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- W2895559480 abstract "Introduction: Radiofrequency ablation (RFA) for colorectal liver metastasis (CRLM) requires a wide margin to prevent local recurrence(LR) , although the minimal required margin is unknown. Moreover, no reliable tool is available for post-ablation margin assessment. In this study, we evaluated feasibility of 3D margin assessment and correlation of minimal margins to LR. Methods: Retrospectively 30 patients were included, all treated with percutaneous RFA for a solitary CRLM. Pre- and post-ablation CT scans were loaded into RTx Mirada software and merged by two independent radiologists based on venous structures in proximity of the tumor. Tumor and ablation volumes were determined on both scans based on automatic contour detection. Subsequently, minimal margins were determined and correlated with occurrence of LR within one year during follow-up. Inter-observer agreement was calculated. Results: In twelve patients merging was too unreliable to assess the ablation margin, the remaining 18 patients, with high-quality merged scans, were included. Technical success was reported in all patients at the time of the procedure based on qualitative assessment. LR was detected in nine patients, of which eight tumors were incompletely ablated, compared with nine patients without LR, in whom eight tumors were completely ablated with a minimal obtained margin of ≥1 mm (p-value = 0.003). There was perfect inter-observer agreement (K=1.000, p< 0.001). Conclusion: Automated 3D margin assessment appears to predict LR. We will determine the potential of real-time margin assessment in improving local control by direct re-ablation if necessary in a prospective, randomized clinical trial." @default.
- W2895559480 created "2018-10-12" @default.
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- W2895559480 date "2018-09-01" @default.
- W2895559480 modified "2023-10-14" @default.
- W2895559480 title "Predicting local regrowth after radiofrequency ablation of colorectal liver metastases by 3D merging of pre- and post-ablation imaging" @default.
- W2895559480 doi "https://doi.org/10.1016/j.hpb.2018.06.2593" @default.
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