Speaker
Description
Radiation therapy is commonly used for cancer treatment. However, not only tumor tissue is affected by ionizing radiation, but also healthy tissue is damaged [1]. The ratio of tumor control with respect to healthy tissue damage needs to be optimised by choosing suitable particle types, energies, and dose rates. Healthy tissue is less affected if dose is applied with very high dose rates, i.e. short pulse duration, while tumor control is approximately independent of dose rate (FLASH effect) [2]. Therefore, high dose rate treatments might allow for larger treatment windows and better tumor regulation.
There is no detector at the time of this abstract (April 2023) that is capable of correctly reconstructing spectra of the radiation fields occuring in FLASH applications. In this abstract, simulations of a prototype of a spectrometer based on the hybrid photon-counting energy-resolving pixel detector Dosepix are presented [3]. Dosepix has been developed by a collaboration of Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and the European Organisation for Nuclear Research (CERN). A 300 µm thick silicon sensor layer is attached to Dosepix ASIC. Deposited energies are sorted into a histogram of 16 energy bins by the individual pixel electronics.
Ten Dosepix detectors are aligned behind each other. Filters of different materials and thicknesses are positioned between the detectors. Therefore, information about the particle type and energy is accessible from its absorption behaviour, i.e. the ratios of registered events in the individual Dosepix detectors. Read-out electronics is taken into account by the utilised Allpix-Squared simulation only in terms of its scattering behaviour. The novel CSADigitizer-Module is used to receive information about the detector behaviour under ultra-high dose rates. Spectral reconstruction is currently performed via deconvolution similar to the procedure described in [4]. Exhaustive simulation data is hereby crucial to determine the response of each energy-channel of Dosepix in each layer. In the future, a different analysis approach utilising a neural network is going to be compared to the classical deconvolution.
[1] K. Lindberg et al: J Thoracic Oncol Journal of Thoracic Oncology, Volume 12, Issue 1, Supplement, 2017, Page S340, ISSN 1556-0864,
[2] A. Schüller et al: Physica Medica 80, 2020, Page 134–150
[3] W. Wong et al: Radiation Measurements, 2011, vol. 46, no. 12, Page 1619–1623
[4] R. Behrens: PTB-Dos-44: ISBN 978-3-86509-002-7
| Will the talk be given in person or remotely? | In person |
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