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An excellent nomogram predicts microvascular invasion that cannot independently stratify outcomes of small
Huanhuan Chong1,2, Peiyun Zhou3,4, Chun Yang2
1Shanghai Institute of Medical Imaging, Shanghai, China.
Background:
Whether microvascular invasion is a prognosis factor for small hepatocellular carcinoma (sHCC) is controversial, and a preoperatively predictive model based on gadoxetate disodium (Gd-EOB-DTPA) MRI is clinically needed for MVI in sHCC.
Methods:
Between March 2012 and September 2020, 455 consecutive patients with pathologically confirmed HCC ≤3 cm who underwent hepatectomy and preoperative Gd-EOB-DTPA MRI were retrospectively enrolled. Univariate and multivariate logistic regression combined with cox regression were conducted to find the confounding factors in the cohorts. Propensity score matching (PSM) was employed to balance the biases between MVI and non-MVI groups. Nomogram with C-index visualized the predictive model of MVI.
Results:
Multivariate logistic regression identified that 5 characteristics (AFP, tumor size, tumor margin, peritumoral enhancement, radiologic capsule) were markedly associated with MVI of sHCC and incorporated into the nomogram with excellent predictive performance in the training (AUC/C-index: 0.884/0.874, n=288), validation (AUC/C-index: 0.845/0.828, n=123) and test cohorts (AUC/C-index: 0.903/0.954, n=44). Before PSM, histologic MVI independently affected tumor recurrence (hazard ratio: 1.555, 95% CI: 1.055-2.293, P=0.026). However, due to the confounder of tumor size, there was a significant bias between MVI-positive and MVI-negative groups (propensity score: 0.249±0.105 vs. 0.179±0.106, P<0.001). Meanwhile, the frequency of MVI significantly increased as tumor size growing (P<0.001). After PSM, 70 of 79 MVI cases matched with 171 non-MVI (total 332), and no biases were observed between the two groups (propensity score: 0.238±0.104 vs. 0.217±0.109, P=0.186). Although the median recurrence time in non-MVI sHCC was still longer than that in MVI group (74.3 vs. 43.0 months, P=0.063), MVI was not an independent risk factor for RFS in sHCC. Additionally, MVI was not independently vulnerable to mortality in our population.
Conclusions:
A preoperative model, mainly based on the peritumoral hallmarks of Gd-EOB-DTPA MRI, showed an excellent performance to predict the occurrence of MVI. Nevertheless, MVI was a potential but not an independent risk factor for recurrence and mortality in sHCC ≤3 cm.
