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  4. Fast numerical simulation of focused ultrasound treatments during respiratory motion with discontinuous motion boundaries
 
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2017
Journal Article
Title

Fast numerical simulation of focused ultrasound treatments during respiratory motion with discontinuous motion boundaries

Abstract
Objective: Focused ultrasound (FUS) is rapidly gaining clinical acceptance for several target tissues in the human body. Yet, treating liver targets is not clinically applied due to a high complexity of the procedure (noninvasiveness, target motion, complex anatomy, blood cooling effects, shielding by ribs, and limited image-based monitoring). To reduce the complexity, numerical FUS simulations can be utilized for both treatment planning and execution. These use-cases demand highly accurate and computationally efficient simulations. Methods: We propose a numerical method for the simulation of abdominal FUS treatments during respiratory motion of the organs and target. Especially, a novel approach is proposed to simulate the heating during motion by solving Pennes' bioheat equation in a computational reference space, i.e., the equation is mathematically transformed to the reference. The approach allows for motion discontinuities, e.g., the sliding of the liver along the abdominal wall. Results: Implementing the solver completely on the graphics processing unit and combining it with an atlas-based ultrasound simulation approach yields a simulation performance faster than real time (less than 50-s computing time for 100 s of treatment time) on a modern off-the-shelf laptop. The simulation method is incorporated into a treatment planning demonstration application that allows to simulate real patient cases including respiratory motion. Conclusion: The high performance of the presented simulation method opens the door to clinical applications. Significance: The methods bear the potential to enable the application of FUS for moving organs.
Author(s)
Schwenke, M.
Georgii, J.
Preusser, T.
Journal
IEEE Transactions on Biomedical Engineering BME  
DOI
10.1109/TBME.2016.2619741
Language
English
Fraunhofer-Institut für Digitale Medizin MEVIS  
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