- Oral presentation
- Open Access
Real-time MRI feedback of cavitation ablation therapy (histotripsy)
© Allen and Hall; licensee BioMed Central Ltd. 2015
Published: 30 June 2015
Histotripsy ablation of liver tumors is a non-invasive surgery that uses high-intensity acoustic pulses to control an inertial cavitation cloud. Repeated exposure to the cavitation cloud renders a target tissue into a homogenous slurry which is then gradually absorbed by the body. Like other non-invasive surgeries, histotripsy requires a feedback system that can estimate therapy location and dose in real-time. Because the time-average power output of histotripsy is very small, the treatment region does not express a significant rise in temperature, making MRI thermometry an ineffective method to actively monitor therapy. Previous work has shown that MRI pulse sequences can be made sensitive to the chaotic water flow present during inertial cavitation. This is done by synchronizing the timing of the histotripsy pulses with the timing of the sequence’s gradient waveforms. Incoherent water flow caused by cavitation attenuates the MR signal through a process similar to that used in diffusion-weighted MRI. It was shown that these sequences can give localized contrast specific to histotripsy bubble clouds. However, the MR images could only be acquired in a piecemeal fashion over several minutes such that a single image represented the influence of many cavitation events. Here, we introduce a single-shot MR acquisition sequence that is able to rapidly acquire a complete MR image and remain sensitive to histotripsy cavitation. This is done by synchronizing each histotripsy pulse with incoherent motion-weighting gradients placed just before the readout portion of the sequence. When repeated at the same rate as the histotripsy pulses, the resulting MR images can give feedback on the location of every cavitation cloud applied to the target tissue.
Results and conclusions
Author Timothy Hall has equity, consulting, and royalty interests in Histosonics Inc. This work is funded in part by NIH grants R01DK087871, R01CA134579.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.