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Register a new userResponse to the authors of On the (un)effectiveness of Proton Boron Capture in Proton Therapy
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Giuseppe A Pablo Cirrone
Publication date
2018
fields
Physics
and research's language is
English
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This manuscript provides a response to a recent report by Mazzone et al. available online on arXiv that, in turn, tentatively aims at demonstrating the inefficacy of proton boron capture in hadrotherapy. We clarify that Mazzone et al. do not add any scientific or technical insights to the points extensively discussed in the original manuscript by Cirrone et al., and/or in the series of iterations had with the Referee, which ultimately lead to the publication of our original and pioneering experimental work. Here we summarize some of the key points of the long scientific debate we had during the review process of paper by Cirrone et al., which are very similar to the considerations presented by Mazzone et al.. In conclusion, no quantitative explanation of our robust experimental achievements presented in Cirrone et al. is provided in Mazzone et al.
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Selective accumulation of B-10 compound in tumour tissue is a fundamental condition for the achievement of BNCT (Boron Neutron Capture Therapy), since the effectiveness of therapy irradiation derives just from neutron capture reaction of B-10. Hence, the determination of the B-10 concentration ratio, between tumour and healthy tissue, and a control of this ratio, during the therapy, are essential to optimise the effectiveness of the BNCT, which it is known to be based on the selective uptake of B-10 compound. In this work, experimental methods are proposed and evaluated for the determination in vivo of B-10 compound in biological samples, in particular based on neutron radiography and gammaray spectroscopy by telescopic system. Measures and Monte Carlo calculations have been performed to investigate the possibility of executing imaging of the 10B distribution, both by radiography with thermal neutrons, using 6LiF/ZnS:Ag scintillator screen and a CCD camera, and by spectroscopy, based on the revelation of gamma-ray reaction products from B-10 and the H. A rebuilding algorithm has been implemented. The present study has been done for the standard case of B-10 uptake, as well as for proposed case in which, to the same carrier, is also synthesized Gd-157, in the amount of is used like a contrast agent in NMRI.
Proton beam therapy can potentially offer improved treatment for cancers of the head and neck and in paediatric patients. There has been a sharp uptake of proton beam therapy in recent years as improved delivery techniques and patient benefits are observed. However, treatments are currently planned using conventional x-ray CT images due to the absence of devices able to perform high quality proton computed tomography (pCT) under realistic clinical conditions. A new plastic-scintillator-based range telescope concept, named ASTRA, is proposed here as the energy tagging detector of a pCT system. Simulations conducted using Geant4 yield an expected energy resolution of 0.7% and have demonstrated the ability of ASTRA to track multiple protons simultaneously. If calorimetric information is used the energy resolution could be further improved to about 0.5%. Assuming clinical beam parameters the system is expected to be able to efficiently reconstruct at least, 10$^8$ protons/s. The performance of ASTRA has been tested by imaging phantoms to evaluate the image contrast and relative stopping power reconstruction.
Fast procedures for the beam quality assessment and for the monitoring of beam energy modulations during the irradiation are among the most urgent improvements in particle therapy. Indeed, the online measurement of the particle beam energy could allow assessing the range of penetration during treatments, encouraging the development of new dose delivery techniques for moving targets. Towards this end, the proof of concept of a new device, able to measure in a few seconds the energy of clinical proton beams (from 60 to 230 MeV) from the Time of Flight (ToF) of protons, is presented. The prototype consists of two Ultra Fast Silicon Detector (UFSD) pads, featuring an active thickness of 80 um and a sensitive area of 3 x 3 mm2, aligned along the beam direction in a telescope configuration, connected to a broadband amplifier and readout by a digitizer. Measurements were performed at the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy), at five different clinical beam energies and four distances between the sensors (from 7 to 97 cm) for each energy. In order to derive the beam energy from the measured average ToF, several systematic effects were considered, Monte Carlo simulations were developed to validate the method and a global fit approach was adopted to calibrate the system. The results were benchmarked against the energy values obtained from the water equivalent depths provided by CNAO. Deviations of few hundreds of keV have been achieved for all considered proton beam energies for both 67 and 97 cm distances between the sensors and few seconds of irradiation were necessary to collect the required statistics. These preliminary results indicate that a telescope of UFSDs could achieve in a few seconds the accuracy required for the clinical application and therefore encourage further investigations towards the improvement and the optimization of the present prototype.
Purpose: Dual-energy CT (DECT) has been used to derive relative stopping power (RSP) map by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-based mapping techniques, which would affect subsequent clinical applications. This work presents a noise-robust learning-based method to predict RSP maps from DECT for proton radiation therapy. Methods: The proposed method uses a residual attention cycle-consistent generative adversarial (CycleGAN) network. CycleGAN were used to let the DECT-to-RSP mapping be close to a one-to-one mapping by introducing an inverse RSP-to-DECT mapping. We retrospectively investigated 20 head-and-neck cancer patients with DECT scans in proton radiation therapy simulation. Ground truth RSP values were assigned by calculation based on chemical compositions, and acted as learning targets in the training process for DECT datasets, and were evaluated against results from the proposed method using a leave-one-out cross-validation strategy. Results: The predicted RSP maps showed an average normalized mean square error (NMSE) of 2.83% across the whole body volume, and average mean error (ME) less than 3% in all volumes of interest (VOIs). With additional simulated noise added in DECT datasets, the proposed method still maintained a comparable performance, while the physics-based stoichiometric method suffered degraded inaccuracy from increased noise level. The average differences in DVH metrics for clinical target volumes (CTVs) were less than 0.2 Gy for D95% and Dmax with no statistical significance. Conclusion: These results strongly indicate the high accuracy of RSP maps predicted by our machine-learning-based method and show its potential feasibility for proton treatment planning and dose calculation.
We study the propagation of nucleons and nuclei in tissue-like media within a Monte Carlo Model for Heavy-ion Therapy (MCHIT) based on the GEANT4 toolkit (version 8.2). The model takes into account fragmentation of projectile nuclei and secondary interactions of produced nuclear fragments. Model predictions are validated with available experimental data obtained for water and PMMA phantoms irradiated by monoenergetic carbon-ion beams. The MCHIT model describes well (1) the depth-dose distributions in water and PMMA, (2) the doses measured for fragments of certain charge, (3) the distributions of positron emitting nuclear fragments produced by carbon-ion beams, and (4) the energy spectra of secondary neutrons measured at different angles to the beam direction. Radial dose profiles for primary nuclei and for different projectile fragments are calculated and discussed as possible input for evaluation of biological dose distributions. It is shown that at the periphery of the transverse dose profile close to the Bragg peak the dose from secondary nuclear fragments is comparable to the dose from primary nuclei.
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