Prediction of microvascular invasion in solitary hepatocellular carcinoma ≤ 5 cm based on computed tomography radiomics

Figure 1 Screening process for patients with liver cancer. HCC: Hepatocellular carcinoma; CT: Computed tomography; MVI: Microvascular invasion.

Figure 2 Specific performance of two-trait predictor of venous invasion and radiogenomic invasion. A and B: The discriminant process of two-trait predictor of venous invasion (TTPVI) (A) and radiogenomic invasion (RVI) (B); C: Negative intratumoral arteries: Negative TTPVI and RVI; D: Positive intratumoral arteries and peritumoral low density: Negative TTPVI and PVI; E: Positive intratumoral arteries, negative peritumoral low-density shadow, and positive tumor-liver differences: Positive TTPVI and negative RVI; F: Positive intratumoral arteries, negative peritumoral low density, and negative tumor-liver differences: Positive TTPVI and RVI. TTPVI: Two-trait predictor of venous invasion; RVI: Radiogenomic invasion.

Figure 3 Selection of radiomic features using the least absolute shrinkage and selection operator-logistic regression model. A: Coefficient profile of 158 radiomics features against the area under the curve; B: Cross-validation curve. Red dotted vertical lines are drawn at the optimal log (Lambda) by using 10-fold cross-validation and the 1-SE criteria. Ten nonzero coefficients are chosen. AUC: Area under the curve.

Figure 4 The two-trait predictor of venous invasion (green curve), radiogenomic invasion (red curve), and receiver operator characteristic of radiomics tag (blue curve) from the two groups. A: Training group; B: Verification group. TTPVI: Two-trait predictor of venous invasion; RVI: Radiogenomic invasion.