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Updated: Jan 16, 2026
Thermal Ablation for the Treatment of Abdominal Tumors
Published on: March 7, 2011
A predictive model for optimal CT-guided thermal ablation margins in liver malignancies ≤3 cm: a retrospective cohort
Zhenkang Qiu1, Guobao Wang2, Zixiong Chen1
1Department of Minimally Invasive and Interventional Radiology, Sun Yat-sen University Cancer Center and Sun Yat-sen University State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Background And Aims:
Standardized quantitative criteria are lacking for the recommended circumferential thermal ablative margin in liver malignancies ≤3 cm. This study aimed to identify predictors of technical success in thermal ablation and develop a predictive model defining optimal ablation margins.
Methods:
This retrospective study analyzed 979 patients undergoing computed tomography-guided radiofrequency or microwave ablation for liver malignancies ≤3 cm. Using a radiotherapy treatment planning system, preoperative tumor dimensions [maximum tumor area, preoperative maximum tumor area (PreMTA); tumor volume, preoperative tumor volume (PreTV)] and postoperative ablation characteristics [maximum ablation area, postoperative maximum ablation area (Post-MAA); ablation volume, postoperative ablation volume (PostAV)] were volumetrically quantified. Volume ratio (PostAV/PreTV) and area ratio (PostMAA/PreMTA) were calculated. Univariate and multivariate logistic regression identified predictors of residual tumor. A nomogram was developed and validated using Harrell's C-index, calibration curves, and receiver operating characteristic analysis. Size- and location-specific margin recommendations were derived mathematically.
Results:
Residual tumor occurred in 91 patients (9.3%). Multivariate analysis identified adjacent large vessel [odd ratio (OR) = 1.97; P = 0.015], larger PreMTA (OR = 1.44; P = 0.014), and lower volume ratio (OR = 0.77; P = 0.009) as independent predictors. For non-perivascular tumors, optimal volume ratios were 4.3, 6.0, and 8.8 (corresponding ΔR = 0.3 cm, 0.8 cm, 1.6 cm) for diameters 1.0 cm, 2.0 cm, and 3.0 cm, respectively. A web-based calculator was implemented (https://fbzl.org/monitor/ablation_model.html).
Conclusions:
This study establishes and validates a computational model defining tumor size- and vessel proximity-specific optimal ablation margins for liver malignancies ≤3 cm. The web-accessible model provides evidence-based individualized ablation targets that optimize oncological efficacy while preserving parenchyma, replacing conventional fixed margins.
