Predictive Value of Pattern Classification 24 Hours after Radiofrequency Ablation of Liver Metastases on CT and Positron Emission Tomography/CT

Abstract

PurposeTo assess a classification scheme for predicting local tumor progression (LTP) after radiofrequency (RF) ablation of liver metastases, using predefined patterns on contrast-enhanced computed tomography (CT) and positron emission tomography (PET) combined with CT (PET/CT) acquired 24 hours after RF ablation. Materials and MethodsThere were 45 metastases in 20 patients treated. After 24 hours, imaging of the ablation zones was performed with contrast-enhanced PET/CT. Three independent radiologists prospectively assessed contrast-enhanced CT and combined PET/CT images to identify three patterns: pattern I, no tissue enhancement or fluorodeoxyglucose uptake between the ablation zone and the liver parenchyma; pattern II, a rimlike pattern; and pattern III, a peripheral nodule. PET/CT images obtained after 8–10 weeks were evaluated for LTP. The patterns were analyzed for their sensitivity, specificity, positive predictive value, and negative predictive value for predicting LTP. ResultsPattern I was most frequently observed (81% for contrast-enhanced CT and 61% for PET/CT) as well as for ablation zones that showed LTP (52% and 37%, respectively). Conversely, pattern II was observed for tumors that were completely ablated (6% and 29%, respectively). Patterns II and III together had the highest sensitivity for predicting LTP (48% and 63%, respectively); pattern III had the highest specificity (94% and 95%, respectively). For nodular patterns, test characteristics were better for PET/CT compared with contrast-enhanced CT, but the difference was not significant. Nodular patterns > 1 cm achieved high positive predictive value (both 100%). ConclusionsInflammation and hyperemia can hinder interpretation on imaging 24 hours after RF ablation, especially on PET/CT. Nodular patterns around the ablation zone on early contrast-enhanced CT and PET/CT have a high predictive value for LTP and should be taken into account for disease management.