Abstract
Purpose: Thermotherapy is a clinical procedure which delivers thermal energy to a target, and it has been applied for various medical treatments. Temperature monitoring during thermotherapy is important to achieve precise and reproducible results. Medical ultrasound can be used for thermal monitoring and is an attractive medical imaging modality due to its advantages including non-ionizing radiation, cost-effectiveness and portability. We propose an ultrasound thermal monitoring method using a speed-of-sound tomographic approach coupled with a biophysical heat diffusion model. Methods: We implement an ultrasound thermometry approach using an external ultrasound source. We reconstruct the speed-of-sound images using time-of-flight information from the external ultrasound source and convert the speed-of-sound information into temperature by using the a priori knowledge brought by a biophysical heat diffusion model. Results: Customized treatment shapes can be created using switching channels of radio frequency bipolar needle electrodes. Simulations of various ablation lesion shapes in the temperature range of 21–59 ∘C are performed to study the feasibility of the proposed method. We also evaluated our method with ex vivo porcine liver experiments, in which we generated temperature images between 22 and 45 ∘C. Conclusion: In this paper, we present a proof of concept showing the feasibility of our ultrasound thermal monitoring method. The proposed method could be applied to various thermotherapy procedures by only adding an ultrasound source.
Original language | English (US) |
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Pages (from-to) | 815-826 |
Number of pages | 12 |
Journal | International Journal of Computer Assisted Radiology and Surgery |
Volume | 13 |
Issue number | 6 |
DOIs | |
State | Published - Jun 1 2018 |
Keywords
- Ablation therapy
- Bipolar ablation
- Hyperthermia
- RFA modeling
- Speed-of-sound reconstruction
- Thermal monitoring
- Thermotherapy
- Ultrasound
ASJC Scopus subject areas
- Surgery
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Health Informatics
- Computer Science Applications
- Computer Graphics and Computer-Aided Design