Abstract

PurposeTo test the hypothesis that volume changes of ablation zones (AZs) on successive computed tomography (CT) scans could predict ablation site recurrences (ASRs) in patients with colorectal liver metastases treated by radiofrequency (RF) ablation. Materials and MethodsRF ablation was performed in 58 patients with 117 metastases. Metastasis volumes and AZ volumes were measured before RF ablation, 1 week after RF ablation (t1), and every 3 months in the first year after RF ablation (t2–t5). Volumetry was performed semiautomatically on CT scans by drawing freehand regions of interest in the portal venous phase on 2-mm-thickness slices. ASR was defined as contrast enhancement on follow-up imaging or by a hot spot on fludeoxyglucose F 18 positron emission tomography combined with computed tomography (FDG-PET/CT) scanning. Proportional volume change of an AZ was defined as the difference in volume percentages between two successive time points of measurement. Negative values represented a volume decrease, and positive values represented a volume increase. Intraobserver variability and interobserver variability were evaluated by using intraclass correlation coefficients (ICCs). ResultsASRs occurred in 15 patients with 27 AZs. An increase in volume occurred in 26 AZs (96%) with ASRs. AZs without ASR showed no volume increase. Although proportional volume changes at t1–t2 were not predictive for ASR, subsequent volume changes were predictive for ASR. Contrast-enhanced CT–based evaluation detected ASRs in 17 (63%) of 27 AZs, 7 (26%) of 27 AZs were negative, and there was doubt in 3 (11%) of 27 AZs. Intraobserver variability and interobserver variability were good (0.998 [95% confidence interval [CI] 0.996–0.999; P < .001] and 0.993 [95% CI 0.987–0.996; P < .001]). ConclusionsVolumetry of AZs is useful because a volume increase of an AZ during follow-up is highly suggestive of ASR. Negative volume changes of the AZ from t1–t2 were not correlated with the development of ASRs, but subsequent volume changes were predictive for ASRs.

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