ABSTRACT
Abstract The power of computed tomography (CT) radiomics for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) demonstrated in current research is variable. This systematic review and meta-analysis aim to evaluate the value of CT radiomics for MVI prediction in HCC, and to investigate the methodologic quality in the workflow of radiomics research. Databases of PubMed, Embase, Web of Science, and Cochrane Library were systematically searched. The methodologic quality of included studies was assessed. Validation data from studies with Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement type 2a or above were extracted for meta-analysis. Eleven studies were included, among which nine were eligible for meta-analysis. Radiomics quality scores of the enrolled eleven studies varied from 6 to 17, accounting for 16.7%-47.2% of the total points, with an average score of 14. Pooled sensitivity, specificity, and Area Under the summary receiver operator Characteristic Curve (AUC) were 0.82 (95% CI 0.77-0.86), 0.79 (95% CI 0.75-0.83), and 0.87 (95% CI 0.84-0.91) for the predictive performance of CT radiomics, respectively. Meta-regression and subgroup analyses showed radiomics model based on 3D tumor segmentation, and deep learning model achieved superior performances compared to 2D segmentation and non-deep learning model, respectively (AUC: 0.93 vs. 0.83, and 0.97 vs. 0.83, respectively). This study proves that CT radiomics could predict MVI in HCC. The heterogeneity of the included studies precludes a definition of the role of CT radiomics in predicting MVI, but methodology warrants uniformization in the radiology community regarding radiomics in HCC.
ABSTRACT
OBJECTIVE: The aim of this study was to determine whether and how the diameter of the vein that gives rise to the inflowing vein of the esophageal and gastric fundic varices secondary to posthepatitic cirrhosis, as measured with multidetector-row computed tomography, could predict the varices and their patterns. METHODS: A total of 106 patients with posthepatitic cirrhosis underwent multidetector-row computed tomography. Patients with and without esophageal and gastric fundic varices were enrolled in Group 1 and Group 2, respectively. Group 1 was composed of Subgroup A, consisting of patients with varices, and Subgroup B consisted of patients with varices in combination with portal vein-inferior vena cava shunts. The diameters of the originating veins of veins entering the varices were reviewed and statistically analyzed. RESULTS: The originating veins were the portal vein in 8% (6/75) of patients, the splenic vein in 65.3% (49/75) of patients, and both the portal and splenic veins in 26.7% (20/75) of patients. The splenic vein diameter in Group 1 was larger than that in Group 2, whereas no differences in portal vein diameters were found between groups. In Group 1, the splenic vein diameter in Subgroup A was larger than that in Subgroup B. A cut-off splenic vein diameter of 8.5 mm achieved a sensitivity of 83.3% and specificity of 58.1% for predicting the varices. For discrimination of the varices in combination with and without portal vein-inferior vena cava shunts, a cut-off diameter of 9.5 mm achieved a sensitivity of 66.7% and specificity of 60.0%. CONCLUSION: The diameter of the splenic vein can be used to predict esophageal and gastric fundic varices and their patterns.