Analytical estimation of ultrasound properties, thermal diffusivity, and perfusion using magnetic resonance-guided focused ultrasound temperature data
| Autor: | Christopher Dillon, Allison Payne, Giovanni Borasi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Materials science
Ultrasonic Therapy Quantitative Biology::Tissues and Organs medicine.medical_treatment Physics::Medical Physics Thermal diffusivity Noise (electronics) Article High-Energy Shock Waves 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Nuclear magnetic resonance medicine Animals Radiology Nuclear Medicine and imaging Radiological and Ultrasound Technology medicine.diagnostic_test business.industry Ultrasound Temperature Time constant Magnetic resonance imaging Magnetic Resonance Imaging High-intensity focused ultrasound 030220 oncology & carcinogenesis Rabbits business Perfusion Biomedical engineering Gaussian beam |
| Zdroj: | Physics in Medicine and Biology. 61:923-936 |
| ISSN: | 1361-6560 0031-9155 |
| Popis: | For thermal modeling to play a significant role in treatment planning, monitoring, and control of magnetic resonance-guided focused ultrasound (MRgFUS) thermal therapies, accurate knowledge of ultrasound and thermal properties is essential. This study develops a new analytical solution for the temperature change observed in MRgFUS which can be used with experimental MR temperature data to provide estimates of the ultrasound initial heating rate, Gaussian beam variance, tissue thermal diffusivity, and Pennes perfusion parameter. Simulations demonstrate that this technique provides accurate and robust property estimates that are independent of the beam size, thermal diffusivity, and perfusion levels in the presence of realistic MR noise. The technique is also demonstrated in vivo using MRgFUS heating data in rabbit back muscle. Errors in property estimates are kept less than 5% by applying a third order Taylor series approximation of the perfusion term and ensuring the ratio of the fitting time (the duration of experimental data utilized for optimization) to the perfusion time constant remains less than one. |
| Databáze: | OpenAIRE |
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