Prediction Model for Intermediate-Stage Hepatocellular Carcinoma Response to Transarterial Chemoembolization
Fei Jia1, Baolin Wu2, Ruifang Yan1
1Department of MR, First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Background:
The outcome of intermediate-stage hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) is greatly heterogeneous. Current means for predicting HCC response to TACE are lacking.
Purpose:
To investigate whether the combination of parameters derived from amide proton transfer (APT) and intravoxel incoherent motion (IVIM) imaging, and morphological characteristics of tumor can establish a better prediction model than the univariant model for HCC response to TACE.
Study Type:
Prospective.
Subjects:
56 patients with intermediate-stage HCC (50 males and six females).
Field Strength/Sequences:
3.0T; T2 -weighted-fast spin echo, 3D liver acquisition with volume flex, single-shot fast spin echo-planar imaging (EPI), spin echo-EPI.
Assessment:
Pretreatment APT signal intensities (SIs), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) for tumor, peritumoral, and normal tissues were measured. Follow-up MRI scanning was performed, and the patients were classified as responders or nonresponders based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria.
Statistical Tests:
The imaging parameters were compared among the three tissues and between the two groups using analysis of variance (ANOVA) or two-sample t-test. The prediction model's variables were derived from univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance.
Results:
Based on the logistic regression analysis results, we established a prediction model that integrated the APT SI and D values in the tumor tissue and the tumor size. ROC analyses revealed that the model was better able to predict tumor response to TACE (area under the ROC curve = 0.851) than the individual parameters on their own.
Data Conclusion:
A prediction model incorporating pretreatment APT SI, D in the tumor tissue and tumor size may be useful for predicting the response of intermediate-stage HCC to TACE.
Level Of Evidence:
1 TECHNICAL EFFICACY: Stage 1 J. MAGN. RESON. IMAGING 2020;52:1657-1667.
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