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ObjectivesRecently, several scoring systems for prognosis prediction based on tumor burden have been promoted for patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). This multicenter study aimed to perform the first head-to-head comparison of three scoring systems.MethodsWe retrospectively enrolled 849 treatment-naïve patients with HCC undergoing TACE at six tertiary care centers between 2010 and 2020. The tumor burden score (TBS), the Six-and-Twelve score (SAT), and the Seven-Eleven criteria (SEC) were calculated based on the maximum lesion size and the number of tumor nodes. All scores were compared in univariate and multivariate regression analyses, adjusted for established risk factors.ResultsThe median overall survival (OS) times were 33.0, 18.3, and 12.8 months for patients with low, medium, and high TBS, respectively (p<0.001). The median OS times were 30.0, 16.9, and 10.2 months for patients with low, medium, and high SAT, respectively (p<0.001). The median OS times were 27.0, 16.7, and 10.5 for patients with low, medium, and high SEC, respectively (p<0.001). In a multivariate analysis, only the SAT remained an independent prognostic factor. The C-Indexes were 0.54 for the TBS, 0.59 for the SAT, and 0.58 for the SEC.ConclusionIn a direct head-to-head comparison, the SAT was superior to the TBS and SEC in survival stratification and predictive ability. Therefore, the SAT can be considered when estimating the tumor burden. However, all three scores showed only moderate predictive power. Therefore, tumor burden should only be one component among many in treatment decision making.

Background and Aims An association between Crohn's disease (CD) and hepatic steatosis has been reported. However, the underlying mechanisms of steatosis progression in CD are not clear. Among the most effective CD treatments are agents that inhibit Tumor‐Necrosis‐Factor (TNF) activity, yet it is unclear why anti‐TNFα agents would affect steatosis in CD. Recent studies suggest that microbiome can affect both, CD and steatosis pathogenesis. Therefore, we here analysed a potential relationship between anti‐TNF treatment and hepatic steatosis in CD, focusing on the gut‐liver axis. Methods This cross‐sectional study evaluated patients with established CD, with and without anti‐TNFα treatment, analysing serum markers of liver injury, measurement of transient elastography, controlled attenuation parameter (CAP) and MRI for fat detection. Changes in lipid and metabolic profiles were assessed by serum and stool lipidomics and metabolimics. Additionally, we analysed gut microbiota composition and mediators of bile acid (BA) signalling via stool and serum analysis. Results Patients on anti‐TNFα treatment had less hepatic steatosis as assessed by CAP and MRI. Serum FGF19 levels were significantly higher in patients on anti‐TNFα therapy and associate with reduced steatosis and increased bowel motility. Neutral lipids including triglycerides were reduced in the serum of patients on anti‐TNF treatment. Bacteria involved in BA metabolism and FGF19 regulation, including Firmicutes, showed group‐specific alterations with low levels in patients without anti‐TNFα treatment. Low abundance of Firmicutes was associated with higher triglyceride levels. Conclusions Anti‐TNFα treatment is associated with reduced steatosis, lower triglyceride levels, alterations in FXR‐signalling (eg FGF19) and microbiota composition in CD.

For CT pulmonary angiograms, a scout view obtained in anterior–posterior projection is usually used for planning. For bolus tracking the radiographer manually locates a position in the CT scout view where the pulmonary trunk will be visible in an axial CT pre-scan. We automate the task of localizing the pulmonary trunk in CT scout views by deep learning methods. In 620 eligible CT scout views of 563 patients between March 2003 and February 2020 the region of the pulmonary trunk as well as an optimal slice (“reference standard”) for bolus tracking, in which the pulmonary trunk was clearly visible, was annotated and used to train a U-Net predicting the region of the pulmonary trunk in the CT scout view. The networks’ performance was subsequently evaluated on 239 CT scout views from 213 patients and was compared with the annotations of three radiographers. The network was able to localize the region of the pulmonary trunk with high accuracy, yielding an accuracy of 97.5% of localizing a slice in the region of the pulmonary trunk on the validation cohort. On average, the selected position had a distance of 5.3 mm from the reference standard. Compared to radiographers, using a non-inferiority test (one-sided, paired Wilcoxon rank-sum test) the network performed as well as each radiographer (P < 0.001 in all cases). Automated localization of the region of the pulmonary trunk in CT scout views is possible with high accuracy and is non-inferior to three radiographers.