Estimation of neutron-equivalent dose in organs of patients undergoing radiotherapy by the use of a novel online digital detector

F. Sánchez-Doblado, C. Domingo, F. Gómez, B. Sánchez-Nieto, J. L. Muñiz, M. J. García-Fusté, M. R. Expósito, R. Barquero, G. Hartmann, J. A. Terrón, J. Pena, R. Méndez, F. Gutiérrez, F. X. Guerre, J. Roselló, L. Núñez, L. Brualla-González, F. Manchado, A. Lorente, E. GallegoR. Capote, D. Planes, J. I. Lagares, X. González-Soto, F. Sansaloni, R. Colmenares, K. Amgarou, E. Morales, R. Bedogni, J. P. Cano, F. Fernández

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39 Citations (Scopus)


Neutron peripheral contamination in patients undergoing high-energy photon radiotherapy is considered as a risk factor for secondary cancer induction. Organ-specific neutron-equivalent dose estimation is therefore essential for a reasonable assessment of these associated risks. This work aimed to develop a method to estimate neutron-equivalent doses in multiple organs of radiotherapy patients. The method involved the convolution, at 16 reference points in an anthropomorphic phantom, of the normalized Monte Carlo neutron fluence energy spectra with the kerma and energy-dependent radiation weighting factor. This was then scaled with the total neutron fluence measured with passive detectors, at the same reference points, in order to obtain the equivalent doses in organs. The latter were correlated with the readings of a neutron digital detector located inside the treatment room during phantom irradiation. This digital detector, designed and developed by our group, integrates the thermal neutron fluence. The correlation model, applied to the digital detector readings during patient irradiation, enables the online estimation of neutron-equivalent doses in organs. The model takes into account the specific irradiation site, the field parameters (energy, field size, angle incidence, etc) and the installation (linac and bunker geometry). This method, which is suitable for routine clinical use, will help to systematically generate the dosimetric data essential for the improvement of current risk-estimation models. © 2012 Institute of Physics and Engineering in Medicine.
Original languageEnglish
Pages (from-to)6167-6191
JournalPhysics in Medicine and Biology
Publication statusPublished - 7 Oct 2012


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