RayStation/GATE Monte Carlo simulation framework for verification of proton therapy based on theN imaging.

Phys Med Biol

Particle Therapy Research Center (PARTREC), Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Published: September 2024

.N, having a half-life of 11 ms, is a highly effective positron emitter that can potentially provide near real-time feedback in proton therapy. There is currently no framework for comparing and validating positron emission imaging ofN. This work describes the development and validation of a Monte Carlo (MC) framework to calculate the images ofN, as well as long-lived isotopes, originating from activation by protons.. The available dual-panel Biograph mCT PET scanner was modeled in GATE and validated by comparing the simulated sensitivity map with the measured one. The distributions ofN and long-lived isotopes were calculated by RayStation and used as the input of GATE simulations. The RayStation/GATE combination was verified using proton beam irradiations of homogeneous phantoms. A 120 MeV pulsed pencil beam with 10protons per pulse was used. Two-dimensional images were created from the GATE output and compared with the images based on the measurements and the 1D longitudinal projection of the full 2D image was used to calculate theN activity range.. The simulated sensitivity in the center of the FoV (5.44%) agrees well with the measured one (5.41%). The simulated and measured 2D sensitivity maps agree in good detail. The relative difference between the measured and simulated positron activity range for bothN and long-lived isotopes is less than 1%. The broadening of theN images relative to those of the longer-lived isotopes can be understood in terms of the large positron range ofN.. We developed and validated a MC framework based on RayStation/GATE to support the in-beam PET method for quality assurance of proton therapy. The inclusion of the very short-lived isotopeN makes the framework useful for developing near real-time verification. This represents a significant step towards translatingN real-time in vivo verification to the clinic.

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Source
http://dx.doi.org/10.1088/1361-6560/ad7d5cDOI Listing

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