Computational modeling of radiofrequency ablation: Evaluation on ex vivo data using ultrasound monitoring

Chloé Audigier, Younsu Kim, Austin Dillow, Emad Boctor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Radiofrequency ablation (RFA) is the most widely used minimally invasive ablative therapy for liver cancer, but it is challenged by a lack of patient-specific monitoring. Inter-patient tissue variability and the presence of blood vessels make the prediction of the RFA dificult. A monitoring tool which can be personalized for a given patient during the intervention would be helpful to achieve a complete tumor ablation. However, the clinicians do not have access to such a tool, which results in incomplete treatment and a large number of recurrences. Computational models can simulate the phenomena and mechanisms governing this therapy. The temperature evolution as well as the resulted ablation can be modeled. When combined together with intra-operative measurements, computational modeling becomes an accurate and powerful tool to gain quantitative understanding and to enable improvements in the ongoing clinical settings. This paper shows how computational models of RFA can be evaluated using intra-operative measurements. First, simulations are used to demonstrate the feasibility of the method, which is then evaluated on two ex vivo datasets. RFA is simulated on a simplified geometry to generate realistic longitudinal temperature maps and the resulted necrosis. Computed temperatures are compared with the temperature evolution recorded using thermometers, and with temperatures monitored by ultrasound (US) in a 2D plane containing the ablation tip. Two ablations are performed on two cadaveric bovine livers, and we achieve error of 2.2 °C on average between the computed and the thermistors temperature and 1.4 °C and 2.7 °C on average between the temperature computed and monitored by US during the ablation at two different time points (t = 240 s and t = 900 s).

Original languageEnglish (US)
Title of host publicationMedical Imaging 2017
Subtitle of host publicationImage-Guided Procedures, Robotic Interventions, and Modeling
PublisherSPIE
Volume10135
ISBN (Electronic)9781510607156
DOIs
StatePublished - 2017
EventMedical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling - Orlando, United States
Duration: Feb 14 2017Feb 16 2017

Other

OtherMedical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling
CountryUnited States
CityOrlando
Period2/14/172/16/17

Fingerprint

Ablation
ablation
Ultrasonics
Temperature
Monitoring
evaluation
temperature
liver
Liver
therapy
Thermometers
Physiologic Monitoring
Liver Neoplasms
Thermistors
thermistors
necrosis
Blood Vessels
blood vessels
Blood vessels
thermometers

Keywords

  • Computational modeling
  • Ex vivo Vali-dation
  • Radiofrequency ablation
  • Ultrasound thermal monitoring

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Audigier, C., Kim, Y., Dillow, A., & Boctor, E. (2017). Computational modeling of radiofrequency ablation: Evaluation on ex vivo data using ultrasound monitoring. In Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling (Vol. 10135). [1013525] SPIE. https://doi.org/10.1117/12.2254986

Computational modeling of radiofrequency ablation : Evaluation on ex vivo data using ultrasound monitoring. / Audigier, Chloé; Kim, Younsu; Dillow, Austin; Boctor, Emad.

Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling. Vol. 10135 SPIE, 2017. 1013525.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Audigier, C, Kim, Y, Dillow, A & Boctor, E 2017, Computational modeling of radiofrequency ablation: Evaluation on ex vivo data using ultrasound monitoring. in Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling. vol. 10135, 1013525, SPIE, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, Orlando, United States, 2/14/17. https://doi.org/10.1117/12.2254986
Audigier C, Kim Y, Dillow A, Boctor E. Computational modeling of radiofrequency ablation: Evaluation on ex vivo data using ultrasound monitoring. In Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling. Vol. 10135. SPIE. 2017. 1013525 https://doi.org/10.1117/12.2254986
Audigier, Chloé ; Kim, Younsu ; Dillow, Austin ; Boctor, Emad. / Computational modeling of radiofrequency ablation : Evaluation on ex vivo data using ultrasound monitoring. Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling. Vol. 10135 SPIE, 2017.
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