Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach for predicting MVI status based on preoperative multiphase CT images and to identify MVI-associated differentially expressed genes. Materials and Methods Patients with pathologically proven HCC from May 2012 to September 2020 were retrospectively included from four medical centers. Radiomics features were extracted from tumors and peritumor regions on preoperative registration or subtraction CT images. In the training set, these features were used to build five radiomics models via logistic regression after feature reduction. The models were tested using internal and external test sets against a pathologic reference standard to calculate area under the receiver operating characteristic curve (AUC). The optimal AUC radiomics model and clinical-radiologic characteristics were combined to build the hybrid model. The log-rank test was used in the outcome cohort (Kunming center) to analyze early recurrence-free survival and overall survival based on high versus low model-derived score. RNA sequencing data from The Cancer Image Archive were used for gene expression analysis. Results A total of 773 patients (median age, 59 years; IQR, 49-64 years; 633 men) were divided into the training set (n = 334), internal test set (n = 142), external test set (n = 141), outcome cohort (n = 121), and RNA sequencing analysis set (n = 35). The AUCs from the radiomics and hybrid models, respectively, were 0.76 and 0.86 for the internal test set and 0.72 and 0.84 for the external test set. Early recurrence-free survival (P < .01) and overall survival (P < .007) can be categorized using the hybrid model. Differentially expressed genes in patients with findings positive for MVI were involved in glucose metabolism. Conclusion The hybrid model showed the best performance in prediction of MVI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Summers in this issue.

Background A better understanding of the association between liver MRI proton density fat fraction (PDFF) and liver diseases might support the clinical implementation of MRI PDFF. Purpose To quantify the genetically predicted causal effect of liver MRI PDFF on liver disease risk. Materials and Methods This population-based prospective observational study used summary-level data mainly from the UK Biobank and FinnGen. Mendelian randomization analysis was conducted using the inverse variance-weighted method to explore the causal association between genetically predicted liver MRI PDFF and liver disease risk with Bonferroni correction. The individual-level data were downloaded between August and December 2020 from the UK Biobank. Logistic regression analysis was performed to validate the association between liver MRI PDFF polygenic risk score and liver disease risk. Mediation analyses were performed using multivariable mendelian randomization. Results Summary-level and individual-level data were obtained from 32 858 participants and 378 436 participants (mean age, 57 years ± 8 [SD]; 203 108 female participants), respectively. Genetically predicted high liver MRI PDFF was associated with increased risks of malignant liver neoplasm (odds ratio [OR], 4.5; P < .001), alcoholic liver disease (OR, 1.9; P < .001), fibrosis and cirrhosis of the liver (OR, 3.0; P < .004), fibrosis of the liver (OR, 3.6; P = .002), cirrhosis of the liver (OR, 3.8; P < .001), nonalcoholic steatohepatitis (OR, 7.7; P < .001), and nonalcoholic fatty liver disease (NAFLD) (OR, 4.4; P < .001). Individual-level evidence supported these associations after grouping participants based on liver MRI PDFF polygenic risk score (all P < .004). The mediation analysis indicated that genetically predicted high-density lipoprotein cholesterol, type 2 diabetes mellitus, and waist-to-hip ratio (mediation effects, 25.1%-46.3%) were related to the occurrence of fibrosis and cirrhosis of the liver, cirrhosis of the liver, and NAFLD at liver MRI PDFF (all P < .05). Conclusion This study provided evidence of the association between genetically predicted liver MRI PDFF and liver health. © RSNA, 2023 Supplemental material is available for this article. See also the editorials by Reeder and Starekova and Monsell in this issue.

PURPOSE: Transarterial chemoembolization (TACE) alone has shown limited efficacy in improving survival among patients with unresectable hepatocellular carcinoma (HCC). This phase II trial compared TACE combined with camrelizumab (anti–PD-1 antibody) and rivoceranib (vascular endothelial growth factor receptor 2 inhibitor) versus TACE in unresectable HCC. METHODS: Patients with unresectable HCC (Barcelona Clinic Liver Cancer stage A to C without extrahepatic metastases) and Child-Pugh class A liver function were randomly assigned (1:1), stratified by macrovascular invasion, previous tyrosine kinase inhibitor treatment, and number of previous TACE procedures, to receive TACE combined with camrelizumab (200 mg once every 3 weeks) and rivoceranib (250 mg once daily; TACE-C-R) or TACE alone. The primary end point was progression-free survival (PFS) per composite criteria (progression per Response Evaluation Criteria in Cancer of the Liver version 5, transient deterioration to Child-Pugh class C, or TACE failure or refractoriness) in the intention-to-treat population. RESULTS: Between December 28, 2020, and October 29, 2023, 200 patients were randomly assigned (100 in each group). Median PFS per composite criteria was significantly longer with TACE-C-R than with TACE (10.8 months [95% CI, 8.8 to 13.7] v 3.2 months [95% CI, 2.4 to 4.2]; hazard ratio, 0.34 [95% CI, 0.24 to 0.50], P < .001). Grade ≥3 treatment-related adverse events occurred in 74.5% (70 of 94) of patients with TACE-C-R and 22.3% (23 of 103) of patients with TACE, with the most common being increased AST (29 [30.9%] and 13 [12.6%]) and increased ALT (23 [24.5%] and 14 [13.6%]). CONCLUSION: The addition of camrelizumab and rivoceranib to TACE showed statistically significant improvement in PFS for patients with unresectable HCC, with a manageable safety profile. Follow-up for further overall survival analysis is ongoing.

Distinct vascular patterns, including microvascular invasion (MVI) and vessels encapsulating tumour clusters (VETC), are associated with poor outcomes of hepatocellular carcinoma (HCC). Imaging surrogates of these vascular patterns potentially help to predict post-resection recurrence. Herein, a prognostic model integrating imaging-based surrogates of these distinct vascular patterns was developed to predict postoperative recurrence-free survival (RFS) in patients with HCC. Clinico-radiological data of 1,285 patients with HCC from China undergoing surgical resection were retrospectively enrolled from seven medical centres between 2014 and 2020. A prognostic model using clinical data and imaging-based surrogates of MVI and VETC patterns was developed (n = 297) and externally validated (n = 373) to predict RFS. The surrogates (i.e. MVI and VETC scores) were individually built from preoperative computed tomography using two independent cohorts (n = 360 and 255). Whether the model's stratification was associated with postoperative recurrence following anatomic resection was also evaluated. The MVI and VETC scores demonstrated effective performance in their respective training and validation cohorts (AUC: 0.851–0.883 for MVI and 0.834–0.844 for VETC). The prognostic model incorporating serum alpha-foetoprotein, tumour multiplicity, MVI score, and VETC score achieved a C-index of 0.748–0.764 for the developing and external validation cohorts and generated three prognostically distinct strata. For patients at model-predicted medium risk, anatomic resection was associated with improved RFS (p <0.05). By contrast, anatomic resection had no impact on RFS in patients at model-predicted low or high risk (both p >0.05). The proposed model integrating imaging-based surrogates of distinct vascular patterns enabled accurate prediction for RFS. It can potentially be used to identify HCC surgical candidates who may benefit from anatomic resection. MVI and VETC are distinct vascular patterns of HCC associated with aggressive biological behaviour and poor outcomes. Our multicentre study provided a model incorporating imaging-based surrogates of these patterns for preoperatively predicting RFS. The proposed model, which uses imaging detection to estimate the risk of MVI and VETC, offers an opportunity to help shed light on the association between tumour aggressiveness and prognosis and to support the selection of the appropriate type of surgical resection.

CT imaging of coronavirus disease 2019 (COVID-19): from the qualitative to quantitative

With the proposal of the “biological-psychological-social” model, clinical decision-makers and researchers have paid more attention to the bidirectional interactive effects between psychological factors and diseases. The brain-gut-microbiota axis, as an important pathway for communication between the brain and the gut, plays an important role in the occurrence and development of inflammatory bowel disease. This article reviews the mechanism by which psychological disorders mediate inflammatory bowel disease by affecting the brain-gut-microbiota axis. Research progress on inflammatory bowel disease causing “comorbidities of mind and body” through the microbiota-gut-brain axis is also described. In addition, to meet the needs of individualized treatment, this article describes some nontraditional and easily overlooked treatment strategies that have led to new ideas for “psychosomatic treatment”.