Diagnostic model using LI-RADS v2018 for predicting early recurrence of microvascular invasion-negative solitary hepatocellular carcinoma

TL;DR

This study developed a model using MRI features to predict early recurrence in a specific type of liver cancer after surgery.

Contribution

The study introduces a diagnostic model using LI-RADS v2018 MRI features to predict early recurrence in MVI-negative HCC.

Findings

Infiltrative appearance and targetoid hepatobiliary phase appearance were independent predictors of early recurrence.

The model combining these features had an AUC of 0.76 for predicting early recurrence.

Patients with these features had significantly lower recurrence-free survival rates.

Abstract

To develop a diagnostic model for predicting the early recurrence of microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) after surgical resection, using the Liver Imaging Reporting and Data System (LI-RADS) version 2018.

This retrospective study included 73 patients with MVI-negative HCC who underwent Gadoxetic acid-enhanced MRI (EOB-MRI) scanning before surgical resection. The clinical factors and LI-RADS v2018 MRI features associated with early recurrence were determined using univariable and multivariable analyses. A diagnostic model predicting early recurrence after surgical resection was developed, and its predictive ability was evaluated via a receiver operating characteristic curve. Then, the recurrence-free survival (RFS) rates were analyzed by Kaplan–Meier method.

In total, 26 (35.6%) patients were diagnosed with early recurrence according to the follow-up results. Infiltrative appearance and targetoid hepatobiliary phase (HBP) appearance were independent predictors associated with early recurrence (p < 0.05). For the established diagnostic model that incorporated these two significant predictors, the AUC value was 0.76 (95% CI: 0.64–0.85) for predicting early recurrence after resection, which was higher than the infiltrative appearance (AUC: 0.67, 95% CI: 0.55–0.78, p = 0.019) and targetoid HBP appearance (AUC: 0.68, 95% CI:0.57–0.79, p = 0.028). In the RFS analysis, patients with infiltrative appearance and targetoid HBP appearance showed significantly lower RFS rates than those without infiltrative appearance (2-year RFS rate, 48.0% vs. 72.0%; p = 0.009) and targetoid HBP appearance (2-year RFS rate, 60.0% vs. 35.0%; p = 0.003).

An EOB-MRI model based on infiltrative appearance and targetoid HBP appearance showed good performance in predicting early recurrence of HCC after surgery, which may provide personalized guidance for clinical treatment decisions in patients with MVI-negative HCC.

Infiltrative appearance and targetoid HBP appearance were associated with early recurrence in patients with MVI-negative HCC.Based on the nomogram incorporating these risk factors, the MVI-negative HCC patients could be stratified into two subgroups with significantly different prognoses.The diagnostic model could identify a high risk of early recurrence in MVI-negative HCC and assist in prognosis evaluation.

Infiltrative appearance and targetoid HBP appearance were associated with early recurrence in patients with MVI-negative HCC.

Based on the nomogram incorporating these risk factors, the MVI-negative HCC patients could be stratified into two subgroups with significantly different prognoses.

The diagnostic model could identify a high risk of early recurrence in MVI-negative HCC and assist in prognosis evaluation.

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