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Hindawi, Journal of Oncology, (2019), p. 1-8, 2019

DOI: 10.1155/2019/4049287

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Quantitative Volumetric Assessment of Ablative Margins in Hepatocellular Carcinoma: Predicting Local Tumor Progression Using Nonrigid Registration Software

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Purpose. After radiofrequency ablation (RFA) of hepatocellular carcinoma (HCC), pre- and postinterventional contrast-enhanced CT (CECT) images are usually qualitatively interpreted to determine technical success, by eyeballing. The objective of this study was to evaluate the feasibility of quantitative assessment, using a nonrigid CT-CT coregistration algorithm. Materials and Methods. 25 patients treated with RFA for HCC between 2009 and 2014 were retrospectively included. Semiautomated coregistration of pre- and posttreatment CECT was performed independently by two radiologists. In scans with a reliable registration, the tumor and ablation area were delineated to identify the side and size of narrowest RFA margin. In addition, qualitative assessment was performed independently by two other radiologists to determine technical success and the anatomical side and size of narrowest margin. Interobserver agreement rates were determined for both methods, and the outcomes were compared with occurrence of local tumor progression (LTP). Results. CT-CT coregistration was technically feasible in 18/25 patients with almost perfect interobserver agreement for quantitative analysis (κ = 0.88). The interobserver agreement for qualitative RFA margin analysis was κ = 0.64. Using quantitative assessment, negative ablative margins were found in 12/18 patients, with LTP occurring in 8 of these patients. In the remaining 6 patients, quantitative analysis demonstrated complete tumor ablation and no LTP occurred. Conclusion. Feasibility of quantitative RFA margin assessment using nonrigid coregistration of pre- and postablation CT is limited, but appears to be a valuable tool in predicting LTP in HCC patients (p=0.013).