Objective:

To develop and externally validate a preoperative nomogram based on tumor margin irregularity and alpha-fetoprotein (AFP) positivity for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Approach:

• Study Design: Retrospective multicenter study with a training cohort of 487 patients and an external validation cohort of 256 patients.
• Data Collection: Demographic, clinical, tumor-related, serological, and preoperative CT variables were compared by MVI status.
• Analysis Method: LASSO regression for predictor selection followed by multivariable logistic regression; model performance assessed using ROC curves, AUC, calibration, and DCA.

Key Findings:

• MVI was present in 187 of 487 patients in the training cohort and 95 of 256 patients in the validation cohort.
• LASSO selected AFP positivity, irregular tumor margins, capsular interruption, and intratumoral hyperplastic vessels as predictors.
• Irregular tumor margins (adjusted OR = 5.275, 95% CI: 3.165–8.791, p < 0.001) and AFP positivity (adjusted OR = 3.297, 95% CI: 1.983–5.481, p < 0.001) were identified as independent predictors.
• The final model achieved AUCs of 0.740 and 0.781 in the training and validation cohorts, respectively.

Interpretation:

The nomogram based on tumor margin irregularity and AFP positivity showed fair-to-acceptable discrimination for preoperative MVI risk stratification in HCC patients.

Limitations:

• The study is retrospective and may have selection bias.
• External validation was limited to a single cohort.
• The model requires further prospective multicenter validation.

Conclusion:

The nomogram may support exploratory preoperative MVI risk stratification in surgically treated or resectable HCC patients.