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. 2021 May 21:11:649682.
doi: 10.3389/fonc.2021.649682. eCollection 2021.

Preoperative Gadoxetic Acid-Enhanced MRI Based Nomogram Improves Prediction of Early HCC Recurrence After Ablation Therapy

Chengguang Hu  1   2 , Yangda Song  1   2 , Jing Zhang  3 , Lin Dai  2 , Cuirong Tang  1   2 , Meng Li  1   2 , Weijia Liao  4 , Yuchen Zhou  5 , Yikai Xu  3 , Yong-Yuan Zhang  6 , Yuanping Zhou  1
Affiliations

Preoperative Gadoxetic Acid-Enhanced MRI Based Nomogram Improves Prediction of Early HCC Recurrence After Ablation Therapy

Chengguang Hu et al. Front Oncol. .

Abstract

Purpose: This study aimed to identify preoperative gadoxetic acid-enhanced MRI features and establish a nomogram for predicting early recurrence (≤ 2 years) of hepatocellular carcinoma (HCC) after ablation therapy.

Methods: A total of 160 patients who underwent gadoxetic acid-enhanced MRI and ablation HCC therapy from January 2015 to June 2018, were included retrospectively and divided into a training cohort (n = 112) and a validation cohort (n = 48). Independent clinical risk factors and gadoxetic acid-enhanced MRI features associated with early recurrence were identified by univariate and multivariate logistic regression analysis and used for construction of a nomogram. The performance of the nomogram was evaluated by discrimination, calibration, and clinical utility.

Results: Alpha-fetoprotein (AFP) level, tumor number, arterial peritumoral enhancement, satellite nodule and peritumoral hypointensity at hepatobiliary phases in the training cohort were identified as independent risk factors for early recurrence after ablation. A new nomogram that was constructed with these five features showed an area under the curve (AUC) of 0.843 (95%CI 0.771-0.916) and 0.835 (95%CI 0.713-0.956) in the training and validation cohort, respectively. The calibration curve and decision curve analysis (DCA) suggested that the nomogram had good consistency and clinical utility.

Conclusions: A new nomogram that was constructed using four preoperative gadoxetic acid-enhanced MRI features and serum AFP level can predict the risk of early HCC recurrence after ablation therapy with AUC up to 0.843. The strong performance of this nomogram may help hepatologists to categorize patients' recurrent risk to guide selecting treatment options and improve postoperative management.

Keywords: ablation technique; early recurrence; hepatocellular carcinoma; magnetic resonance imaging; nomogram; prediction.

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Conflict of interest statement

Y-YZ is the founder and CSO of HBVtech. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of patient inclusion.
Figure 2
Figure 2
Univariate (A) and multivariate (B) analyses of independent risk factors associated with early HCC recurrence in the training cohort. (*Statistically significant results from logistic regression analysis; †Used as the reference category).
Figure 3
Figure 3
Gadoxetic acid-enhanced MR image (A) in arterial phase shows a 2.0 cm × 1.6 cm nodular lesion with arterial enhancement in hepatic segment V (arrow) and this nodule shows washout (arrow) in the portal venous phase (B). In hepatobiliary phase (C) the lesion shows wedge-shaped peritumoral hypointensity area (arrow).
Figure 4
Figure 4
Nomogram predicting probability of early recurrence within 2 years after ablation therapy of HCC.
Figure 5
Figure 5
(A, B) Comparison of receiver operating characteristics (ROC) curves for predicting early recurrence between nomogram and clinical model in the training and validation cohort. The clinical model included AFP level and tumor number. (C, D) Calibration curve for the nomogram in the training and validation cohort. Calibration curves depict the agreement of the model between the predicted risks of early recurrence and the actual observed recurrence. X-axis represents the predicted probability of early recurrence. Y-axis represents the actual early recurrence, and the diagonal dashed line indicates the optimal prediction by a perfect model. The red solid line represents the performance of the nomogram, and the closer the red line is to the diagonal dashed line, the higher the prediction accuracy of the model.
Figure 6
Figure 6
Patients were stratified by the scores calculated with the nomogram. The recurrence-free survival rate (RFS) of each group in the training cohort (A) and the validation cohort (B) were calculated, and significant differences in each risk group were observed by the Log-rank test (P < 0.001).
Figure 7
Figure 7
Decision curve analysis for two models. The use of the nomogram for early recurrence prediction provides more benefit than two extreme conditions [the treat-all-patients scheme (gray line) and the treat-none scheme (horizontal black line)]. Nomogram (red line) receives a higher net benefit than the model based on clinical factors (blue line) across a full range of reasonable threshold probabilities.
See this image and copyright information in PMC

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