MatMRI and MatHIFU: software toolboxes for real-time monitoring and control of MR-guided HIFU

BACKGROUND: The availability of open and versatile software tools is a key feature to facilitate pre-clinical research for magnetic resonance imaging (MRI) and magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) and expedite clinical translation of diagnostic and therapeutic medical applications. In the present study, two customizable software tools that were developed at the Thunder Bay Regional Research Institute are presented for use with both MRI and MR-HIFU. Both tools operate in a MATLAB(®;) environment. The first tool is named MatMRI and enables real-time, dynamic acquisition of MR images with a Philips MRI scanner. The second tool is named MatHIFU and enables the execution and dynamic modification of user-defined treatment protocols with the Philips Sonalleve MR-HIFU therapy system to perform ultrasound exposures in MR-HIFU therapy applications. METHODS: MatMRI requires four basic steps: initiate communication, subscribe to MRI data, query for new images, and unsubscribe. MatMRI can also pause/resume the imaging and perform real-time updates of the location and orientation of images. MatHIFU requires four basic steps: initiate communication, prepare treatment protocol, and execute treatment protocol. MatHIFU can monitor the state of execution and, if required, modify the protocol in real time. RESULTS: Four applications were developed to showcase the capabilities of MatMRI and MatHIFU to perform pre-clinical research. Firstly, MatMRI was integrated with an existing small animal MR-HIFU system (FUS Instruments, Toronto, Ontario, Canada) to provide real-time temperature measurements. Secondly, MatMRI was used to perform T2-based MR thermometry in the bone marrow. Thirdly, MatHIFU was used to automate acoustic hydrophone measurements on a per-element basis of the 256-element transducer of the Sonalleve system. Finally, MatMRI and MatHIFU were combined to produce and image a heating pattern that recreates the word ‘HIFU’ in a tissue-mimicking heating phantom. CONCLUSIONS: MatMRI and MatHIFU leverage existing MRI and MR-HIFU clinical platforms to facilitate pre-clinical research. MatMRI substantially simplifies the real-time acquisition and processing of MR data. MatHIFU facilitates the testing and characterization of new therapy applications using the Philips Sonalleve clinical MR-HIFU system. Under coordination with Philips Healthcare, both MatMRI and MatHIFU are intended to be freely available as open-source software packages to other research groups.