Impact of multi-parameter images obtained from dual-energy CT on radiomics to predict pathological grading of bladder urothelial carcinoma.

OBJECTIVE: To investigate the effect of radiomics models obtained from dual-energy CT (DECT) material decomposition images and virtual monoenergetic images (VMIs) in predicting the pathological grading of bladder urothelial carcinoma (BUC). MATERIALS AND METHODS: A retrospective analysis of preoperative DECT examination was conducted on 112 patients diagnosed with BUC. This cohort included 76 cases of high-grade urothelial carcinoma and 36 cases of low-grade urothelial carcinoma. DECT can provide material decomposition images of venous phase Iodine maps and Water maps based on the differences in attenuation of substances, as well as VMIs at 40 to 140 keV (interval 10 keV). A total of 13 image sets were obtained, and radiomics features were extracted and analyzed from each set to achieve preoperative prediction of BUC. The best features related to BUC were identified by recursive feature elimination (RFE), the Minimum Redundancy Maximum Relevance (mRMR), and the Least Absolute Shrinkage and Selection Operator (LASSO) in order. A five-fold cross-validation method was used to divide the samples into training and testing sets, and models for pathological prediction of BUC grading were constructed by a random forest (RF) classifier. Receiver operating curves (ROC) were plotted to evaluate the performance of 13 models obtained from each image set. RESULTS: Despite the notable differences in the best radiomics features chosen from each image set, all the features selected from 40 to 100 keV VMIs included the Dependence Variance of the GLDM feature set. There were no statistically significant differences in the area under the curve (AUC) between the training set and the testing set for all 13 models. In the testing set, the AUCs of the models established through 40 keV to 140 keV (interval of 10 keV) image sets were 0.895, 0.874, 0.855, 0.889, 0.841, 0.868, 0.852, 0.847, 0.889, 0.887 and 0.863 respectively. The AUCs for the models established using the Iodine maps and Water maps image sets were 0.873 and 0.852, respectively. CONCLUSION: Despite the differences in the selected radiomic features from DECT multi-parameter images, the performance of radiomics models in predicting the pathological grading of BUC was not affected by the variations in the types of images used for model training.

Novel imaging-based approaches for predicting the hepatic venous pressure gradient in a porcine model of liver cirrhosis and portal hypertension.

AIMS: Hepatic venous pressure gradient (HVPG) is critical for staging and prognosis prediction of portal hypertension (PH). However, HVPG measurement has limitations (e.g., invasiveness). This study examined the value of non-invasive, imaging-based approaches including magnetic resonance elastography (MRE) and intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for the prediction of HVPG in a porcine model of liver cirrhosis and PH. MAIN METHODS: Male Bama miniature pigs were used to establish a porcine model of liver cirrhosis and PH induced by embolization. They were randomly assigned to an experimental group (n = 12) and control group (n = 3). HVPG was examined before and after transjugular intrahepatic portosystemic shunt (TIPS). MRE and IVIM-DWI were performed to obtain quantitative parameters including liver stiffness (LS) in MRE, tissue diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) in IVIM-DWI. The correlation between HVPG and the parameters was assessed. KEY FINDINGS: LS values were significantly greater in the experimental group, while f values were significantly decreased at 4, 8, and 12 weeks after embolization compared to the control group. Furthermore, HVPG was significantly lower immediately after versus before TIPS. In parallel, LS and f values showed significant alterations after TIPS, and these changes were consistent with a reduction in HVPG. Spearman analysis revealed a significant correlation between the parameters (LS and f) and HVPG. The equation was eventually generated for prediction of HVPG. SIGNIFICANCE: The findings show a good correlation between HVPG and the quantitative parameters; thus, imaging-based techniques have potential as non-invasive methods for predicting HVPG.

LncRNA-ATB promotes autophagy by activating Yes-associated protein and inducing autophagy-related protein 5 expression in hepatocellular carcinoma.

BACKGROUND: Long non-coding RNAs (lncRNAs) play important roles in many diseases, including hepatocellular carcinoma (HCC). Autophagy is a metabolic pathway that facilitates cancer cell survival in response to stress. The relationship between autophagy and the lncRNA-activated by transforming growth factor beta (lncRNA-ATB) in HCC remains unknown. AIM: To explore the influence of lncRNA-ATB in regulating autophagy in HCC cells and the underlying mechanism. METHODS: In the present study, we evaluated lncRNA-ATB expression in tumor and adjacent non-tumor tissues from 72 HCC cases by real-time PCR. We evaluated the role of lncRNA-ATB in the proliferation and clonogenicity of HCC cells in vitro. The effect of lncRNA-ATB on autophagy was determined using a LC3-GFP reporter and transmission electron microscopy. Furthermore, the mechanism by which lncRNA-ATB regulates autophagy was explored by immunofluorescence staining, RNA immunoprecipitation (RIP), and Western blot. RESULTS: The expression of lncRNA-ATB was higher in HCC tissues than in normal liver tissues, and lncRNA-ATB expression was positively correlated with tumor size, TNM stage, and poorer survival of patients with HCC. Moreover, ectopic overexpression of lncRNA-ATB promoted cell proliferation and clonogenicnity of HCC cells in vitro. LncRNA-ATB promoted autophagy by activating Yes-associated protein (YAP). Moreover, lncRNA-ATB interacted with autophagy-related protein 5 (ATG5) mRNA and increased ATG5 expression. CONCLUSION: LncRNA-ATB regulates autophagy by activating YAP and increasing ATG5 expression. Our data demonstrate a novel function for lncRNA-ATB in autophagy and suggest that lncRNA-ATB plays an important role in HCC.