Motivation: Effective management of liver tumors through thermal ablation requires precise monitoring of the ablation zone to ensure successful treatment outcomes. Computed tomography (CT) thermometry offers a promising non-invasive solution to monitor if tumor cells have been heated to the lethal temperature threshold. However, achieving reproducible, precise, and accurate temperature measurements remains a challenge, particularly due to metal artifacts introduced by the ablation equipment.

Purpose: This study investigates the applicability of spectral CT thermometry in monitoring liver microwave ablation. It compares the reproducibility, precision and accuracy of CT thermometry on attenuation value images, with CT thermometry on physical density maps using spectral CT. Furthermore, it identifies the optimal metal artifact reduction (MAR) method — among O-MAR, deep learning-MAR, spectral CT, or a combination — to reduce needle artifacts and improve CT thermometry precision.

Materials and Methods: Four liver-mimicking gel phantoms embedded with temperature sensors underwent a 10-minute, 60W microwave ablation imaged by dual-layer spectral CT using a Philips CT7500 scanner. Each scan was processed to reconstruct standard 120 kVp images alongside physical density maps, which were derived from virtual monochromatic imaging (70 - 150 keV) and effective atomic number maps. During each procedure, 23 CT scans were acquired to monitor attenuation and physical density values in proximity of the ablation antenna over time. Attenuation-based and physical density-based thermometry models were tested for reproducibility (coefficient of variation) over three repetitions; a fourth repetition focused on accuracy (Bland-Altman analysis). MAR techniques were applied to a single repetition to evaluate temperature precision in artifact-corrupted slices.

Results: The correlation between CT value and temperature was highly linear with an R-squared value exceeding 96% for both attenuation and physical density-based thermometry. Model parameters for attenuation-based and physical density-based thermometry were -0.38 HU/ºC and 0.00039 ºC-1, with coefficients of variation of 0.023 and 0.067, respectively, indicating a high reproducibility. CT thermometry precision increased with distance from the ablation antenna, the use of attenuation maps and deep learning-MAR. Physical density maps generated at 150 keV alone and in combination with O-MAR and deep learning-MAR reduced needle artifacts by 73% on average (p=0.003) compared to attenuation images. Bland-Altman analysis reveals limits-of-agreement of -7.7°C to 5.3°C and -9.5°C to 8.1°C for attenuation and physical density-based thermometry, respectively.

Conclusion: Spectral CT has the potential to make CT thermometry more universally applicable. This study demonstrates the effectiveness of spectral CT thermometry for non-invasive temperature monitoring during liver microwave ablation. It shows that using spectral physical density maps at 150 keV, alongside deep learning-MAR and O-MAR, enhances temperature accuracy and minimizes metal artifacts. However, standardizing thermometry parameters across different patient conditions remains a challenge. Future enhancements in photon counting CT and deep learning technologies could further refine this method, ultimately reducing the risk of local tumor recurrence.

Purpose Manufacturer’s predictions of ablation zone dimensions are the current directives for treatment planning in thermal ablation, while they are mostly based on ex vivo experiments making its reliability questionable. The aim of this study is to determine the correspondence in dimensions, volume, shape and overlap of the manufactures’ predicted with the clinically realized ablation zones following thermal ablation of hepatocellular carcinoma (HCC). The secondary objective is to determine the effect of tumor- and liver characteristics on this correspondence.
Methods Data was retrospectively collected from two prospective studies. A registered pre-ablation and post-ablation computed tomography scan with liver, tumor and ablation zone segmentations were available for analysis. Needle position reconstruction was performed based on image visual assessment (e.g., gas formation, tumor location and subcapsular hemorrhage) using in-house developed software. The dimensions of the predicted ablation zone were derived from the manufacturer’s chart corresponding to treatment settings used during ablation. The long axis diameter (LAD), short axis diameter (SAD) and volume of the realized and predicted ablation zone were compared. The overlap was determined using the Dice similarity coefficient (DSC) and the average surface deviation between the realized and predicted ablation zone. The effect of tumor location, vascular proximity and liver cirrhosis on the overlap was quantified using the DSC and average surface deviation.
Results Nineteen patients and 21 ablations were included for analysis. The median realized volume did not significantly differ from the predicted volume, 25.7 cm3 and 22.6 cm3 respectively (p = 0.526). The median LAD and SAD of the realized ablation zone differed significantly from the manufacturer’s prediction (51.9 mm vs 40.0 mm, p<0.001 and 36.9 mm vs 35.0 mm, p<0.001 respectively). The predicted ablation zone corresponds to the realized ablation zone with a mean DSC of 0.73 and mean average surface deviation of 3.04 mm. Tumor location and vascular proximity did not affect the overlap between the realized and predicted ablation zone. The effect of liver cirrhosis was not assessed due to a low sample size of HCC in a non-cirrhotic liver (n=2).
Conclusion The manufacturer’s predicted volume of liver ablation zones corresponds well to the clinically realized ablation volume. However, the LAD and SAD are underestimated by the manufacturers. The shape and overlap of the predicted and realized ablation zone were sufficient. Further studies evaluating the effect of tumor- and liver characteristics on the correspondence of the predicted with the realized ablation zone with a larger patient cohort is needed.

Introduction The objective of this research is to assess whether there is a correlation between quantitatively assessed ablation margins and the occurrence of local tumor progression (LTP) using dedicated image processing software.
Methods 28 patients with 45 de novo HCCs treated with percutaneous thermal ablation, e.g. radiofrequency ablation (RFA) and microwave ablation (MWA) between January 2014 and March 2019 were retrospectively included. Semi-automated segmentation of the liver and the ablation zone, manual segmentation of the tumor, and semi-automated registration of pre- and postprocedural contrast enhanced computed tomography (CECT) and magnetic resonance imaging (MRI) images was performed using in-house developed software deLIVERed. The image processing results were used for quantitative analysis of the minimal ablation margin (MAM) and the ablation margin surface area. The outcome of the quantitative analysis was compared to LTP occurence.
Results Image processing of the scans of 39 of the 45 tumors was feasible. 5/39 tumors developed LTP. Based on quantitative analysis, thermal ablation was insufficient in 29/39 tumors. Of these 29 tumors, 4 developed LTP. The median MAM for the LTP group and no LTP group was -4.6 and -1.7 mm, respectively. There was no clear correlation between the MAM and LTP occurrence.
The median tumor surface area exposed to insufficient margins was 28.9% and 7.7.% with and without development of LTP, respectively.
Conclusion Quantitative analysis of postablation images can provide insight in ablation margins and the development of LTP. The ablation margin surface area provides additional information to the MAM. However, additional research is needed in order to further investigate the implications of ablation margin surface area.