A Monte Carlo model of synchrotron radiotherapy shows good agreement with experimental dosimetry measurements: Data from the imaging and medical beamline at the Australian Synchrotron.
Phys Med
; 77: 64-74, 2020 Sep.
Article
en En
| MEDLINE
| ID: mdl-32791426
Experimental measurement of Synchrotron Radiotherapy (SyncRT) doses is challenging, especially for Microbeam Radiotherapy (MRT), which is characterised by very high dynamic ranges with spatial resolutions on the micrometer scale. Monte Carlo (MC) simulation is considered a gold standard for accurate dose calculation in radiotherapy, and is therefore routinely relied upon to produce verification data. We present a MC model for Australian Synchrotron's Imaging and Medical Beamline (IMBL), which is capable of generating accurate dosimetry data to inform and/or verify SyncRT experiments. Our MC model showed excellent agreement with dosimetric measurement for Synchrotron Broadbeam Radiotherapy (SBBR). Our MC model is also the first to achieve validation for MRT, using two methods of dosimetry, to within clinical tolerances of 5% for a 20×20 mm2 field size, except for surface measurements at 5 mm depth, which remained to within good agreement of 7.5%. Our experimental methodology has allowed us to control measurement uncertainties for MRT doses to within 5-6%, which has also not been previously achieved, and provides a confidence which until now has been lacking in MRT validation studies. The MC model is suitable for SyncRT dose calculation of clinically relevant field sizes at the IMBL, and can be extended to include medical beamlines at other Synchrotron facilities as well. The presented MC model will be used as a validation tool for treatment planning dose calculation algorithms, and is an important step towards veterinary SyncRT trials at the Australian Synchrotron.
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Base de datos:
MEDLINE
Asunto principal:
Radiometría
/
Sincrotrones
Tipo de estudio:
Health_economic_evaluation
País/Región como asunto:
Oceania
Idioma:
En
Revista:
Phys Med
Asunto de la revista:
BIOFISICA
/
BIOLOGIA
/
MEDICINA
Año:
2020
Tipo del documento:
Article