Spectral CT quantitative parameters for predicting complete ablation after radiofrequency ablation in liver tumors: a...

Radiofrequency ablation (RFA) is a key minimally invasive treatment for liver tumors, but predicting complete ablation remains challenging.

This study aimed to evaluate the correlation between spectral CT quantitative parameters and complete ablation after RFA for liver tumors.

This retrospective study enrolled 109 patients who underwent RFA for liver tumors and completed preoperative spectral CT scans (January 2022-October 2025). Patients were divided into complete ablation (n=81) and incomplete ablation (n=28) groups based on postoperative MRI. Preoperative spectral CT parameters [normalized iodine concentration (NIC), spectral curve slope (λ-HU), effective atomic number (Z-eff)] in arterial and portal venous phases were measured. Clinical factors including tumor size, AFP, and vessel adjacency were collected. Logistic regression and ROC analysis were used to build a predictive model.

The arterial phase NIC, λ-HU, and Z-eff in the lesion parenchymal area of the complete ablation group were significantly lower than those in the incomplete ablation group (P<0.05). Additionally, the proportions of patients with preoperative serum alpha-fetoprotein (AFP) >100 ng/mL, tumors adjacent to major intrahepatic vessels, and a maximum tumor diameter >3 cm were significantly lower in the complete ablation group compared to the incomplete ablation group (P<0.05). Logistic regression analysis identified maximum tumor diameter >3 cm (OR = 8.50, 95% CI: 1.38-52.50), preoperative AFP >100 ng/mL (OR = 9.69, 95% CI: 1.34-70.15), tumor adjacency to major intrahepatic vessels (OR = 12.90, 95% CI: 1.34-124.21), arterial phase NIC (OR = 5.66, 95% CI: 1.49-21.57), λ-HU (OR = 4.32, 95% CI: 1.50-12.47), and Z-eff (OR = 5.12, 95% CI: 1.18-22.22) as independent predictive factors. The combined predictive model constructed from these factors achieved an AUC of 0.933 (95% CI: 0.869-0.972) for predicting complete ablation, with a predictive performance superior to that of any single parameter (P<0.001).

Spectral CT quantitative parameters, along with tumor size, vessel adjacency, and AFP level, are significantly associated with complete ablation after RFA for liver tumors and can serve as predictive biomarkers for optimizing individualized treatment.