MRI-Derived Intra- and Peritumoral Heterogeneity for Predicting Response to Transarterial Chemoembolization in
Fei Wu1, Peng Huang1, Yuyao Xiao1
1Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China (F.W., P.H., Y.X., C.Z., M.Z., Y.Z.); Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai 200032, China (F.W., P.H., Y.X., C.Z., M.Z., Y.Z.).
Rationale And Objectives:
The compromised therapeutic efficacy of transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) is closely associated with tumor heterogeneity. Magnetic resonance imaging (MRI)-derived quantification of intratumoral and peritumoral heterogeneity (ITH and PTH) may provide novel, noninvasive biomarkers. To develop and validate an MRI-based strategy leveraging quantitative ITH and PTH for pretreatment identification of patients with HCC achieving objective response to TACE monotherapy.
Materials And Methods:
This retrospective study included patients with intermediate-stage HCC who underwent TACE. Tumoral and peritumoral regions on pretreatment MRI were partitioned into distinct imaging habitats using unsupervised clustering. High-dimensional radiomic features were extracted from each habitat, and inter-habitat feature dispersion was quantified to yield ITH and PTH metrics. Performance for discriminating responders from non-responders was evaluated using receiver operating characteristic (ROC) analysis, calibration curves, decision curve analysis, and confusion matrices. Shapley additive explanations were applied to interpret model decision-making.
Results:
A total of 156 patients (139 men; age, 60.52 ± 9.90 years; 91 responders) were included and split into a training cohort (n = 124) and a testing cohort (n = 32). Ten ITH/PTH features were selected to construct the ITH/PTH-driven model (TH). Ascites and enhancement pattern were identified as independent predictors of TACE response and were used to build a clinical-radiological model (Cli-Rad). A combined model integrating Cli-Rad and TH features (Cli-Rad-TH) achieved the highest discrimination for predicting TACE response (area under the receiver operating characteristic curve (AUC) = 0.899-0.901), followed by TH (AUC = 0.822 and 0.884) and Cli-Rad (AUC = 0.663-0.704).
Conclusion:
MRI-derived quantification of ITH and PTH enables noninvasive pretreatment prediction of TACE response. This strategy may support individualized treatment stratification and improve clinical decision-making.
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