Identifying optimal clinical scenarios for synchrotron microbeam radiation therapy: A treatment planning study

Lloyd M.L. Smyth, Liam R. Day, Katrina Woodford, Peter A.W. Rogers, Jeffrey C. Crosbie, Sashendra Senthi

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)

Abstract

Purpose: Synchrotron Microbeam Radiation Therapy (MRT) is a pre-clinical modality characterised by spatial dose fractionation on a microscopic scale. Treatment planning studies using clinical datasets have not yet been conducted. Our aim was to investigate MRT dose-distributions in scenarios refractory to conventional treatment and to identify optimal settings for a future Phase I trial. Methods: MRT plans were generated for seven scenarios where re-irradiation was performed clinically. A hybrid algorithm, combining Monte Carlo and convolution-based methods, was used for dose-calculation. The valley dose to organs at risk had to respect the single fraction tolerance doses achieved in the corresponding re-irradiation plans. The resultant peak dose and the peak-to-valley dose ratio (PVDR) at the tumour target volume were assessed. Results: Peak doses greater than 80 Gy in a single fraction, and PVDRs greater than 10, could be achieved for plans with small (<35 cm 3 ) or shallow volumes, particularly recurrent glioblastoma, head and neck tumours, and select loco-regionally recurrent breast cancer sites. Treatment volume was a more important factor than treatment depth in determining the PVDR. The mean PVDR correlated strongly with the size of the target volume (r s = −0.70, p = 0.01). The PVDRs achieved in these clinical scenarios are considerably lower than those reported in previous pre-clinical studies. Conclusion: Our findings suggest that head and neck sites will be optimal scenarios for MRT.

Original languageEnglish
Pages (from-to)111-119
Number of pages9
JournalPhysica Medica
Volume60
DOIs
Publication statusPublished - Apr 2019

Keywords

  • Microbeams
  • Synchrotron X-rays
  • Treatment planning

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