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Tuning the Pennes Perfusion Rate to Model Large Vessel Cooling Effects in Hepatic Radiofrequency Ablation
Nikhil Vaidya1, Marco Baragona2, Valentina Lavezzo2
1Faculty of Civil Engineering, RWTH Aachen University, Aachen 52062, Germany; High Performance Computation for Engineered Systems, RWTH Aachen University, Schinkelstraße 2, Aachen 52062, Germany.
Journal of Biomechanical Engineering
|February 19, 2022
Summary
Mathematical modeling improves radio frequency ablation (RFA) for liver cancer by optimizing blood vessel models. This study finds optimal perfusion rates to enhance thermal lesion prediction accuracy, aiding treatment outcomes.
Area of Science:
- Biomedical Engineering
- Computational Biology
- Medical Physics
Background:
- Radio frequency ablation (RFA) is a key minimally invasive treatment for liver cancer.
- Treatment success in RFA is highly dependent on clinician experience.
- Mathematical modeling offers a way to predict RFA treatment outcomes.
Purpose of the Study:
- To determine optimal perfusion rates for modeling blood vessel cooling effects in RFA.
- To minimize discrepancies between advection-diffusion and perfusion-based models for thermal lesions.
- To improve the accuracy of RFA outcome predictions.
Main Methods:
- Investigated vessel radii ranging from 0.55 mm to 5 mm.
- Compared advection-diffusion models with Pennes perfusion models for large-scale blood vessels.
- Calculated perfusion rates that minimize thermal lesion volume errors.
Main Results:
- Identified best-estimate perfusion rates for specific vessel radii (0.55-5 mm).
- Demonstrated that previously used perfusion rates may not be optimal.
- Quantified the error reduction achievable with optimized perfusion rates.
Conclusions:
- Optimized perfusion rates enhance the accuracy of simplified RFA models.
- Findings can be integrated into existing methods for rapid RFA outcome estimation.
- Methodology provides a foundation for further refinement of RFA modeling.
