Effective models of microwave antennae for ablation treatment planning

Tokoutsi, Zoi; Baragona, Marco; Frackowiak, Bruno

doi:10.1109/embc46164.2021.9630943

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…The heat source term Q appl that is generated by the ablation applicator is modeled with a simplified formulation. It considers the type of the MW applicator, and it is fitted to accurately reproduce manufacturer´s specifications 28 , as verified in the subsequent section. The heat source is prescribed on the applicator active zone and relates to the ablation power and treatment duration through a temperature dependent absorption rate 23 .…”

Section: Biophysical Model Descriptionmentioning

confidence: 99%

“…Overall, the biophysical model performs within less than a minute throughput time, thus making the planning tool compatible for a real time usage during the clinical procedure. More details on the MW model can be found in a separate contribution 28 . Reproducibility of the simulations can be upheld from the detailed description of the model combined with the clinical data.…”

Section: Biophysical Model Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

Model-based hepatic percutaneous microwaveablation planning. First validation on a clinical dataset

Frackowiak

Bosch

Tokoutsi

et al. 2023

Preprint

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A model-based planning tool, integrated in an imaging system, is envisioned for CT-guided percutaneous microwave ablation. This study aims to evaluate the biophysical model performance, by comparing its prediction retrospectively with the actualablation ground truth from a clinical data set in liver. The biophysical model uses a simplified formulation of heat depositionon the applicator and a heat sink related to vasculature to solve the bioheat equation. A performance metric is defined toassess how the planned ablation overlaps the actual ground truth. Results demonstrate superiority of this model predictioncompared to manufacturer tabulated data and a significant influence of the vasculature cooling effect. Nevertheless, vasculatureshortage due to branches occlusion and applicator misalignment due to registration error between scans affects the thermalprediction. With a more accurate vasculature segmentation, occlusion risk can be estimated, whereas branches can be usedas liver landmarks to improve the registration accuracy. Overall, this study emphasizes the benefit of a model-based thermalablation solution in better planning the ablation procedures. Contrast and registration protocols must be adapted to facilitate itsintegration into the clinical workflow.

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Section: Biophysical Model Descriptionmentioning

confidence: 99%

Section: Biophysical Model Descriptionmentioning

confidence: 99%