Abstract
MR guided focused ultrasound (MRgFUS) therapy has been a promising treatment modality for many neurological disorders. However, the lack of real-time image processing software platform sets barriers for relevant pre-clinical researches. This work intends to develop an integrated software for MRgFUS therapy. The software contains three functional modules: a communication module, an image post-processing module, and a visualization module. The communication module provides a data interface with an open-source MR image reconstruction platform (Gadgetron) to receive the reconstructed MR images in real-time. The post-processing module contains the algorithms of image coordinate registration, focus localization by MR acoustic radiation force imaging (MR-ARFI), temperature and thermal dose calculations, motion correction, and temperature feedback control. The visualization module displays monitoring information and provides a user-machine interface. The software was tested to be compatible with systems from two different vendors and validated in multiple scenarios for MRgFUS. The software was tested in many ex vivo and in vivo experiments to validate its functions. The in vivo transcranial focus localization experiments were carried out for targeting the focused ultrasound in neuromodulation.
Highlights
MR guided focused ultrasound (MRgFUS) therapy has been a promising treatment modality for many neurological d isorders, such as essential tremor [1], Parkinson’s disease [2], Alzheimer disease [3] etc
We developed an MRgFUS software named MARFit
MR acoustic radiation force imaging (MR-acoustic radiation force ima ging (ARFI)) was performed in a monkey to verify the transcranial focus localization
Summary
MR guided focused ultrasound (MRgFUS) therapy has been a promising treatment modality for many neurological d isorders, such as essential tremor [1], Parkinson’s disease [2], Alzheimer disease [3] etc. MR plays a crucial role in nearly every step of FUS therapy, from treatment planning to real-time monitoring, and trea tment assessment. MRgFUS demands faster image acquisition, reconstruction, and post-processing compared to diagnostic MR imaging. The anatomical images and processed monitoring information should be visualized with minimum latency for real-time guidance. Automatic adjustment of FUS parameters combined with safety concerns is indispensable. All these specific requirements raise the need for a dedicated, extensible MRgFUS softwa re pla tform
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