A commercial treatment planning system with a hybrid dose calculation algorithm for synchrotron radiotherapy trials
Details
Publication Year 2021-03,Volume 66,Issue #5,Page 055016
Journal Title
Physics in Medicine & Biology
Publication Type
Research article
Abstract
Synchrotron Radiotherapy (SyncRT) is a preclinical radiation treatment which delivers synchrotron x-rays to cancer targets. SyncRT allows for novel treatments such as Microbeam Radiotherapy, which has been shown to have exceptional healthy tissue sparing capabilities while maintaining good tumour control. Veterinary trials in SyncRT are anticipated to take place in the near future at the Australian Synchrotron's Imaging and Medical Beamline (IMBL). However, before veterinary trials can commence, a computerised treatment planning system (TPS) is required, which can quickly and accurately calculate the synchrotron x-ray dose through patient CT images. Furthermore, SyncRT TPS's must be familiar and intuitive to radiotherapy planners in order to alleviate necessary training and reduce user error. We have paired an accurate and fast Monte Carlo (MC) based SyncRT dose calculation algorithm with Eclipse(TM), the most widely implemented commercial TPS in the clinic. Using Eclipse(TM), we have performed preliminary SyncRT trials on dog cadavers at the IMBL, and verified calculated doses against dosimetric measurement to within 5% for heterogeneous tissue-equivalent phantoms. We have also performed a validation of the TPS against a full MC simulation for constructed heterogeneous phantoms in Eclipse(TM), and showed good agreement for a range of water-like tissues to within 5%-8%. Our custom Eclipse(TM) TPS for SyncRT is ready to perform live veterinary trials at the IMBL.
Keywords
*Algorithms; Animals; Cadaver; Computer Simulation; Dog Diseases/*radiotherapy; Dogs; Monte Carlo Method; Neoplasms/radiotherapy/*veterinary; *Phantoms, Imaging; Radiometry; Radiotherapy Dosage; Radiotherapy Planning, Computer-Assisted/*methods; Synchrotrons/*instrumentation
Department(s)
Physical Sciences
PubMed ID
33373979
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Creation Date: 2026-01-28 12:31:57
Last Modified: 2026-01-28 12:33:28
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