Quantitative prediction of the extent of pelvic tumour ablation by magnetic resonance-guided high intensity focused ultrasound

Abstract

Background

Patient suitability for magnetic resonance-guided high intensity focused ultrasound (MRgHIFU) therapy of pelvic tumors is currently assessed by visual estimation of the proportion of tumor that can be reached by the device’s focus (coverage). Since it is important to assess whether enough energy reaches the tumor to achieve ablation, a methodology for estimating the proportion of the tumor that can be ablated (treatability) was developed. Predicted treatability was compared against clinically achieved thermal ablation.

Methods

MR Dixon sequence images of five patients with recurrent gynecological tumors were acquired during their treatment. Acousto-thermal simulations were performed using k-Wave for three exposure points (the deepest and shallowest reachable focal points within the tumor, identified from tumor coverage analysis, and a point halfway in-between) per patient. Interpolation between the resulting simulated ablated tissue volumes was used to estimate the maximum treatable depth and hence, tumor treatability. Predicted treatability was compared both to predicted tumor coverage and to the clinically treated tumor volume. The intended and simulated volumes and positions of ablated tissues were compared.

Results

Predicted treatability was less than coverage by 52% (range: 31–78%) of the tumor volume. Predicted and clinical treatability differed by 9% (range: 1–25%) of tumor volume. Ablated tissue volume and position varied with beam path length through tissue.

Conclusion

Tumor coverage overestimated patient suitability for MRgHIFU therapy. Employing patient-specific simulations improved treatability assessment. Patient treatability assessment using simulations is feasible.

Keywords:

• High intensity focused ultrasound
• modeling
• pelvis
• treatment prediction
• simulation

Geolocation information

The study was conducted at the Institute of Cancer Research and the Royal Marsden Hospital, Sutton, Surrey, United Kingdom.

Acknowledgments

The authors would like to thank: Matthew Blackledge, Simon Doran and Matthew Orton from the Institute of Cancer Research (ICR) for their technical support; Bradley Treeby and Elly Martin from University College London (UCL), and Jiří Jaroš from Brno University of Technology, for their support with k-Wave; and Ari Partanen and others from Profound Medical for their support. We are grateful to Philips for their loan of the Sonalleve system to The Royal Marsden Hospital (RMH), and we acknowledge the support of the RMH MRI team, volunteers and patients, the Focused Ultrasound Foundation, CRUK and EPSRC in association with MRC & Department of Health (C1060/A10334, C1060/A16464), the NHS, the NIHR Biomedical Research Centre, the Clinical Research Facility in Imaging, and the Cancer Research Network.

Disclosure statement

The lead author was the recipient of a studentship supported by Philips. This study resulted from research performed as part of a studentship supported by Philips. The views expressed are those of the authors, and not necessarily those of the National Health Service (NHS), the Department of Health, the ICR, the RMH, UCL, Profound Medical, Philips or the NIHR.

Data availability statement

The data that support the findings of this study are not available due to limitations in the ethical review.

Additional information

Funding

The first author (NFDL) produced this work whilst on a studentship supported by Philips. Funding from the NIHR Research for Patient Benefit programme [PB-PG-0815-20001] enabled the acquisition of data for the study.