Computed tomography-based thermography (CTT) in microwave ablation: prediction of the heat ablation zone in the porcine liver

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Abstract

Objectives: The aim of the study was to investigate computed tomography-based thermography (CTT) for ablation zone prediction in microwave ablation (MWA). Methods: CTT was investigated during MWA in an in vivo porcine liver. For CTT, serial volume scans were acquired every 30 s during ablations and every 60 s immediately after MWA. After the procedure, contrast-enhanced computed tomography (CECT) was performed. After euthanasia, the liver was removed for sampling and further examination. Color-coded CTT maps were created for visualization of ablation zones, which were compared with both CECT and macroscopy. Average CT attenuation values in Hounsfield units (HU) were statistically correlated with temperatures using Spearman’s correlation coefficient. CTT was retrospectively evaluated in one patient who underwent radiofrequency ablation (RFA) treatment of renal cell carcinoma. Results: A significant correlation between HU and temperature was found with r = − 0.77 (95% confidence interval (CI), − 0.89 to − 0.57) and p < 0.001. Linear regression yielded a slope of − 1.96 HU/°C (95% CI, − 2.66 to − 1.26). Color-coded CTT maps provided superior visualization of ablation zones. Conclusion: Our results show that CTT allows visualization of the ablation area and measurement of its size and is feasible in patients, encouraging further exploration in a clinical setting. Critical relevance statement: CT-based thermography research software allows visualization of the ablation zone and is feasible in patients, encouraging further exploration in a clinical setting to assess risk reduction of local recurrence. Graphical Abstract: [Figure not available: see fulltext.]

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Kostyrko, B., Rubarth, K., Althoff, C., Poch, F. G. M., Neizert, C. A., Zibell, M., … Pohlan, J. (2023). Computed tomography-based thermography (CTT) in microwave ablation: prediction of the heat ablation zone in the porcine liver. Insights into Imaging, 14(1). https://doi.org/10.1186/s13244-023-01537-z

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