using different MRI scanners within a year were evaluated. On axial hepatobiliary phase images, right anterior (LSNRT_ANT), right posterior (LSNRT_POST), and left anterior hepatic surface (LSNLT) were chosen for the quantification of LSN score. Repeated-measures ANOVA, paired t test, Pearson's correlation coefficient analysis, and intraclass correlation coefficient (ICC) were used for statistical analysis. LSN scores from high to low were LSNRT_POST, LSNRT_ANT, and LSNLT, representing trans-regional differences (p < 0.001). Reproducibility of LSN measurement across different MRI scanners was high to excellent (ICC = 0.838-0.921). The mean difference between first and second examinations in LSNRT_ANT, LSNRT_POST, and LSNLT were 0.032 (p = 0.013), 0.002 (p = 0.910), and 0.010 (p = 0.285) for reader 1 and 0.051 (p = 0.004), 0.061 (p = 0.002), and 0.023 (p = 0.005) for reader 2. The first and second examinations were highly correlated in all hepatic regions (r = 0.712-0.839, p < 0.001). There was a low to moderate correlation between LSN score and LS value (r = 0.364-0.592, p ≤ 0.001), which was higher in the chronic hepatitis B (CHB) group than in the non-CHB group in all hepatic regions. In our study, LSN measurement on liver MRI showed trans-regional differences and excellent reproducibility across different MRI scanners. To use LSN score more widely, standardization of quantification software and selected hepatic regions is needed.

Development and validation of a management system and dataset quality assessment tool for the Radiology Common Data Model (R_CDM): A case study in liver disease

BackgroundThe Observational Medical Outcomes Partnership—Common Data Model (OMOP-CDM), a distributed research network, has low clinical data coverage. Radiological data are valuable, but imaging metadata are often incomplete, and a standardized recording format in the OMOP-CDM is lacking. We developed a web-based management system and data quality assessment (RQA) tool for a radiology_CDM (R_CDM) and evaluated the feasibility of clinically applying this dataset. MethodsWe designed an R_CDM with Radiology_Occurrence and Radiology_Image tables. This was seamlessly linked to the OMOP-CDM clinical data. We adopted the standardized terminology using the RadLex playbook and mapped 5,753 radiology protocol terms to the OMOP vocabulary. An extract, transform, and load (ETL) process was developed to extract detailed information that was difficult to extract from metadata and to compensate for missing values. Image-based quantification was performed to measure liver surface nodularity (LSN), using customized Wonkwang abdomen and liver total solution (WALTS) software. ResultsOn a PACS, 368,333,676 DICOM files (1,001,797 cases) were converted to R_CDM chronic liver disease (CLD) data (316,596 MR images, 228 cases; 926,753 CT images, 782 cases) and uploaded to a web-based management system. Acquisition date and resolution were extracted accurately, but other information, such as “contrast administration status” and “photography direction”, could not be extracted from the metadata. Using WALTS, 9,609 pre-contrast axial-plane abdominal MR images (197 CLD cases) were assigned LSN scores by METAVIR fibrosis grades, which differed significantly by ANOVA (p < 0.001). The mean RQA score (83.5) indicated good quality. ConclusionThis study developed a web-based system for management of the R_CDM dataset, RQA tool, and constructed a CLD R_CDM dataset, with good quality for clinical application. Our management system and R_CDM CLD dataset would be useful for multicentric and image-based quantification researches.

Multiinstitutional Evaluation of the Liver Surface Nodularity Score on CT for Staging Liver Fibrosis and Predicting Liver-Related Events in Patients With Hepatitis C.

BACKGROUND. In single-institution multireader studies, the liver surface nodularity (LSN) score accurately detects advanced liver fibrosis and cirrhosis and predicts liver decompensation in patients with chronic liver disease (CLD) from hepatitis C virus (HCV). OBJECTIVE. The purpose of this study was to assess the diagnostic performance of the LSN score alone and in combination with the (FIB-4; fibrosis index based on four factors) to detect advanced fibrosis and cirrhosis and to predict future liver-related events in a multiinstitutional cohort of patients with CLD from HCV. METHODS. This retrospective study included 40 consecutive patients, from each of five academic medical centers, with CLD from HCV who underwent nontargeted liver biopsy within 6 months before or after abdominal CT. Clinical data were recorded in a secure web-based database. A single central reader measured LSN scores using software. Diagnostic performance for detecting liver fibrosis stage was determined. Multivariable models were constructed to predict baseline liver decompensation and future liver-related events. RESULTS. After exclusions, the study included 191 patients (67 women, 124 men; mean age, 54 years) with fibrosis stages of F0-F1 (n = 37), F2 (n = 44), F3 (n = 46), and F4 (n = 64). Mean LSN score increased with higher stages (F0-F1, 2.26 ± 0.44; F2, 2.35 ± 0.37; F3, 2.42 ± 0.38; F4, 3.19 ± 0.89; p < .001). The AUC of LSN score alone was 0.87 for detecting advanced fibrosis (≥ F3) and 0.89 for detecting cirrhosis (F4), increasing to 0.92 and 0.94, respectively, when combined with FIB-4 scores (both p = .005). Combined scores at optimal cutoff points yielded sensitivity of 75% and specificity of 82% for advanced fibrosis, and sensitivity of 84% and specificity of 85% for cirrhosis. In multivariable models, LSN score was the strongest predictor of baseline liver decompensation (odds ratio, 14.28 per 1-unit increase; p < .001) and future liver-related events (hazard ratio, 2.87 per 1-unit increase; p = .03). CONCLUSION. In a multiinstitutional cohort of patients with CLD from HCV, LSN score alone and in combination with FIB-4 score exhibited strong diagnostic performance in detecting advanced fibrosis and cirrhosis. LSN score also predicted future liver-related events. CLINICAL IMPACT. The LSN score warrants a role in clinical practice as a quantitative marker for detecting advanced liver fibrosis, compensated cirrhosis, and decompensated cirrhosis and for predicting future liver-related events in patients with CLD from HCV.

Performance of non-invasive biomarkers compared with invasive methods for risk prediction of posthepatectomy liver failure in hepatocellular carcinoma.

Posthepatectomy liver failure (PHLF) is a rare but dreaded complication. The aim was to test whether a combination of non-invasive biomarkers (NIBs) and CT data could predict the risk of PHLF in patients who underwent resection of hepatocellular carcinoma (HCC). Patients with HCC who had liver resection between 2012 and 2020 were included. A relevant combination of NIBs (NIB model) to model PHLF risk was identified using a doubly robust estimator (inverse probability weighting combined with logistic regression). The adjustment variables were body surface area, ASA fitness grade, male sex, future liver remnant (FLR) ratio, difficulty of liver resection, and blood loss. The reference invasive biomarker (IB) model comprised a combination of pathological analysis of the underlying liver and hepatic venous pressure gradient (HVPG) measurement. Various NIB and IB models for prediction of PHLF were fitted and compared. NIB model performances were validated externally. Areas under the curve (AUCs) were corrected using bootstrapping. Overall 323 patients were included. The doubly robust estimator showed that hepatitis C infection (odds ratio (OR) 4.33, 95 per cent c.i. 1.29 to 9.20; P = 0.001), MELD score (OR 1.26, 1.04 to 1.66; P = 0.001), fibrosis-4 score (OR 1.36, 1.06 to 1.85; P = 0.001), liver surface nodularity score (OR 1.55, 1.28 to 4.29; P = 0.031), and FLR volume ratio (OR 0.99, 0.97 to 1.00; P = 0.014) were associated with PHLF. Their combination (NIB model) was fitted externally (2-centre cohort, 165 patients) to model PHLF risk (AUC 0.867). Among 129 of 323 patients who underwent preoperative HVPG measurement, NIB and IB models had similar performances (AUC 0.753 versus 0.732; P = 0.940). A well calibrated nomogram was drawn based on the NIB model (AUC 0.740). The risk of grade B/C PHLF could be ruled out in patients with a cumulative score of less than 160 points. The NIB model provides reliable preoperative evaluation with performance at least similar to that of invasive methods for PHLF risk prediction.

Intraindividual comparison of MRI-derived liver surface nodularity score at 1.5T and 3T.

To compare the MRI-derived liver surface nodularity (LSN) scores acquired on both 1.5T and 3T. Forty chronic liver disease patients who underwent gadoxetic acid-enhanced MRI at both 1.5 and 3T were included. Axial hepatobiliary phase images with the same voxel size were used to calculate the LSN score in both liver lobes with a quantitative software. Rank correlation, Wilcoxon test, and Bland-Altman limits of agreement were used for statistical analysis. There was a weak correlation between the right and left liver lobe on 1.5T (rs = 0.331, p = 0.037) and 3T (rs = 0.381, p = 0.015). The correlation between 1.5T and 3T on both liver lobes showed a very strong correlation (right, rs = 0.927, p < 0.001; left, rs = 0.845, p < 0.001). LSN scores differed significantly between both lobes on 1.5T (median, 1.201 vs. 0.674, right vs. left) and 3T (1.076 vs. 0.592) (all p < 0.001). LSN scores differed significantly between 1.5T and 3T on both lobes (all p < 0.001). The Bland-Altman plot comparing 1.5T and 3T on right and left liver lobes showed a systemic bias of 0.08 and 0.07, respectively. LSN scores differed significantly on 1.5T vs. 3T and right vs. left liver lobe. Caution should be made when comparing LSN scores derived from different field strengths or the hepatic lobe. Interplatform, interlobar reproducibility should be resolved to use LSN scores, which is relatively easy to perform without additional hardware or images.

Diagnostic performance of liver fibrosis assessment by quantification of liver surface nodularity on computed tomography and magnetic resonance imaging: systematic review and meta-analysis.

To determine the diagnostic performance of the liver surface nodularity (LSN) score for assessment of hepatic fibrosis. Major databases were searched to identify studies reporting the diagnostic performance of the LSN score published from January 2011 to April 2021. The pooled sensitivity and specificity of the LSN score in the diagnosis of significant fibrosis (F2-4), advanced fibrosis (F3-4), and liver cirrhosis (F4) were calculated using a bivariate random-effects model, and the summary areas under the hierarchical summary receiver operating characteristics curve (AUC) for each were calculated. Subgroup analysis was performed to explore the causes of study heterogeneity. Of 168 screened studies, six were included in the analysis. The pooled sensitivity, specificity, and AUC of the LSN score were 68% (95% confidence interval [CI], 45-84%), 89% (95% CI, 83-93%), and 0.90 (95% CI, 0.87-0.92), respectively, for the diagnosis of significant fibrosis; 88% (95% CI, 60-97%), 78% (95% CI, 57-90%), and 0.89 (95% CI, 0.86-0.91), respectively, for the diagnosis of advanced fibrosis; and 83% (95% CI, 71-91%), 80% (95% CI, 72-85%), and 0.87 (95% CI, 0.83-0.89), respectively, for the diagnosis of liver cirrhosis. Cutoff values of the LSN score affected study heterogeneity in the diagnosis of advanced fibrosis (p = 0.03) and liver cirrhosis (p = 0.01). Imaging modality (p = 0.01) and reference standard (p = 0.01) affected study heterogeneity in the diagnosis of liver cirrhosis. The LSN score showed good diagnostic performance in assessing the hepatic fibrosis stage. Additional investigations are needed to improve and standardize the LSN score. Key Points • The liver surface nodularity (LSN) score showed overall good diagnostic performance in assessing hepatic fibrosis. • The pooled sensitivity of the LSN score was highest in the diagnosis of advanced fibrosis (88%; 95% confidence interval [CI], 60-97%), and the pooled specificity was highest in the diagnosis of significant fibrosis (89%; 95% CI, 83-93%). • The diagnostic performance of the LSN score differed according to the cutoff value, imaging modality, and reference standard.

Quantitative liver surface nodularity score based on imaging for assessment of early cirrhosis in patients with chronic liver disease: A protocol for systematic review and meta-analysis.

Background:Early stage of cirrhosis is of great value in the diagnosis and management in patients with chronic liver disease (CLD). Recent studies have shown that quantitative liver surface nodularity (LSN) score based on imaging techniques can be used to predict the early cirrhosis stage noninvasively, with varied diagnostic accuracy and limited sample size. Hence, this study will evaluate the diagnostic accuracy of LSN in the prediction of early cirrhosis.Methods:We will conduct a comprehensive search in PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases to identify eligible studies. The literature screening, data extraction, data analysis, and quality assessment will then be carried out. The summary receiver-operating-characteristic (ROC) and pooled sensitivity, specificity will be calculated to summarize the diagnostic performance of LSN using a random-effect model. A meta-regression analysis will be performed to investigate the underlying cause of the heterogeneity.Results:This study will evaluate the diagnostic accuracy of LSN score in the identification of early cirrhosis, which may further determine whether this method can be used as an alternative in the assessment of CLD patients.Conclusions:This study will help to determine the diagnostic accuracy and summarize the recent evidence on this issue.Study registration:INPLASY2020100096.

Computed Tomography-Derived Liver Surface Nodularity and Sarcopenia as Prognostic Factors in Patients with Resectable Metabolic Syndrome-Related Hepatocellular Carcinoma.

The aim of this study was to assess the prognostic value of liver surface nodularity (LSN) and sarcopenia from preoperative computed tomography (CT) in patients with resectable metabolic syndrome (MS)-related hepatocellular carcinoma (HCC). Patients with MS undergoing hepatectomy for HCC between 2006 and 2018 at a single center were retrospectively analyzed. LSN and sarcopenia were assessed on preoperative CT scans, and their association with severe (Clavien-Dindo grade 3-5) postoperative complications was analyzed on multivariate analysis. The influence of LSN and sarcopenia on overall survival (OS) and recurrence-free survival (RFS) was assessed. Overall, 110 patients (92 men [84%], mean 67.7 ± 7.7years of age) were analyzed. Severe postoperative complications occurred in 34/110 (31%) patients. Patients with severe complications had a significantly higher LSN score (area under the receiver operating characteristic curve 0.68 ± 0.05, optimal cut-off > 2.50) and were more frequently sarcopenic (47% vs. 13% without major complications, p < 0.001). Multivariate analysis identified sarcopenia (odds ratio [OR] 6.51, 95% confidence interval [CI] 2.08-20.39; p < 0.001), LSN > 2.50 (OR 7.05, 95% CI 2.13-23.35; p < 0.001), and preoperative portal vein embolization (PVE; OR 6.06, 95% CI 1.71-21.48; p = 0.005) as independent predictors of severe complications. LSN and sarcopenia had no influence on OS. Stratification according to a combination of LSN > 2.50 and sarcopenia predicted the risk of severe postoperative complications from 7% (no sarcopenia and LSN ≤2.50) to 71% (sarcopenia and LSN > 2.50; p < 0.001), as well as RFS from 61months (95% CI 40-82) to 17months (95% CI 9-25; p = 0.033). Results remained significant in 52 patients without advanced fibrosis. The combination of LSN and sarcopenia derived from routine preoperative CT seems to help predict severe postoperative complications and stratification of RFS in patients with MS and resectable HCC.

Diagnostic value of MRI-derived liver surface nodularity score for the non-invasive quantification of hepatic fibrosis in non-alcoholic fatty liver disease.

To assess the accuracy of MRI-derived liver surface nodularity (LSN) score for staging of hepatic fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). Forty-seven patients with clinicopathological diagnosis of NAFLD who underwent 1.5-T liver MRI within 12months of liver biopsy were included. Axial non-contrast T1-weighted 3D GRE was used for image analysis. LSN of the left lobe was measured using a custom semiautomated software. Histopathologic analysis (F0-F4) served as the reference standard for staging of fibrosis. Mann-Whitney test and Spearman's correlation coefficient were used to compare LSN scores between different stages of fibrosis and to assess the correlation. Diagnostic performance of LSN score for detection of significant (F2-F4) and advanced (F3-F4) fibrosis was assessed by receiver operating characteristics (ROC) curve. p value of less than 0.05 was considered statistically significant different. Twenty-one subjects had advanced fibrosis. The LSN scores among different stages of fibrosis were significantly different (p < 0.001). The correlation between LSN score and stage of fibrosis was also strong (ρ = 0.71; p < 0.001). The areas under ROC curves for detection of significant and advanced fibrosis were 0.80 (95% CI 0.66-0.95) and 0.86 (95% CI 0.75-0.97), using a threshold of 2.23 and 2.44, respectively. This method showed 81% sensitivity and 88% specificity for detection of advanced fibrosis. MR-based LSN score is a promising non-invasive objective tool for detection of advanced fibrosis in patients with NAFLD. • Liver surface nodularity (LSN) score is a fast retrospective method for precise quantification of nodularity of liver surface. • MR-based LSN score is a promising non-invasive objective tool to accurately detect different stages of fibrosis in patients with non-alcoholic fatty liver disease (NAFLD).

Staging of Liver Fibrosis by Means of Semiautomatic Measurement of Liver Surface Nodularity in MRI

OBJECTIVE. The purposes of this study were to evaluate the accuracy of a semiautomatic method of measuring liver surface nodularity (LSN) on contrast-enhanced MR images and to compare the LSN score with pathologic fibrosis stage. MATERIALS AND METHODS. This retrospective study included patients who had undergone gadoxetate disodium-enhanced liver MRI 6 months before or after histopathologic investigation including percutaneous parenchymal biopsy and surgical biopsy for staging of chronic liver disease between January 2010 and December 2018. Semiautomated LSN quantification software was developed to measure LSN at MRI. Aspartate aminotransferase to platelet ratio index and fibrosis-4 index were derived from serum laboratory test results. The reference standard for staging of liver fibrosis was Metavir score. The accuracy of LSN score for staging of liver fibrosis was evaluated with AUC, and the optimal cutoff value was calculated by Youden index. Spearman correlation coefficient was used for correlation analysis. RESULTS. The study included 132 patients (93 men, 39 women). LSN score was evaluated without technical failure. There was high correlation between LSN score and Metavir score (Spearman ρ = 0.713, p < 0.001). The AUCs of LSN score for distinguishing Metavir score were 0.93 for F0-F1 versus F2-F4 (95% CI, 0.88-0.97; p < 0.001), 0.98 for F0-F2 vs F3-F4 (95% CI, 0.95-1.00; p < 0.001), and 0.83 for F0-F3 versus F4 (95% CI, 0.76-0.90; p < 0.001). The optimal cutoff value for differentiating F0-F2 from F3-F4 was 0.850 with 100% sensitivity and 85.4% specificity. CONCLUSION. LSN score calculated semiautomatically from MR images of the liver has high accuracy and correlates directly with the pathologic fibrosis stage.

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

Quantification of liver surface nodularity (LSN) on routine preoperative CT images allows detection of cirrhosis and clinically significant portal hypertension. This study aimed to assess the relevance of LSN in preoperative assessment of operative risks for patients with resectable hepatocellular carcinoma (HCC). All patients undergoing hepatectomy for HCC between 2012 and 2017 were analysed retrospectively. LSN was assessed at the liver-fat interface on the left liver lobe on preoperative CT images. The feasibility of LSN quantification was assessed. The association between LSN and outcomes (severe complications and posthepatectomy liver failure (PHLF)) was evaluated by multivariable analysis and after propensity score matching. Among 210 patients, LSN measurement was successful in 187 (89·0 per cent). Among these, the median LSN score was 2·42 (i.q.r. 2·21-2·66) and 52·9 per cent had severe fibrosis, including 33·7 per cent with cirrhosis. LSN score increased with hepatic venous pressure gradient (P = 0·048), severity of steatosis (P = 0·011) and fibrosis grade (P = 0·001). LSN score was independently associated with severe complications (odds ratio (OR) 5·25; P = 0·006) and PHLF (OR 6·78; P = 0·003). After matching with respect to model for end-stage liver disease, aspartate aminotransferase-to-platelet ratio index and fibrosis-4 score, patients with a LSN score of 2·63 or higher retained an increased risk of PHLF (OR 5·81; P = 0·018). In the subgroup of patients without severe fibrosis, LSN was accurate in predicting severe complications (P = 0·005). Patients with (P = 0·039) or without (P = 0·018) severe fibrosis with increased LSN score had a higher comprehensive complication index score. Among patients with cirrhosis who had clinically significant portal hypertension, a LSN value below 2·63 ruled out the risk of PHLF. LSN measurement represents a practical tool that may allow improvement in the preoperative evaluation and management of patients with HCC.

Development of liver surface nodularity quantification program and its clinical application in nonalcoholic fatty liver disease

The liver morphological changes in relation to fibrosis stage in nonalcoholic fatty liver disease (NAFLD) have not yet been clearly understood. This study was to develop a liver surface nodularity (LSN) quantification program and to compare the fibrosis grades in simple steatosis (SS) and nonalcoholic steatohepatitis (NASH). Thirty subjects (7 normal controls [NC], 12 SS and 11 NASH) were studied. LSN quantification procedure was bias correction, boundary detection, segmentation and LSN measurement. LSN scores among three groups and fibrosis grades compared using Kruskal–Wallis H test. Diagnostic accuracy was determined by calculating the area under the receiver operating characteristics (ROC) curve. Mean LSN scores were NC 1.30 ± 0.09, SS 1.54 ± 0.21 and NASH 1.59 ± 0.23 (p = 0.008). Mean LSN scores according to fibrosis grade (F) were F0 1.30 ± 0.09, F1 1.45 ± 0.17 and F2&F3 1.67 ± 0.20 (p = 0.001). The mean LSN score in F2&F3 is significantly higher than that in F1 (p = 0.019). The AUROC curve to distinguish F1 and F2&F3 was 0.788 (95% CI 0.595–0.981, p = 0.019) at a cut-off LSN score greater than 1.48, and its diagnostic accuracy had 0.833 sensitivity and 0.727 specificity. This study developed LSN program and its clinical application demonstrated that the quantitative LSN scores can help to differentially diagnose fibrosis stage in NAFLD.

Current Imaging Techniques for Noninvasive Staging of Hepatic Fibrosis.

OBJECTIVE. The purpose of this article is to discuss quantitative methods of CT, MRI, and ultrasound (US) for noninvasive staging of hepatic fibrosis. Hepatic fibrosis is the hallmark of chronic liver disease (CLD), and staging by random liver biopsy is invasive and prone to sampling errors and subjectivity. Several noninvasive quantitative imaging methods are under development or in clinical use. The accuracy, precision, technical aspects, advantages, and disadvantages of each method are discussed. CONCLUSION. The most promising methods are the liver surface nodularity score using CT and measurement of liver stiffness using MR elastography or US elastography.

03:36 PM Abstract No. 77 Liver surface nodularity score on CT for evaluation of portal hypertension in patients with chronic liver disease

03:36 PM Abstract No. 77 Liver surface nodularity score on CT for evaluation of portal hypertension in patients with chronic liver disease

Precision analysis of a quantitative CT liver surface nodularity score.

To evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images. An anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The phantom was scanned multiple times on a single CT scanner with adjustment of image acquisition and reconstruction parameters (N = 34) and on 22 different CT scanners from 4 manufacturers at 12 imaging centers. LSN scores were obtained using a software-based method. Repeatability and reproducibility were evaluated by intraclass correlation (ICC) and coefficient of variation. Using abdominal CT images from 68 patients with various stages of chronic liver disease, inter-observer agreement and test-retest repeatability among 12 readers assessing LSN by software- vs. visual-based scoring methods were evaluated by ICC. There was excellent repeatability of LSN scores (ICC:0.79-0.99) using the CT phantom and routine image acquisition and reconstruction parameters (kVp 100-140, mA 200-400, and auto-mA, section thickness 1.25-5.0mm, field of view 35-50cm, and smooth or standard kernels). There was excellent reproducibility (smooth ICC: 0.97; 95% CI 0.95, 0.99; CV: 7%; nodular ICC: 0.94; 95% CI 0.89, 0.97; CV: 8%) for LSN scores derived from CT images from 22 different scanners. Inter-observer agreement for the software-based LSN scoring method was excellent (ICC: 0.84; 95% CI 0.79, 0.88; CV: 28%) vs. good for the visual-based method (ICC: 0.61; 95% CI 0.51, 0.69; CV: 43%). Test-retest repeatability for the software-based LSN scoring method was excellent (ICC: 0.82; 95% CI 0.79, 0.84; CV: 12%). The software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability.

Accuracy of liver surface nodularity quantification on MDCT for staging hepatic fibrosis in patients with hepatitis C virus.

To evaluate semi-automated measurement of liver surface nodularity (LSN) on MDCT in a cause-specific cohort of patients with chronic hepatitis C virus infection (HCV) for identification of hepatic fibrosis (stages F0-4). MDCT scans in patients with known HCV were evaluated with an independently validated, semi-automated LSN measurement tool. Consecutive LSN measurements along the anterior liver surface were performed to derive mean LSN scores. Scores were compared with METAVIR fibrosis stage (F0-4). Fibrosis stages F0-3 were based on biopsy results within 1year of CT. Most patients with cirrhosis (F4) also had biopsy within 1year; the remaining cases had unequivocal clinical/imaging evidence of cirrhosis and biopsy was not indicated. 288 patients (79F/209M; mean age, 49.7 years) with known HCV were stratified based on METAVIR fibrosis stage: F0 (n = 43), F1 (n = 29), F2 (n = 53), F3 (n = 37), and F4 (n = 126). LSN scores increased with increasing fibrosis (mean: F0 = 2.3 ± 0.2, F1 = 2.4 ± 0.3, F2 = 2.6 ± 0.5, F3 = 2.9 ± 0.6, F4 = 3.8 ± 1.0; p < 0.001). For identification of significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (≥ F4), the ROC AUCs were 0.88, 0.89, and 0.90, respectively. The sensitivity and specificity for significant fibrosis (≥ F2) using LSN threshold of 2.80 were 0.68 and 0.97; for advanced fibrosis (≥ F3; threshold = 2.77) were 0.83 and 0.85; and for cirrhosis (≥ F4, LSN threshold = 2.9) were 0.90 and 0.80. Liver surface nodularity assessment at MDCT allows for accurate discrimination of intermediate stages of hepatic fibrosis in a cause-specific cohort of patients with HCV, particularly at more advanced levels.

Feasibility and reproducibility of liver surface nodularity quantification for the assessment of liver cirrhosis using CT and MRI

PurposeTo assess intra-observer, inter-observer and inter-modality (CT vs. MRI) reproducibility of liver surface nodularity (LSN) scores measured with software used for detection of liver fibrosis. MethodsThis IRB-approved retrospective study included patients with both abdominal CT and MRI within 6 months of histopathologic sampling. Two independent observers used post-processing software to quantify LSN scores on axial non-contrast CT (NCT), axial contrast-enhanced CT (CECT), axial T2-weighted (T2W) HASTE, and axial and coronal post-gadoxetic acid T1-weighted (T1W) images obtained during the hepatobiliary phase (HBP). Ten slices were used to acquire the LSN scores. Intra-observer, inter-observer, and inter-modality (CT vs. MRI) reproducibility were assessed with intraclass correlation coefficient (ICC) and coefficients of variability (CV). Accuracy for detection of cirrhosis was evaluated for each technique. Results26 patients (M/F 19/7, mean age 57 years), including 7 with cirrhosis (26.9%), were assessed. Technical failure occurred with NCT (1/23, 4.3%) and T2 HASTE (8/28, 28.6%). Intra-observer reproducibility was excellent for NCT, CECT, axial and coronal T1W HBP [ICC≥0.92, CV≤8%]. Inter-observer reproducibility was also excellent for NCT and CECT (ICC≥0.95, CV≤7.3%) and for coronal T1W HBP (ICC=0.84, CV=5.6%). There was fair to moderate agreement between CT and MRI (ICC 0.20–0.44). There were significant differences in mean LSN scores between non-cirrhotic and cirrhotic patients with NCT (2.6 vs. 4.2, p=0.04) and T1W HBP (3.7 vs. 4.6; p=0.01) images, with AUCs of 0.81 and 0.82, respectively. ConclusionsLSN measurement is highly reproducible with NCT and post-contrast T1W HBP on MRI, with different results obtained between CT and MRI.

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.

Accuracy of Liver Surface Nodularity Quantification on MDCT as a Noninvasive Biomarker for Staging Hepatic Fibrosis.

The purpose of this study was to investigate objective semiautomated measurement of liver surface nodularity on MDCT for prediction of underlying hepatic fibrosis (stages F0-F4). Contrast-enhanced abdominal MDCT scans were assessed with an independently validated semiautomated surface nodularity tool. A series of 10 or more consecutive ROI measurements along the anterior aspect of the liver totaling a length of 80 cm or more were made with the left lateral segment as the default. All intermediate stages of fibrosis (F1-F3) were based on liver biopsy results within 1 year of MDCT. The study participants were 367 patients (191 men, 176 women; mean age, 51.1 years) divided into a healthy (F0) control group (n = 118) and patients with fibrosis in stages F1 (n = 47), F2 (n = 38), F3 (n = 67), and F4, which constituted cirrhosis (n = 97). MDCT-based liver surface nodularity scores increased with stage of fibrosis: F0, 2.01 ± 0.28; F1, 2.34 ± 0.39; F2, 2.37 ± 0.39; F3, 2.88 ± 0.68; and F4, 4.11 ± 0.95. For discriminating significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (≥ F4), the ROC AUCs were 0.902, 0.932, and 0.959, respectively. The sensitivity and specificity for significant fibrosis (≥ F2; liver surface nodularity threshold, 2.38) were 80.2% and 80.0%, for advanced fibrosis (≥ F3; liver surface nodularity threshold, 2.53) were 89.0% and 84.2%, and for cirrhosis (≥ F4; liver surface nodularity threshold, 2.81) were 97.9% and 84.8%. Objective quantification of liver surface nodularity at MDCT allows accurate discrimination between stages of hepatic fibrosis, especially at more advanced levels. Although the results are comparable to those of elastography, this simple semiautomated biomarker can be measured retrospectively without additional equipment or patient time.

Liver Surface Nodularity Quantification from Routine CT Images as a Biomarker for Detection and Evaluation of Cirrhosis

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.