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  4. Optimizing microwave ablation planning with the ablation success ratio
 
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2025
Journal Article
Title

Optimizing microwave ablation planning with the ablation success ratio

Abstract
The size of hepatic microwave ablations (MWA) is often difficult to predict due to cooling effects from liver vessels. This study introduces a simplified predictive model, the Ablation Success Ratio (ASR), which estimates the likelihood of a successful ablation based on tumor size and specific ablation parameters. The ASR model is based on the three-dimensional minimum ablation radius (r3Dmin), defining the spherical region within which complete ablation is achieved. To validate the ASR, standardized MWAs were performed in an ex vivo porcine liver model using a glass tube to simulate the vascular cooling effect. Ablations (n = 148) were conducted at 100 W for 5 min, with antenna-to-vessel (A-V) distances set at 2.5, 5.0, and 10.0 mm. Subsequently, the r3Dmin was calculated. Without vascular cooling (0 ml/min, corresponding to an intraoperative Pringle maneuver), an ASR of 100% was achieved for ablation diameters up to 20 mm. However, in the presence of vascular cooling (1–500 ml/min), the ASR reached 100% only for ablation diameters up to 12 mm, demonstrating that the ASR effectively includes the impact of vascular cooling effects. The ASR is a promising and simple approach for predicting ablation success while also accounting for vascular cooling effects in hepatic MWA.
Author(s)
Neizert, Christina Ann
Charité – Universitätsmedizin Berlin
Do, H. N.C.
Charité – Universitätsmedizin Berlin
Zibell, Miriam
Landesamt für Gesundheit und Soziales
Sinden, David  orcid-logo
Fraunhofer-Institut für Digitale Medizin MEVIS  
Rieder, Christian  
Fraunhofer-Institut für Digitale Medizin MEVIS  
Albrecht, Jakob
Charité – Universitätsmedizin Berlin
Niehues, Stefan Markus
Caritas-Klinik Dominikus
Lehmann, Kai Siegfried
Charité – Universitätsmedizin Berlin
Poch, Franz Gerd Martin
Charité – Universitätsmedizin Berlin
Journal
Scientific Reports  
Open Access
DOI
10.1038/s41598-025-94957-4
Language
English
Fraunhofer-Institut für Digitale Medizin MEVIS  
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