Minimal ablative margin (MAM) assessment with image fusion: an independent predictor for local tumor progression in hepatocellular carcinoma after stereotactic radiofrequency ablation

Abstract

Objectives: To assess the minimal ablative margin (MAM) by image fusion of intraprocedural pre- and post-ablation contrast-enhanced CT images and to evaluate if it can predict local tumor progression (LTP) independently. Furthermore, to determine a MAM with which a stereotactic radiofrequency ablation (SRFA) can be determined successful and therefore used as an intraprocedural tool to evaluate treatment success. Methods: A total of 110 patients (20 women, 90 men; mean age 63.7 ± 10.2) with 176 hepatocellular carcinomas were assessed by retrospective analysis of prospectively collected data. The MAM was determined through image fusion of intraprocedural pre- and post-ablation images using commercially available rigid imaging registration software. LTP was assessed in contrast-enhanced CTs or MR scans at 3–6-month intervals. Results: The MAM was the only significant independent predictor of LTP (p = 0.036). For each millimeter increase of the MAM, a 30% reduction of the relative risk for LTP was found (OR = 0.7, 95% CI 0.5–0.98, p = 0.036). No LTP was detected in lesions with a MAM > 5 mm. The overall LTP rate was 9 of 110 (8.2%) on a patient level and 10 of 173 (5.7%) on a lesion level. The median MAM was 3.4 (1.7–6.9) mm. The mean overall follow-up period was 26.0 ± 10.3 months. Conclusions: An immediate assessment of the minimal ablative margin (MAM) can be used as an intraprocedural tool to evaluate the treatment success in patients treated with stereotactic RFA. A MAM > 5 mm has to be achieved to consider an ablation as successful. Key Points: • An intraoperatively measured minimal ablative margin (MAM) > 5 mm correlates with complete remission. • MAM is the only significant independent predictor of LTP (OR = 0.7, 95% CI 0.5–0.98, p = 0.036) after stereotactic RFA of hepatocellular carcinoma. • Image fusion using commercially available rigid imaging registration software is possible, even though considerably complex. Therefore, improved (semi-)automatic fusion software is highly desirable.