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The integration of real-time magnetic resonance imaging (MRI) guidance and proton therapy would potentially improve the proton dose steering capability by reducing daily uncertainties due to anatomical variations. The use of a fixed beamline coupled with an axial patient couch rotation would greatly simplify the proton delivery with MRI guidance. Nonetheless, it is mandatory to assure that the plan quality is not deteriorated by the anatomical deformations due to patient rotation. In this work, an in-house tool allowing for intra-fractional per-beam adaptation of intensity-modulated proton plans (BeamAdapt) was implemented through features available in RayStation. A set of three MRIs was acquired for two healthy volunteers ( V 1 , V 2 ): (1) no rotation/static, (2) rotation to the right and (3) left. V 1 was rotated by 15°, to simulate a clinical pediatric abdominal case and V 2 by 45°, to simulate an extreme patient rotation case. For each volunteer, a total of four intensity-modulated pencil beam scanning plans were optimized on the static MRI using virtual abdominal targets and two-three posterior-oblique beams. Beam angles were defined according to the angulations on the rotated MRIs. With BeamAdapt, each original plan was initially converted into separate plans with one beam per plan. In an iterative order, individual beam doses were non-rigidly deformed to the rotated anatomies and re-optimized accounting for the consequent deformations and the beam doses delivered so far. For evaluation, the final accumulated dose distribution was propagated back to the static MRI. Planned and adapted dose distributions were compared by computing relative differences between dose-volume histogram metrics. Absolute target dose differences were on average below 1% and organs-at-risk mean dose differences were below 3%. With BeamAdapt, not only intra-fractional per-beam proton plan adaptation coupled with axial patient rotation is possible but also the need for a rotating gantry during MRI guidance might be mitigated., (Creative Commons Attribution license.)

Objective: Dose prediction using deep learning networks prior to radiotherapy might lead tomore efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess their clinical usage for paediatric abdominal tumours., Material and Methods: Data from 80 patients with neuroblastoma or Wilms' tumour was included. Pencil beam scanning (PBS) (5 mm/ 3%) and volumetric-modulated arc therapy (VMAT) plans (5 mm) were robustly optimized on the internal target volume (ITV). Separate 3-dimensional patch-based U-net networks were trained to predict PBS and VMAT dose distributions. Doses, planning-computed tomography images and relevant optimization masks (ITV, vertebra and organs-at-risk) of 60 patients were used for training with a 5-fold cross validation. The networks' performance was evaluated by computing the relative error between planned and predicted dose-volume histogram (DVH) parameters for 20 inference patients. In addition, the organs-at-risk mean dose difference between modalities was calculated using planned and predicted dose distributions (ΔD mean  = D VMAT -D PBS ). Two radiation oncologists performed a blind PBS/VMAT modality selection based on either planned or predicted ΔD mean ., Results: Average DVH differences between planned and predicted dose distributions were ≤ |6%| for both modalities. The networks classified the organs-at-risk D mean difference as a gain (ΔD mean  > 0) with 98% precision. An identical modality selection based on planned compared to predicted ΔD mean was made for 18/20 patients., Conclusion: Deep learning networks for accurate prediction of proton and photon dose distributions for abdominal paediatric tumours were established. These networks allowing fast dose visualisation might aid in identifying the optimal radiotherapy technique when experience and/or resources are unavailable., Competing Interests: Declaration of Competing Interest The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: To assess the feasibility of magnetic resonance imaging (MRI)-only treatment planning for photon and proton radiotherapy in children with abdominal tumours., Materials and Methods: The study was conducted on 66 paediatric patients with Wilms' tumour or neuroblastoma (age 4 ± 2 years) who underwent MR and computed tomography (CT) acquisition on the same day as part of the clinical protocol. MRI intensities were converted to CT Hounsfield units (HU) by means of a UNet-like neural network trained to generate synthetic CT (sCT) from T1- and T2-weighted MR images. The CT-to-sCT image similarity was evaluated by computing the mean error (ME), mean absolute error (MAE), peak signal-to-noise ratio (PSNR) and Dice similarity coefficient (DSC). Synthetic CT dosimetric accuracy was verified against CT-based dose distributions for volumetric-modulated arc therapy (VMAT) and intensity-modulated pencil-beam scanning (PBS). Relative dose differences (D diff ) in the internal target volume and organs-at-risk were computed and a three-dimensional gamma analysis (2 mm, 2%) was performed., Results: The average ± standard deviation ME was -5 ± 12 HU, MAE was 57 ± 12 HU, PSNR was 30.3 ± 1.6 dB and DSC was 76 ± 8% for bones and 92 ± 9% for lungs. Average D diff were <0.5% for both VMAT (range [-2.5; 2.4]%) and PBS (range [-2.7; 3.7]%) dose distributions. The average gamma pass-rates were >99% (range [85; 100]%) for VMAT and >96% (range [87; 100]%) for PBS., Conclusion: The deep learning-based model generated accurate sCT from planning T1w- and T2w-MR images. Most dosimetric differences were within clinically acceptable criteria for photon and proton radiotherapy, demonstrating the feasibility of an MRI-only workflow for paediatric patients with abdominal tumours., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: M. van Stralen and P.R. Seevinck are minority shareholders at MRIguidance B.V., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Background and Purpose: To evaluate the dosimetric sparing and robustness against inter-fraction anatomical changes between photon and proton dose distributions for children with abdominal tumors., Material and Methods: Volumetric modulated arc therapy (VMAT) and intensity-modulated pencil beam scanning (PBS) proton dose distributions were calculated for 20 abdominal pediatric cases (average 3, range 1-8 years). VMAT plans were based on a full-arc while PBS plans on 2-3 posterior-oblique irradiation fields. Plans were robustly optimized on a patient-specific internal target volume (ITV) using a uniform 5 mm set-up uncertainty. Additionally, for the PBS plans a ± 3% proton range uncertainty was accounted for. Fractional dose re-calculations were performed using the planning computed tomography (CT) deformably registered to the daily cone-beam CT (CBCT) images. Fractional doses were accumulated rigidly. Planned and CBCT accumulated VMAT and PBS dose distributions were compared using dose-volume histogram (DVH) parameters., Results: Significant better sparing of the organs at risk with a maximum reduction in the mean dose of 40% was achieved with PBS. Mean ITV DVH parameters differences between planned and CBCT accumulated dose distributions were smaller than 0.5% for both VMAT and PBS. However, the ITV coverage (V 95%  > 99%) was not reached for one patient for the accumulated VMAT dose distribution., Conclusions: For pediatric patients with abdominal tumors, improved dosimetric sparing was obtained with PBS compared to VMAT. In addition, PBS delivered by posterior-oblique irradiation fields demonstrated to be robust against anatomical inter-fraction changes. Compared to PBS, daily anatomical changes proved to affect the target coverage of VMAT dose distributions to a higher extent., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Therapeutic proton and heavier ion beams generate prompt gamma photons that may escape from the patient. In principle, this allows for real-time, in situ monitoring of the treatment delivery, in particular, the hadron range within the patient, by imaging the emitted prompt gamma rays. Unfortunately, the neutrons simultaneously created with the prompt photons create a background that may obscure the prompt gamma signal. To enhance the accuracy of proton dose verification by prompt gamma imaging, we therefore propose a time-of-flight (TOF) technique to reject this neutron background, involving a shifting time window to account for the propagation of the protons through the patient. Time-resolved Monte Carlo simulations of the generation and transport of prompt gamma photons and neutrons upon irradiation of a PMMA phantom with 100, 150 and 200 MeV protons were performed using Geant4 (version 9.2.p02) and MCNPX (version 2.7.D). The influence of angular collimation and TOF selection on the prompt gamma and neutron longitudinal profiles is studied. Furthermore, the implications of the proton beam microstructure (characterized by the proton bunch width and repetition period) are investigated. The application of a shifting TOF window having a width of ΔTOF(z) = 1.0 ns appears to reduce the neutron background by more than 99%. Subsequent application of an energy threshold does not appear to sharpen the distal falloff of the prompt gamma profile but reduces the tail that is observed beyond the proton range. Investigations of the influence of the beam time structure show that TOF rejection of the neutron background is expected to be effective for typical therapeutic proton cyclotrons.

Positron emission tomography (PET) is a promising tool for monitoring the three-dimensional dose distribution in charged particle radiotherapy. PET imaging during or shortly after proton treatment is based on the detection of annihilation photons following the ß(+)-decay of radionuclides resulting from nuclear reactions in the irradiated tissue. Therapy monitoring is achieved by comparing the measured spatial distribution of irradiation-induced ß(+)-activity with the predicted distribution based on the treatment plan. The accuracy of the calculated distribution depends on the correctness of the computational models, implemented in the employed Monte Carlo (MC) codes that describe the interactions of the charged particle beam with matter and the production of radionuclides and secondary particles. However, no well-established theoretical models exist for predicting the nuclear interactions and so phenomenological models are typically used based on parameters derived from experimental data. Unfortunately, the experimental data presently available are insufficient to validate such phenomenological hadronic interaction models. Hence, a comparison among the models used by the different MC packages is desirable. In this work, starting from a common geometry, we compare the performances of MCNPX, GATE and PHITS MC codes in predicting the amount and spatial distribution of proton-induced activity, at therapeutic energies, to the already experimentally validated PET modelling based on the FLUKA MC code. In particular, we show how the amount of ß(+)-emitters produced in tissue-like media depends on the physics model and cross-sectional data used to describe the proton nuclear interactions, thus calling for future experimental campaigns aiming at supporting improvements of MC modelling for clinical application of PET monitoring., (© 2012 Institute of Physics and Engineering in Medicine)