Hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC) are the major adult liver cancers. The existence of combined hepatocellular-cholangiocarcinoma (CHC), a histopathological intermediate form between HCC and CC, suggests phenotypic overlap between these tumors. Here, we applied an integrative oncogenomic approach to address the clinical and functional implications of the overlapped phenotype between these tumors. By performing gene expression profiling of human HCC, CHC, and CC, we identified a novel HCC subtype, namely, CC-like HCC (CLHCC), which expressed CC-like traits (CC signature). As like CC and CHC, CLHCC showed aggressive phenotype with shorter recurrence-free and overall survival. In addition, we found that CLHCC coexpressed embryonic stem cell-like expression traits (ES signature) suggesting its derivation from bipotent hepatic progenitor cells. By comparing the expression of CC signature with previous ES-like, hepatoblast-like, or proliferation-related traits, we observed that that the prognostic value of the CC signatures is independent of the expression of those signatures. In conclusion, we suggest that the acquisition of CC like-expression traits play a critical role in the heterogeneous progression of HCC.

Acute kidney injury (AKI) after liver transplantation has been reported to be associated with increased mortality. Recently, machine learning approaches were reported to have better predictive ability than the classic statistical analysis. We compared the performance of machine learning approaches with that of logistic regression analysis to predict AKI after liver transplantation. We reviewed 1211 patients and preoperative and intraoperative anesthesia and surgery-related variables were obtained. The primary outcome was postoperative AKI defined by acute kidney injury network criteria. The following machine learning techniques were used: decision tree, random forest, gradient boosting machine, support vector machine, naïve Bayes, multilayer perceptron, and deep belief networks. These techniques were compared with logistic regression analysis regarding the area under the receiver-operating characteristic curve (AUROC). AKI developed in 365 patients (30.1%). The performance in terms of AUROC was best in gradient boosting machine among all analyses to predict AKI of all stages (0.90, 95% confidence interval [CI] 0.86–0.93) or stage 2 or 3 AKI. The AUROC of logistic regression analysis was 0.61 (95% CI 0.56–0.66). Decision tree and random forest techniques showed moderate performance (AUROC 0.86 and 0.85, respectively). The AUROC of support the vector machine, naïve Bayes, neural network, and deep belief network was smaller than that of the other models. In our comparison of seven machine learning approaches with logistic regression analysis, the gradient boosting machine showed the best performance with the highest AUROC. An internet-based risk estimator was developed based on our model of gradient boosting. However, prospective studies are required to validate our results.

Purpose: To determine the sensitivity and specificity of MR elastography (MRE) in the staging of hepatic fibrosis (HF) using histopathology as the reference standard in an Asian population.Materials and Methods: MRE was performed on 55 patients with chronic liver diseases or biliary diseases and on 5 living related liver donors (48 men and 12 women; mean age, 55.7 years). MRE was performed with modified, phase-contrast, gradient-echo sequences, and the mean stiffness values were measured on the elastograms in kilopascals(kPa). Receiver operating characteristic curve analysis was performed to determine the cutoff value and accuracy of MRE for staging HF. Histopathologic staging of HF according to the METAVIR scoring system served as the reference.Results: Liver stiffness increased systematically along with the fibrosis stage. With a shear stiffness cutoff value of 3.05 kPa, the predicted sensitivity and specificity for differentiating significant liver fibrosis (! F2) from mild fibrosis (F1) were 89.7% and 87.1%, respectively. In addition, MRE was able to discriminate between patients with severe fibrosis (F3) and those with liver cirrhosis (sensitivity, 100%; specificity, 92.2%), with a shear stiffness cutoff value of 5.32 kPa.Conclusion: MRE could be a promising, noninvasive technique with excellent diagnostic accuracy for detecting significant HF and liver cirrhosis.

The guideline for the management of hepatocellular carcinoma (HCC) was first developed in 2003 and revised in 2009 by the Korean Liver Cancer Study Group and the National Cancer Center, Korea. Since then, many studies on HCC have been carried out in Korea and other countries. In particular, a substantial body of knowledge has been accumulated on diagnosis, staging, and treatment specific to Asian characteristics, especially Koreans, prompting the proposal of new strategies. Accordingly, the new guideline presented herein was developed on the basis of recent evidence and expert opinions. The primary targets of this guideline are patients with suspicious or newly diagnosed HCC. This guideline provides recommendations for the initial treatment of patients with newly diagnosed HCC.

529sis determines patient eligibility for and the potential success of curative treatments. Therefore, CT and MRI aided by technologic advances that afford improved spatial, temporal, and contrast resolution are regarded as promising alternative surveillance tools for detecting HCC [4,5]. Contrast-enhanced dynamic multiphasic imaging has substantial performance benefits because most HCCs are hypervascular lesions that typically become enhanced during the hepatic arterydominant phase of imaging [6]. OBJECTIVE. The purpose of this study was to retrospectively evaluate the diagnostic performance of dynamic gadobenate dimeglumine-enhanced MRI with explant pathologic correlation in the detection of hepatocellular carcinoma (HCC) in patients undergoing liver transplantation. Hepatocellular Carcinoma in H e p a t o b i l i a r y I m ag i ng • O r ig i n a l R e s e a rc hMATERIALS AND METHODS. Forty-seven patients (28 men, 19 women; mean age, 49 years) underwent dynamic gadobenate dimeglumine-enhanced MRI within 3 months before primary liver transplantation. Dynamic imaging was performed before (unenhanced) and after (hepatic arterial, portal venous, equilibrium, and 1-hour delayed phases) IV bolus administration of gadobenate dimeglumine at 0.1 mmol/kg body weight. Retrospective image analysis to detect HCC nodules was performed independently by two abdominal radiologists who had no pathologic information. On a per-nodule basis, the sensitivity and positive predictive value were calculated for the two observers. Sensitivity and specificity in the diagnosis of HCC also were evaluated. Fisher's exact test was performed to determine whether there was a detection difference between HCC nodules 1 cm in diameter or larger and nodules smaller than 1 cm and to evaluate the differences in causes of false-positive MRI findings based on lesion size (≥ 1 cm vs < 1 cm).RESULTS. Twenty-seven patients had 41 HCCs. In HCC detection, gadobenate dimeglumine-enhanced MRI had a sensitivity of 85% (35 of 41 HCCs) and a positive predictive value of 66% (35 of 53 readings) for observer 1 and a sensitivity of 80% (33 of 41 HCCs) and a positive predictive value of 65% (34 of 52 readings) for observer 2. For both observers, sensitivity in the detection of HCCs 1 cm in diameter and larger (91-94%) was significantly different (p < 0.05) from that in detection of HCCs smaller than 1 cm (29-43%). Nonneoplastic arterial hypervascular lesions more often caused false-positive diagnoses of lesions smaller than 1 cm in diameter (80-86%) on MR images than of those 1 cm in diameter and larger (0-25%). The difference was statistically significant (p < 0.05) for both observers. In diagnosis, gadobenate dimeglumine-enhanced MRI had a sensitivity of 87% (20 of 23 patients) and a specificity of 79% (19 of 24 patients) for both observers.CONCLUSION. Dynamic gadobenate dimeglumine-enhanced MRI has a sensitivity of 80-85% and a positive predictive value of 65-66% in the detection of HCC. The technique, however, is of limited value for detecting and characterizi...

No abstract

Purpose:To evaluate the diagnostic performance of magnetic resonance (MR) fat quantification and MR elastography for the assessment of hepatic steatosis and fibrosis in living liver donor candidates. Materials and Methods:This retrospective study was approved by the institutional review board, and the requirement of informed consent was waived. Donors who underwent MR fat quantification and MR elastography at 1.5 T, followed by liver biopsy, were chronologically grouped into test and validation groups. In the test group (n = 362), MR fat fraction and liver stiffness were compared among donors with normal parenchyma (n = 244), simple steatosis (n = 71), steatosis with inflammatory activity (n = 21), nonalcoholic steatohepatitis (n = 17), and fibrosis (n = 9). Diagnostic performance of the two techniques was assessed by using receiver operating characteristic curve analysis for the detection of substantial steatosis (macrovesicular fat  10%) or fibrosis (F1) and was tested in a validation group (n = 34). Results:In the test group, donors with steatosis showed significantly higher fat fraction than donors without steatosis (P , .0001), and donors with fibrosis and nonalcoholic steatohepatitis showed significantly higher liver stiffness values than donors without fibrosis (P , .0001). Areas under the curve were 0.93 (cutoff value . 5.8%) for MR fat quantification and 0.85 (cutoff value . 1.94 kPa) for MR elastography. By using those values, the combination of the two techniques could be used to detect substantial steatosis or fibrosis with 100% sensitivity (12 of 12 patients, 95% confidence interval: 73.4%, 100%) and 100% negative predictive value (15 of 15 patients, 95% confidence interval: 78.0%, 100%) in the validation group. Conclusion:A combination of MR fat quantification and MR elastography can provide sufficient sensitivity to detect substantial steatosis or fibrosis (F1) in liver donor candidates.q RSNA, 2015

).q RSNA, 2015 Purpose:To investigate the diagnostic performance of acoustic structure quantification (ASQ) for the assessment of hepatic steatosis by using hydrogen 1 ( 1 H) magnetic resonance (MR) spectroscopy as the reference standard and to compare ASQ with hepatorenal ratio. Materials andMethods:This prospective study was approved by an institutional review board, and informed written consent was obtained from all participants. ASQ and MR spectroscopy were performed in 89 participants (mean age, 41.48 years 6 14.16; 35 men, 54 women) without history of chronic liver disease. Obtained were focal disturbance (FD) ratio by using ASQ, hepatic fat fraction (HFF) by using MR spectroscopy, and hepatorenal ratio by using a histogram. Correlation coefficient, intraclass correlation coefficient, and receiver operating curve analyses were performed. Results:FD ratio measured with ASQ had a strong linear correlation with HFF measured with MR spectroscopy after logarithmic transformation of both variables (r = 20.87; P , .001). By using HFF of 5.79% as a cutoff value of 10% hepatic steatosis, 29 of 89 participants (32.6%) were categorized into the group with hepatic steatosis of 10% or greater (mean HFF, 13.18% 6 4.89). The area under curve of the FD ratio for diagnosing hepatic steatosis 10% or greater was 0.959 (95% confidence interval: 0.895, 0.990) with sensitivity of 86.2% (95% confidence interval: 68.3%, 96.0%) and specificity of 100% (95% confidence interval: 94.0%, 100.0%) by using a cutoff value of 0.1; the area under curve and specificity of the FD ratio were significantly higher than those of the hepatorenal ratio (respectively, 0.772 and 73.3%; respective P values, .001 and ,.001). Conclusion:This pilot study in a cohort of patients with hepatic steatosis without other parenchymal disease suggested ASQ may be valuable for the quantification of hepatic steatosis and detection of hepatic steatosis 10% or greater in living liver donors.q RSNA, 2015