Objective To construct a prediction model based on peritumoral radiomics signatures from CT images and investigate its efficiency in predicting early recurrence (ER) of hepatocellular carcinoma (HCC) after curative treatment. Materials and methods In total, 156 patients with primary HCC were randomly divided into the training cohort (109 patients) and the validation cohort (47 patients). From the pretreatment CT images, we extracted 3-phase two-dimensional images from the largest cross-sectional area of the tumor. A region of interest (ROI) was manually delineated around the lesion for tumoral radiomics (T-RO) feature extraction, and another ROI was outlined with an additional 2 cm peritumoral area for peritumoral radiomics (PT-RO) feature extraction. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. The T-RO and PT-RO models were constructed. In the validation cohort, the prediction efficiencies of the two models and peritumoral enhancement (PT-E) were evaluated qualitatively by receiver operating characteristic (ROC) curves, calibration curves and decision curves and quantitatively by area under the curve (AUC), the category-free net reclassification index (cfNRI) and integrated discrimination improvement values (IDI). Results By comparing AUC values, the prediction accuracy in the validation cohort was good for the PT-RO model (0.80 vs. 0.79, P = 0.47) but poor for the T-RO model (0.82 vs. 0.62, P < 0.01), which was significantly overfitted. In the validation cohort, the ROC curves, calibration curves and decision curves indicated that the PT-RO model had better calibration efficiency and provided greater clinical benefits. CfNRI indicated that the PT-RO model correctly reclassified 47% of ER patients and 32% of non-ER patients compared to the T-RO model (P < 0.01); additionally, the PT-RO model correctly reclassified 24% of ER patients and 41% of non-ER patients compared to PT-E ( P = 0.02). IDI indicated that the PT-RO model could improve prediction accuracy by 0.22 (P < 0.01) compared to the T-RO model and by 0.20 ( P = 0.01) compared to PT-E. Conclusion The CT-based PT-RO model can effectively predict the ER of HCC and is more efficient than the T-RO model and the conventional imaging feature PT-E. Electronic supplementary material The online version of this article (10.1186/s40644-019-0197-5) contains supplementary material, which is available to authorized users.

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Objective To investigate the imaging features observed in preoperative Gd-EOB-DTPA-dynamic enhanced MRI and correlated with the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. Methods 66 HCCs in 60 patients with preoperative Gd-EOB-DTPA-dynamic enhanced MRI were retrospectively analyzed. Features including tumor size, signal homogeneity, tumor capsule, tumor margin, peritumor enhancement during mid-arterial phase, peritumor hypointensity during hepatobiliary phase, signal intensity ratio on DWI and apparent diffusion coefficients (ADC), T1 relaxation times, and the reduction rate between pre- and postcontrast enhancement images were assessed. Correlation between these features and histopathological presence of MVI was analyzed to establish a prediction model. Results Histopathology confirmed that MVI were observed in 17 of 66 HCCs. Univariate analysis showed tumor size (p = 0.003), margin (p = 0.013), peritumor enhancement (p = 0.001), and hypointensity during hepatobiliary phase (p = 0.004) were associated with MVI. A multiple logistic regression model was established, which showed tumor size, margin, and peritumor enhancement were combined predictors for the presence of MVI (α = 0.1). R2 of this prediction model was 0.353, and the sensitivity and specificity were 52.9% and 93.0%, respectively. Conclusion Large tumor size, irregular tumor margin, and peritumor enhancement in preoperative Gd-EOB-DTPA-dynamic enhanced MRI can predict the presence of MVI in HCC.

In comparison with the left and right hepatic arteries, there is a relative lack of information on the middle hepatic artery (MHA). In this study, data obtained by multidetector computed tomography from 145 patients were studied to evaluate anatomical variations of the MHA, a hilar artery that primarily supplies hepatic segment 4. An MHA was present in 103 (71%) of the subjects. In livers that had a replaced left hepatic artery, the MHA originated from the right hepatic artery; in livers that had a replaced right hepatic artery, it originated from the left hepatic artery. It always arose directly or indirectly from the common hepatic artery, from which the gastroduodenal artery also arose. We classified MHAs into 5 types according to the anatomical variations of the origin. This classification may have major relevance to modern surgical practice related to living donor liver transplantation (LDLT). The new classification of hepatic arterial anatomy may enhance the acquisition of further knowledge on arterial development, and its application may favorably influence the outcome of LDLT. Liver Transpl 16:736-741,

The aim of the study is to investigate if the fat content of the liver and pancreas may indicate impaired glucose tolerance (IGT) or type 2 diabetes mellitus (T2DM). A total of 83 subjects (34 men; aged 46.5 ± 13.5 years) were characterized as T2DM, IGT, or normal glucose tolerant (NGT). NGT individuals were stratified as <40 or ≥40 years. Standard laboratory tests were conducted for insulin resistance and β-cell dysfunction. The magnetic resonance imaging Dixon technique was used to determine fat distribution in the liver and pancreas. Correlations among liver and pancreatic fat volume fractions (LFVFs and PFVFs, respectively) and laboratory parameters were analyzed. Among the groups, fat distribution was consistent throughout sections of the liver and pancreas, and LFVFs closely correlated with PFVFs. LFVFs correlated more closely than PFVFs with insulin resistance and β-cell function. Both the LFVFs and PFVFs were the highest in the T2DM patients, less in the IGT, and least in the NGT; all differences were significant. The PFVFs of the NGT subjects ≥40 years were significantly higher than that of those <40 years. The fat content of the liver and pancreas, particularly the liver, may be a biomarker for IGT and T2DM.

BackgroundVariable degrees of differentiation in hepatocellular carcinoma(HCC)under Edmondson-Steiner grading system has been proven to be an independent prognostic indicator for HCC. Up till now, there has been no effective radiological method that can reveal the degree of differentiation in HCC before surgery. This paper aims to evaluate the use of Gd-EOB-DTPA-Enhanced Magnetic Resonance Imaging combined with T1 mapping for the diagnosis of HCC and assessing its degree of differentiation.MethodsForty-four patients with 53 pathologically proven HCC had undergone Gd-EOB-DTPA enhanced MRI with T1 mapping before surgery. Out of the 53 lesions,13 were grade I, 27 were gradeII, and 13 were grade III. The T1 values of each lesion were measured before and at 20 min after Gd-EOB-DTPA administration (T1p and T1e). The absolute reduction in T1 value (T1d) and the percentage reduction (T1d %) were calculated. The one-way ANOVA and Pearson correlation were used for comparisons between the T1 mapping values.ResultsThe T1d and T1d % of grade I, II and III of HCC was 660.5 ± 422.8ms、295.0 ± 99.6ms、276.2 ± 95.0ms and 54.0 ± 12.2 %、31.5 ± 6.9 %、27.7 ± 6.7 % respectively. The differences between grade Iand II, grade Iand III were statistically significant (p < 0.05), but there was no statically significant difference between grade II and III. The T1d % was the best marker for grading of HCC, with a Spearman correlation coefficient of −0.676.ConclusionsT1 mapping before and after Gd-EOB-DTPA administration can predict degree of differentiation in HCC.

Background: Hepatocellular carcinoma (HCC) with hilar bile duct tumor thrombus (HBDTT) often mimic hilar cholangiocarcinoma (hilar CC). The purpose of this study is to analyze the Computed Tomography (CT) characteristics of HCC with HBDTT and to identify imaging features to aid its differentiation from hilar CC on enhanced CT. Methods: We retrospectively identified 58 cases with pathologically proved HCC with HBDTT between 2011 and 2018. Seventy-seven cases of pathologically proven hilar CCs were selected during the same period. The clinical features and CT findings of the two groups were reviewed and compared. Results: HCC with HBDTTs are more commonly found in men (87.9% vs 63.6%, p = 0.001) with lower age of onset (49.84 vs 58.61 years; p < 0.001) in comparison to hilar CCs. Positive correlation were identified between HCC with HBDTTs and chronic HBV infection (72.4% vs 11.7%; p < 0.001), increased serum AFP (67.2% vs 1.3%; p < 0.001), CA19-9 level (58.6% vs 85.7%; p < 0.001) and CEA level (3.4% vs 29.9%; p = 0.001), parenchymal lesion with intraductal lesion (100% vs 18.2%; p < 0.001), washout during the portal venous phase (84.5% vs 6.5%; p < 0.001), thickened bile duct wall (8.6% vs 93.5%; p < 0.001), intrahepatic vascular embolus (44.8% vs 7.8%; p < 0.001), splenomegaly (34.5% vs 2.6%, p < 0.001). A scoring system consisting of the five parameters obtained from characteristics mentioned above was trialed. The sensitivity and specificity for diagnosing HCC with HBDTT were 96.39, 100 and 92.5% respectively when the total score was 2 or more. Conclusions: HCC with HBDTTs are often distinguishable from hilar CCs based on washout during portal venous phase without thickened bile duct wall. HBV infection and serum AFP level facilitate the differentiation.

Abstract. The aim of the present study was to identify computed tomography (CT) features to assist in differentiating gastrointestinal schwannomas from gastrointestinal stromal tumors (GISTs). CT images of gastrointestinal schwannomas (n=15) and GISTs (n=50) were analyzed. The absolute CT values of tumor/aorta during plain scan/arterial phase/venous phase were recorded as tumor plain scan (Tp)/aorta plain scan (Ap), tumor arterial phase (Ta)/aorta arterial phase (Aa) and tumor venous phase (Tv)/aorta venous phase (Av), respectively, and normalized CT values of the three phases were calculated as Sp=Tp/Ap, Sa=Ta/Aa and Sv=Tv/Av, respectively. The difference in tumor CT value between arterial and venous phases was calculated and recorded as Tv-a. CT data including tumor size, contour, margin, growth pattern, presence of calcification, cystic change, hemorrhage, ulceration, perilesional lymph nodes (PLNs), local invasion to surrounding structures, metastasis, ascites, vasculatures, enhancement pattern/degree, Tp/Ta/Tv and Sp/Sa/Sv were evaluated for each patient. Receiver operating characteristic (ROC) curve analysis was used to assess the ability of the CT data to differentiate gastrointestinal schwannomas from GISTs. Compared with GISTs, gastrointestinal schwannomas more frequently demonstrated round contouring, relatively smaller tumor size, a homogeneous enhancement pattern, with the presence of PLNs and a higher level of vasculature (P<0.05), whilst the presence of cystic changes were more common in GISTs compared with gastrointestinal schwannomas (P<0.05). The Sa, Ta and Tv-a of gastrointestinal schwannomas were less compared with those of GISTs (P<0.05). The difference in margin, growth pattern, intra-tumoral calcifications and hemorrhage were insignificant (P>0.05). ROC analysis indicated that tumor size, cystic change, the presence of PLNs, tumor enhancement pattern and Sa demonstrated improved diagnostic potential compared with others [area under the curve (AUC) >0.7], amongst which cystic change demonstrated the best diagnostic ability (AUC=0.82). Size exhibited the highest sensitivity, 90%, and cystic change, Sa exhibited the best specificity, 87%. Quantitative analysis indicated that certain features aided the differentiation between gastrointestinal schwannomas and GISTs using CT imaging. IntroductionSchwannoma are benign tumors arising from Schwann cells in the sheaths of peripheral nerves. Schwannoma are homogeneous tumors and may occur in any tissue of the body. The head and neck region is the most prevalent location for schwannoma to occur; they are rarely observed in the gastrointestinal tract (1). Conventional schwannoma usually arise from peripheral skin nerves and connective tissue, whereas gastrointestinal schwannoma tumors are derived from Schwann cells of the Auerbach's plexus within the gastrointestinal tract wall (1-3) and were first reported by Daimaru et al in 1988 (1)