- Open Access
MatMRI and MatHIFU: software toolboxes for real-time monitoring and control of MR-guided HIFU
© Zaporzan et al.; licensee BioMed Central Ltd. 2013
- Received: 18 December 2012
- Accepted: 28 March 2013
- Published: 4 June 2013
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.
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.
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.
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.
- Transmission Control Protocol
- Magnetic Resonance Imaging Scanner
- Acoustic Power
- Philips Healthcare
- Ultrasound Exposure
Pre-clinical research is a fundamental step in the development of new diagnostic and therapeutic applications. However, this work is often time-consuming and may require multi-disciplinary teams of physicists, medical doctors, biologists, and engineers. Magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) is a novel treatment modality that enables targeted thermal therapy under magnetic resonance imaging (MRI) guidance. In terms of capital cost, the access to an MRI scanner and to an MRI-compatible HIFU device represents one of the most expensive investments for a research team. It is therefore desirable that this investment can be leveraged to its maximum potential to conduct various pre-clinical MR-HIFU projects. The Sonalleve system (Philips Healthcare, Vantaa, Finland) is a clinical MR-HIFU platform used for thermal therapies and operates in tandem with 1.5- and 3.0-T Achieva and Ingenia (Philips Healthcare, Best, the Netherlands) MRI scanners. The MR-HIFU device communicates with the MRI scanner to obtain images that are used for real-time calculations of temperature maps using a technique based on the water-proton resonance frequency shift (PRFS) . This MR-HIFU platform includes a transducer with 256 independent elements operating at a frequency between 1.0 and 1.5 MHz and has a focusing length of 12 cm and a diameter of 13 cm. The system also includes the driving electronics and a motorized subsystem that allows positioning the transducer with 5 degrees of freedom. The system is clinically approved for the treatment of uterine fibroids in several regions including Canada, Europe, India, and Korea .
To showcase results achieved through the use of MatMRI and MatHIFU, four applications that were developed at TBRRI and the Hospital for Sick Children (Toronto, Ontario, Canada) are presented. These applications show the ability of MatMRI and MatHIFU to control MR imaging in real time for pre-clinical animal studies, generate thermal maps using T2-based thermometry, drive individual transducer elements to perform acoustic characterization, and execute custom ablation patterns.
Integration of MatMRI with a small animal MR-HIFU system for the treatment of abscesses in a murine model
End points were at days 1 and 4 after MR-HIFU treatment. For each end point, 18 animals were randomly assigned into three groups with 6 animals each: control, treatment with an acoustic power of 25 W, and treatment with an acoustic power of 35 W. Results indicated that an exposure with an acoustic power of 35 W was able to induce a significant ( p < 0.05) reduction of the bacteria concentration in the abscess when compared to non-treated abscesses and low-power exposures. The bacteria concentration (mean ± standard deviation) at the 4-day end point was 1.0 ± 1.3 × 104, 0.6 ± 0.6 × 104, and 0.09 ± 0.2 × 104 colony-forming units/ μ L for the control, low power, and high power groups, respectively.
T2-based thermometry with MatMRI for the MR-HIFU treatment of the bone marrow
Hydrophone measurements with MatHIFU
Turn off all elements.
Turn on only element n.
Turn on pulsed ultrasound exposure.
Turn off ultrasound after 1.8 s of exposure.
Remain inactive until all data collected by the oscilloscope are transferred.
Prior to the protocol execution, the oscilloscope was prepared to capture 64 samples of the hydrophone signal over time. Querying the status of the MR-HIFU system was used to determine when the ultrasound exposure was finished, after which the average reading of the 64 acquisitions was transferred through an Ethernet link to the external computer running MatHIFU. Post-transfer, a modification to change the active transducer element was executed and the protocol was restarted. The pseudo-code for the whole acquisition, execution, and modification step of the treatment protocol was as follows:
Do For All Elements In Transducer Prepare Oscilloscope If First Element of Transducer Execute Protocol Else Execute Modification Go to Step 1 of Protocol Wait Until Status of MR-HIFU Indicates End of Ultrasound Exposure Collect Data from Oscilloscope Do Next Transducer Element
The ‘HIFU’ application using MatMRI in conjunction with MatHIFU
Move the transducer to the center of the letter.
Pause for 2 s. This pause is used to acquire a reference image for thermometry.
Apply HIFU with an acoustic power of 80 W and electronically steer the focal point in 2-mm steps along the 18-mm-long line. The time between steps (trajectory interval) was set to 25 ms.
Turn off the ultrasound after 8 s of exposure.
Remain inactive. This allows protocol modifications to be performed.
The coordinates for the transducer position and focal point steering were initially set to produce the first line segment (Figure 5). A cooling time of 60 s was observed after the ultrasound was turned off, and then a protocol modification was created and executed to change the transducer position as well as the steering coordinates. MatMRI was used to collect MR magnitude and phase images that were utilized to calculate temperature change using the PRFS technique. Magnetic drift was monitored in non-heated regions, and a correction was applied . The MR parameters for the thermometry were as follows: FOV = 200 mm, pixel size = 1.1 mm, slice thickness = 7 mm, TE/TR = 20/30 ms, flip angle = 19.5°, acquisition matrix = 180, reconstruction matrix = 224, ETL = 9, NEX = 1, and dynamic time = 0.59 s. Reference images for thermometry were acquired at the beginning of each letter. The protocol duration was 637 s, during which 1,080 images were acquired. The pseudo-code for the image acquisition as well as for the protocol execution and modification steps was:
Do Until All Segments Are Finished If first segment Execute Protocol Else Execute Modification If New Letter Go to Step 1 of Protocol Else Go to Step 3 of Protocol If Transducer Movement Just Finished Collect Magnitude and Phase Image For Reference Else Collect Image Calculate Temperature Change If End of Cooling Do next segment
MatMRI and MatHIFU are software tools to perform and facilitate pre-clinical studies. These tools leverage research centers’ multi-million dollar investments in clinical MRI and MR-HIFU hardware, and their greatest strength resides in integrating real-time MRI measurements and controlling the MR-HIFU system with minimal effort. Both MatMRI and MatHIFU toolboxes operate within the MATLAB®; computational software environment, which is well known in many research laboratories. In the present study, four projects were presented to showcase the capabilities of these software tools to simplify and accelerate the development of new MR-HIFU applications. MatMRI was seamlessly integrated with an existing MR-HIFU pre-clinical small animal system. In addition, the development of a new framework to perform T2-based thermometry was facilitated through the use of MatMRI. Furthermore, MatHIFU was used to activate and precisely control the transducer element driving signals of a clinical MR-HIFU system to enable acoustic pressure measurements using a hydrophone. Finally, MatMRI and MatHIFU were combined in a demo application to highlight the capabilities of these tools in pre-clinical thermal therapy applications.
MatMRI substantially simplifies the acquisition and processing of real-time, dynamic MR data, and it may have potential beyond thermal therapy applications. As indicated by the presented examples, applications requiring real-time processing of MR data, such as MR thermometry or functional MRI, may benefit from this software tool. On the other hand, MatHIFU facilitates the exploration of new therapeutic applications using the Philips Sonalleve clinical MR-HIFU system. MatHIFU opens up new opportunities for rapidly adapting this system for application-specific needs in pre-clinical research. MR-HIFU thermal ablation, HIFU-mediated mild hyperthermia and drug delivery, as well as applications utilizing HIFU-induced mechanical effects may benefit from the use of these tools in pre-clinical work.
Both MatMRI and MatHIFU are intended to be freely available as open-source projects to other research groups under the coordination of Philips Healthcare. These tools are meant to facilitate pre-clinical MR-HIFU research and aid collaboration between research teams. The first collaboration under this model initiated by TBRRI took place with the Hospital for Sick Children. The exchange of ideas has been mutually beneficial for both teams, and we aim to expand the community of users to drive the future development of these tools.
In this study, we presented two software tools to facilitate the research and development of pre-clinical MRI and MR-HIFU applications. MatMRI allows dynamic acquisition and processing of real-time MR data, and MatHIFU allows adaptable and robust control of the Philips Sonalleve clinical MR-HIFU system. Four applications were presented to showcase the capabilities of these tools. MatMRI and MatHIFU may simplify as well as accelerate the development process of new MR-HIFU applications and are meant to foster collaboration between research teams. These tools are intended to be freely available to other research groups under the coordination of Philips Healthcare.
All experiments with MatMRI were performed using a Philips Achieva 3.0T TX scanner. MatHIFU experiments were done using the Philips Sonalleve MR-HIFU system.
MatMRI uses the eXTernal Control (XTC) protocol  that was developed to provide low-latency access to MR data as well as to control an MRI scanner in real time. Among other applications, the XTC protocol is used to provide real-time MR data to the Sonalleve clinical MR-HIFU system. A .Net (Microsoft, Redmond, WA, USA) class was written in the C# programming language (Microsoft, Redmond, WA, USA) to encapsulate all the low-level communication protocols. Furthermore, a class in the MATLAB ® programming language was written to expose high-level functions to the end user. These functions are utilized to acquire MR data and to control the scanner.
Available MatMRI functionality includes the acquisition of individual imaging slices as well as volumetric data. The acquisition of individual slices is the preferred choice for real-time imaging because the images are transferred to MatMRI as soon as they are reconstructed. Volumetric acquisition is preferred when acquiring large data sets (multiple 2D slices) in a single dynamic step. The volumetric data are ordered by type, stack, and slice number. Multiple users can subscribe to the data simultaneously. Many different types of images (T1-weighted, T2-weighted, B1 map, etc.), number of slices, stacks, and dynamics can be transferred without any data size limitation related to the active memory of the MR console.
Pause/resume image acquisition
MatMRI allows the end user to pause and resume the MR image acquisition. This is useful in applications that will acquire hundreds or thousands of dynamic images and in which it is desirable that the user code controls the acquisition timing.
Change imaging stack positioning
The position of each imaging stack as well as its stack orientation are user-redefinable in real time. This function is important for dynamic adjustments of the imaging planes based on user code decisions.
Creation of treatment protocols
Each treatment protocol has it its own user-specified identifier such as ‘Protocol_1,’ ‘Heating_Region,’ etc.
The protocols are created with the helper class HIFU_ProtocolBuilder, which contains functions to build the following commands:
Start of continuous ultrasound exposure. This command initiates a continuous ultrasound exposure and allows, for example, the acoustic power, ultrasound frequency, focal point trajectory coordinates, and trajectory interval to be specified as command attributes. The trajectory can be defined as a series of points where the time at each point (trajectory interval) is specified.
Start of pulsed ultrasound exposure. This command initiates an ultrasound exposure with controllable duty cycle, ultrasound frequency, and trajectory coordinates. It also allows synchronizing each pulse with an external trigger if necessary.
Movement of transducer. This command changes the current position of the transducer with 5 degrees of freedom for 3D Cartesian positioning and two rotation angles over the left-right and head-foot directions.
Pausing. This type of command allows defining ‘non-operational’ states for the MR-HIFU system or waiting for the completion of a previous command. This command facilitates the protocol step timing.
R&D command. This is a very powerful command that allows the user to control the 256-element transducer at a low level. The command allows, among other functions, the selection of active/inactive elements and the application of specific phase and/or amplitude to one or more active elements.
Each of these commands has an index that determines the order of execution. In addition, the commands feature a time index that precisely establishes the time point for command execution.
Modification of protocols
Modification commands are similar to the protocol commands. The modifications also have their own identifier (such as ‘Modification_1,’ ‘UpdateExposure,’ etc.) and are created with the helper class HIFU_ModificationBuilder, which contains the functions to build modifications. The most notable difference with the protocol commands is that a modification command specifies the position in the original protocol that will be modified as well as the parameter(s) that is/are to be adjusted.
Querying of status
The MR-HIFU system includes several status indicators that can be used in decision making. The indicators that can be queried include (but are not limited to) the following:
Current position of the transducer
Current total forward and reflected acoustic power
Status of ultrasound exposure (on/off)
Status of transducer movement (moving/idle)
Current time index of execution
The status indicators can be used to synchronize events with other software or hardware components. Examples include data acquisitions using oscilloscopes, temperature sensors, and any other external device.
Contribution of Philips Healthcare
Under a research agreement between Philips Healthcare and the Thunder Bay Regional Research Institute, Philips Healthcare provided libraries, documentation, and example code for the use of the XTC protocol. Philips Healthcare also provided specialized training and example code for the customization of the control of the Sonalleve system.
Access to toolboxes
As indicated in the ‘Discussion’ subsection, both MatMRI and MatHIFU are aimed to be freely available to researchers in coordination with Philips Healthcare. The tools are hosted in a private repository in Github (http://www.github.com). To gain access to the repository, please contact Samuel Pichardo (email@example.com), with copy to Charles Mougenot (firstname.lastname@example.org) and Ari Partanen (email@example.com). You can also get in contact with Samuel Pichardo through his personal web page (http://www.proteus-mrighifu.net).
This project is partially funded by the Ontario Research Fund Round 2. The authors acknowledge Yasmina Berber for sharing her work on the MR communication protocol. The authors also acknowledge Dr. Erkki Vahala, Ronald Holthuizen, and Jouke Smink of Philips Healthcare for their technical support. Finally, the authors acknowledge Dr. Sham Sokka of Philips Healthcare for supporting and sharing our vision to this effort.
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