Proton Dose Research Articles

Cognitive and Imaging Differences After Proton and Photon Whole Brain Irradiation in a Preclinical Model

Purpose:Compared with photon cranial radiation therapy (X-CRT), proton cranial radiation therapy (P-CRT) offers potential advantages in limiting radiation-induced sequalae in the treatment of pediatric brain tumors. This study aims to identify cognitive, functional magnetic resonance and positron emission tomography imaging markers and molecular differences between the radiation modalities.Methods and Materials:Juvenile rats received a single faction of 10 Gy (relative biological effectiveness−weighted dose) delivered with 6 MV X-CRT or at the midspread out Bragg peak of a 100 MeV P-CRT beam. At 3, 6, and 12 months post-CRT, executive function was measured using 5-choice serial reaction time task. At ~12 months post-CRT, animals were imaged with 18F-Flurodeoxy-glucose positron emission tomography imaging followed by functional ex vivo magnetic resonance imaging and stained for markers of neuroinflammation.Results:Irradiated animals had cognitive impairment with a higher number of omissions and lower incorrect and premature responses compared with sham (P ≤ .05). The accuracy of the animals’ X-CRT was less than that of sham (P ≤ .001). No significant difference in rates of cognitive change were found between the radiation modalities. At 12 months post-CRT, glucose metabolism was significantly higher than sham in X-CRT (P = .04) but not P-CRT. Using diffusion tensor imaging, P-CRT brains were found to have higher white matter volume and fiber lengths compared with sham (P < .03). Only X-CRT animals had higher apparent diffusion coefficient values compared with sham (P = .04). P-CRT animals had more connectomic changes compared with X-CRT. Correlative analysis identified several imaging features with cognitive performance. Further-more, microgliosis (P < .05), astrogliosis (P < .01), and myelin thinning (P <.05) were observed in both radiation modalities, with X-CRT showing slightly more inflammation.Conclusions:Both P-CRT and X-CRT lead to neurocognitive changes compared with sham. Although no significant difference was observed in neuroinflammation between the irradiated groups, differences were found in late-term glucose metabolism and brain connectome. Our results indicate that despite relative biological effectiveness weighting of the proton dose there are still differential effects which warrants further investigation.

Upgrade of gamma electron vertex imaging system for high-performance range verification in pencil beam scanning proton therapy

In proton therapy, a highly conformal proton dose can be delivered to the tumor by means of the steep distal dose penumbra at the end of the beam range. The proton beam range, however, is highly sensitive to range uncertainty, which makes accurately locating the proton range in the patient difficult. In-vivo range verification is a method to manage range uncertainty, one of the promising techniques being prompt gamma imaging (PGI). In earlier studies, we proposed gamma electron vertex imaging (GEVI), and constructed a proof-of-principle system. The system successfully demonstrated the GEVI imaging principle for therapeutic proton pencil beams without scanning, but showed some limitations under clinical conditions, particularly for pencil beam scanning proton therapy. In the present study, we upgraded the GEVI system in several aspects and tested the performance improvements such as for range-shift verification in the context of line scanning proton treatment. Specifically, the system showed better performance in obtaining accurate prompt gamma (PG) distributions in the clinical environment. Furthermore, high shift-detection sensitivity and accuracy were shown under various range-shift conditions using line scanning proton beams.

Intra-fractional per-beam adaptive workflow to mitigate the need for a rotating gantry during MRI-guided proton therapy

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.

Validation of proton dose calculation on scatter corrected 4D cone beam computed tomography using a porcine lung phantom

Proton therapy treatment for lungs remains challenging as images enabling the detection of inter- and intra-fractional motion, which could be used for proton dose adaptation, are not readily available. 4D computed tomography (4DCT) provides high image quality but is rarely available in-room, while in-room 4D cone beam computed tomography (4DCBCT) suffers from image quality limitations stemming mostly from scatter detection. This study investigated the feasibility of using virtual 4D computed tomography (4DvCT) as a prior for a phase-per-phase scatter correction algorithm yielding a 4D scatter corrected cone beam computed tomography image (4DCBCTcor), which can be used for proton dose calculation. 4DCT and 4DCBCT scans of a porcine lung phantom, which generated reproducible ventilation, were acquired with matching breathing patterns. Diffeomorphic Morphons, a deformable image registration algorithm, was used to register the mid-position 4DCT to the mid-position 4DCBCT and yield a 4DvCT. The 4DCBCT was reconstructed using motion-aware reconstruction based on spatial and temporal regularization (MA-ROOSTER). Successively for each phase, digitally reconstructed radiographs of the 4DvCT, simulated without scatter, were exploited to correct scatter in the corresponding CBCT projections. The 4DCBCTcor was then reconstructed with MA-ROOSTER using the corrected CBCT projections and the same settings and deformation vector fields as those already used for reconstructing the 4DCBCT. The 4DCBCTcor and the 4DvCT were evaluated phase-by-phase, performing proton dose calculations and comparison to those of a ground truth 4DCT by means of dose-volume-histograms (DVH) and gamma pass-rates (PR). For accumulated doses, DVH parameters deviated by at most 1.7% in the 4DvCT and 2.0% in the 4DCBCTcor case. The gamma PR for a (2%, 2 mm) criterion with 10% threshold were at least 93.2% (4DvCT) and 94.2% (4DCBCTcor), respectively. The 4DCBCTcor technique enabled accurate proton dose calculation, which indicates the potential for applicability to clinical 4DCBCT scans.

SP-0582 Online CBCT-based proton range and dose calculation

SP-0582 Online CBCT-based proton range and dose calculation

PH-0263 Pre-clinical vs. clinical 4D accumulated proton dose delivery for thoracic tumours with large motion

PH-0263 Pre-clinical vs. clinical 4D accumulated proton dose delivery for thoracic tumours with large motion

Range probing as a quality control tool for CBCT-based synthetic CTs: In vivo application for head and neck cancer patients.

PurposeCone‐beam CT (CBCT)‐based synthetic CTs (sCT) produced with a deep convolutional neural network (DCNN) show high image quality, suggesting their potential usability in adaptive proton therapy workflows. However, the nature of such workflows involving DCNNs prevents the user from having direct control over their output. Therefore, quality control (QC) tools that monitor the sCTs and detect failures or outliers in the generated images are needed.This work evaluates the potential of using a range‐probing (RP)‐based QC tool to verify sCTs generated by a DCNN. Such a RP QC tool experimentally assesses the CT number accuracy in sCTs.MethodsA RP QC dataset consisting of repeat CTs (rCT), CBCTs, and RP acquisitions of seven head and neck cancer patients was retrospectively assessed. CBCT‐based sCTs were generated using a DCNN. The CT number accuracy in the sCTs was evaluated by computing relative range errors between measured RP fields and RP field simulations based on rCT and sCT images.ResultsMean relative range errors showed agreement between measured and simulated RP fields, ranging from −1.2% to 1.5% in rCTs, and from −0.7% to 2.7% in sCTs.ConclusionsThe agreement between measured and simulated RP fields suggests the suitability of sCTs for proton dose calculations. This outcome brings sCTs generated by DCNNs closer toward clinical implementation within adaptive proton therapy treatment workflows. The proposed RP QC tool allows for CT number accuracy assessment in sCTs and can provide means of in vivo range verification.

Radiobiological impact of gadolinium neutron capture from proton therapy and alternative neutron sources using TOPAS-nBio.

A multi-scale investigation of the biological properties of gadolinium neutron capture (GdNC) therapy with applications in particle therapy is conducted using the TOPAS Monte Carlo (MC) simulation code. The simulation results are used to quantify the amount of gadolinium dose enhancement produced as a result of the secondary neutron production from proton therapy scaled by measured data. MC modeling was performed using the radiobiology extension TOol for PArticle Simulation TOPAS-nBio MC simulation code to study the radiobiological effects produced from GdNC on a segment of DNA, a spherical cellular model, and from the modeling of previous experimental measurements. The average RBE values were calculated from two methods, microdosimetric kinematic (MK) and biological weighting r(y) within a 2nm DNA segment for GdNC. The single-strand breaks (SSBs) and double-strand breaks (DSBs) were calculated from within the nucleus of a 20µm diameter, spherical cell model. From a previous experimental proton therapy measurement using a spread-out Bragg peak (SOBP) of 4.5-9.5cm and a delivered absorbed dose of 10.4Gy, the amount of Gd neutron captures was calculated and used to quantify the amount of GdNC absolute dose from particle therapy. The average RBE from microdosimetric kinematic and biological weighting was 1.35, and 1.70 for a 10% cell survival on HSG cell-line and weighting function data from early intestinal tolerance of mice. From a central isotropic GdNC source, the energy deposition is found to decrease from roughly 2.7eV per capture down to approximately 0.01eV per capture, a drop of two orders of magnitude within 50nm. This result suggests that Gd needs to be close to the DNA (within 10-20nm) in order for neutron capture to induce a significant dose enhancement due to the short-range electrons emitted after Gd neutron capture. Within a spherical cell model, the SSBs, and DSBs were determined to be 39 and 1.5 per neutron capture, respectively. From the total neutron captures produced from an experimental proton therapy measurement on a 3000 PPM Gd solution, an insignificant absolute Gd dose enhancement was quantified to be 5.4×10-6 Gy per Gy of administered proton dose. From this study and literature review, the production of secondary thermal neutrons from proton therapy is determined to be a limiting factor and unlikely to produce a clinically useful dose enhancement for secondary neutron capture therapy. Moreover, alternative neutron sources, such as, a compact deuterium-tritium (D-T) neutron generator, a "high yield" deuterium-deuterium (D-D) generator, or an industrial strength (100mg) 252 Cf source were investigated, with the 252 Cf source the most likely to be capable of producing enough neutrons for 1Gy of localized GdNC absolute dose within a reasonable treatment time.

Simulation of microtube irradiation on the beam tubes of GA Siwabessy reactor for in-vitro boron neutron capture therapy

The BNCT in-vitro test using a microtube irradiated in the neutron beam of the RSG-GAS beam tubes has been simulated using PHITS code. The simulation was performed by modeling a microtube containing boron solution which was placed 5 cm in front of the beam tubes. Inside the beam tube was installed a beam shaping assembly (BSA) using 80 cm of MgF 2 as a filter to reduce fast neutron and gamma fluences. Microtube containing 1.5 mL of boron solution with boron enriched 10B of 90%. The microtube dose i.e alpha dose, 7Li dose, proton dose, and gamma dose were calculated for boron concentration of 1 ppm. The simulation of microtube containing 1 ppm boron solution shown that irradiated in the BSA-S5 neutron beam can produce 20 Gy dose in the shortest irradiation time of 2.5 hours.

Impact of proton dose calculation algorithms on the interplay effect in PBS proton based SBRT lung plans

Purpose. The purpose of the current study was to investigate the impact of RayStation analytical pencil beam (APB) and Monte Carlo (MC) algorithms on the interplay effect in pencil beam scanning (PBS) proton-based stereotactic body radiation therapy (SBRT) lung plans. Methods. The current in-silico planning study was designed for a total dose of 5000 cGy(RBE) with a fractional dose of 1000 cGy(RBE). First, three sets of nominal plans were generated for each patient: (a) APB optimization followed by APB dose calculation (PB‐PB), (b) APB optimization followed by MC dose calculation (PB‐MC), and (c) MC optimization followed by MC dose calculation (MC‐MC). Second, for each patient, two sets of volumetric repainting plans (five repaintings) – PB-MCVR5 and MC-MCVR5 were generated based on PB-MC and MC-MC, respectively. Dosimetric differences between APB and MC algorithms were calculated on the nominal and interplay dose-volume-histograms (DVHs). Results. Interplay evaluation in non-volumetric repainting plans showed that APB algorithm overestimated the target coverage by up to 8.4% for D95% and 10.5% for D99%, whereas in volumetric repainting plans, APB algorithm overestimated by up to 5.3% for D95% and 7.0% for D99%. Interplay results for MC calculations showed a decrease in D95% and D99% by average differences of 3.5% and 4.7%, respectively, in MC‐MC plans and by 1.8% and 3.0% in MC-MCVR5 plans. Conclusion. In PBS proton-based SBRT lung plans, the combination of APB algorithm and interplay effect reduced the target coverage. This may result in inferior local control. The use of MC algorithm for both optimization and final dose calculations in conjunction with the volumetric repainting technique yielded superior target coverage.

Training a deep neural network coping with diversities in abdominal and pelvic images of children and young adults for CBCT-based adaptive proton therapy

PurposeTo train a deep neural network for correcting abdominal and pelvic cone-beam computed tomography (CBCT) of children and young adults in the presence of diverse patient size, anatomic extent, and scan parameters. Materials and MethodsPretreatment CBCT and planning/repeat CT image pairs from 64 children and young adults treated with proton therapy (aged 1–23 years) were analyzed. To evaluate the impact of anatomic extent in CBCT and data size in the training data, we compared the performance of three cycle-consistent generative adversarial network models that were separately trained by three datasets comprising abdominal (n = 21), pelvic (n = 29), and combined abdominal-pelvic image pairs (n = 50), respectively. The maximum body width of each patient was normalized to a fixed width before training and model application to reduce the impact of variations in body size. The corrected CBCT images by the three models were comparatively evaluated against the repeat CT closest in time to the CBCT (median gap, 0 days; range, 0–6 days) in HU accuracy, estimated dose distribution, and proton range. ResultsThe network model trained by the combined dataset significantly outperformed the abdomen and pelvis models in mean absolute HU error of the corrected CBCT from 14 testing patients (47 ± 7 HU versus 51 ± 8 HU; paired Wilcoxon signed-rank test, P < 0.01). The larger error (60 ± 7 HU) without the body-size normalization confirmed the efficacy of the preprocessing. The model trained with the combined dataset resulted in gamma passing rates of 98.5 ± 1.9% (2%/2 mm criterion) and the range (80% distal fall-off) differences from the reference within ±3 mm for 91.2 ± 11.5% beamlets. ConclusionCombining data from adjacent anatomic sites and normalizing age-dependent body sizes in children and young adults were beneficial in training a neural network to accurately estimate proton dose from CBCT despite limited training data size and anatomic diversities.

Artificial intelligence supported single detector multi-energy proton radiography system

Proton radiography imaging was proposed as a promising technique to evaluate internal anatomical changes, to enable pre-treatment patient alignment, and most importantly, to optimize the patient specific CT number to stopping-power ratio conversion. The clinical implementation rate of proton radiography systems is still limited due to their complex bulky design, together with the persistent problem of (in)elastic nuclear interactions and multiple Coulomb scattering (i.e. range mixing). In this work, a compact multi-energy proton radiography system was proposed in combination with an artificial intelligence network architecture (ProtonDSE) to remove the persistent problem of proton scatter in proton radiography. A realistic Monte Carlo model of the Proteus®One accelerator was built at 200 and 220 MeV to isolate the scattered proton signal in 236 proton radiographies of 80 digital anthropomorphic phantoms. ProtonDSE was trained to predict the proton scatter distribution at two beam energies in a 60%/25%/15% scheme for training, testing, and validation. A calibration procedure was proposed to derive the water equivalent thickness image based on the detector dose response relationship at both beam energies. ProtonDSE network performance was evaluated with quantitative metrics that showed an overall mean absolute percentage error below 1.4% ± 0.4% in our test dataset. For one example patient, detector dose to WET conversions were performed based on the total dose (), the primary proton dose (), and the ProtonDSE corrected detector dose (). The determined WET accuracy was compared with respect to the reference WET by idealistic raytracing in a manually delineated region-of-interest inside the brain. The error was determined 4.3% ± 4.1% for 2.2% ± 1.4% for and 2.5% ± 2.0% for

A Comprehensive Survey of Proton Beam Therapy Research and Development in Iran

Purpose: Proton Beam Therapy (PBT) is an emerging radiotherapy technique using beams of proton to treat cancer. As the first report addressing the topic, the principal aim is to highlight the present status of PBT research and development in Iran as a developing country. Materials and Methods: To do so, the demand for PBT in Iran and Iran National Ion Therapy Center (IRNitc) was investigated and introduced. Then, Scopus and PubMed were searched for studies that dealt with PBT research in Iran and subsequently 6 major subfields of interest were identified. Furthermore, international collaborations were extracted from the bibliographic data. To combine both research and development sides, a SWOT analysis was performed through collecting viewpoints of 48 radiotherapy experts about PBT, and then strengths, weaknesses, opportunities, and threats of it were examined. Results: Iran contributes to approximately 1% of global PBT sciences. Proton dose calculation using Monte Carlo simulation is the dominant subject of interest for Iranian researchers. Italy is recognized as the major foreign partner in PBT researches. Clinical advantages over conventional radiotherapy modalities are the main strength of PBT development in Iran while the high installation cost remains the most weakness. Finally, 10 general considerations for the launching of a PBT facility in Iran were presented based upon both Iranian experts’ viewpoints and IAEA recommendations. Conclusion: This research reveals that while PBT research and development in Iran are still in their infancy, there are promising trends in both the research and development sides of PBT.

Long short‐term memory networks for proton dose calculation in highly heterogeneous tissues

To investigate the feasibility and accuracy of proton dose calculations with artificial neural networks (ANNs) in challenging three-dimensional (3D) anatomies. A novel proton dose calculation approach was designed based on the application of a long short-term memory (LSTM) network. It processes the 3D geometry as a sequence of two-dimensional (2D) computed tomography slices and outputs a corresponding sequence of 2D slices that forms the 3D dose distribution. The general accuracy of the approach is investigated in comparison to Monte Carlo reference simulations and pencil beam dose calculations. We consider both artificial phantom geometries and clinically realistic lung cases for three different pencil beam energies. For artificial phantom cases, the trained LSTM model achieved a 98.57% γ-index pass rate ([1%, 3mm]) in comparison to MC simulations for a pencil beam with initial energy 104.25MeV. For a lung patient case, we observe pass rates of 98.56%, 97.74%, and 94.51% for an initial energy of 67.85, 104.25, and 134.68MeV, respectively. Applying the LSTM dose calculation on patient cases that were fully excluded from the training process yields an average γ-index pass rate of 97.85%. LSTM networks are well suited for proton dose calculation tasks. Further research, especially regarding model generalization and computational performance in comparison to established dose calculation methods, is warranted.

Fluence-modulated proton CT optimized with patient-specific dose and variance objectives for proton dose calculation

Particle therapy treatment planning requires accurate volumetric maps of the relative stopping power, which can directly be acquired using proton computed tomography (pCT). With fluence-modulated pCT (FMpCT) imaging fluence is concentrated in a region-of-interest (ROI), which can be the vicinity of the treatment beam path, and imaging dose is reduced elsewhere. In this work we present a novel optimization algorithm for FMpCT which, for the first time, calculates modulated imaging fluences for joint imaging dose and image variance objectives. Thereby, image quality is maintained in the ROI to ensure accurate calculations of the treatment dose, and imaging dose is minimized outside the ROI with stronger minimization penalties given to imaging organs-at-risk. The optimization requires an initial scan at uniform fluence or a previous x-ray CT scan. We simulated and optimized FMpCT images for three pediatric patients with tumors in the head region. We verified that the target image variance inside the ROI was achieved and demonstrated imaging dose reductions outside of the ROI of 74% on average, reducing the imaging dose from 1.2 to 0.3 mGy. Such dose savings are expected to be relevant compared to the therapeutic dose outside of the treatment field. Treatment doses were re-calculated on the FMpCT images and compared to treatment doses re-recalculated on uniform fluence pCT scans using a 1% criterion. Passing rates were above 98.3% for all patients. Passing rates comparing FMpCT treatment doses to the ground truth treatment dose were above 88.5% for all patients. Evaluation of the proton range with a 1 mm criterion resulted in passing rates above 97.5% (FMpCT/pCT) and 95.3% (FMpCT/ground truth). Jointly optimized fluence-modulated pCT images can be used for proton dose calculation maintaining the full dosimetric accuracy of pCT but reducing the required imaging dose considerably by three quarters. This may allow for daily imaging during particle therapy ensuring a safe and accurate delivery of the therapeutic dose and avoiding excess dose from imaging.

Dead time corrections for Bonner sphere measurements of secondary neutrons at a proton therapy facility

Radiation therapy with proton beams allows the deposition of high doses to the tumour while minimising dose to the surrounding tissue. During such treatment, the patient is also exposed to secondary radiation which produces an out-of-field dose that affects healthy tissue. The largest contribution to this out-of-field dose comes from neutron radiation; therefore, it is of interest to fully characterise the neutron field in the therapy room with measurements. This is usually done with Bonner sphere spectrometers using active detectors, typically 3He-filled proportional counters, as central thermal neutron sensors. Under the experimental conditions encountered in proton therapy facilities, a proper analysis of the measurements is impossible unless dead time corrections are implemented. In this paper, we present a method using a paralysable dead time model for carrying out such corrections for Bonner sphere measurements with 3He-filled proportional counters and apply it to data taken at the University Proton Therapy Dresden (UPTD) facility in double scattering mode. The neutron events were recorded with time stamps and, based on this time-resolved data, the measured neutron rate distribution was sampled. Since the neutron flux is proportional to the proton flux, the integral neutron flux is directly related to the proton dose. Hence, we were able to estimate the detector dead time from the measured rate distributions recorded for a set of measurements with different proton dose rates. Experimental measurements with different intensities of the proton field show that the corrections are in agreement within 0.5% for measured signal rates smaller than 15 × 103 counts per second and do not exceed 1% at 25 × 103 counts per second.

Improving proton dose calculation accuracy by using deep learning

Pencil beam (PB) dose calculation is fast but inaccurate due to the approximations when dealing with inhomogeneities. Monte Carlo (MC) dose calculation is the most accurate method but it is time consuming. The aim of this study was to develop a deep learning model that can boost the accuracy of PB dose calculation to the level of MC dose by converting PB dose to MC dose for different tumor sites. The proposed model uses the PB dose and computed tomography image as inputs to generate the MC dose. We used 290 patients (90 head and neck, 93 liver, 75 prostate and 32 lung) to train, validate, and test the model. For each tumor site, we performed four numerical experiments to explore various combinations of training datasets. Training the model on data from all tumor sites together and using the dose distribution of each individual beam as input yielded the best performance for all four tumor sites. The average gamma passing rate (1 mm/1%) between the converted and the MC dose was 92.8%, 92.7%, 89.7% and 99.6% for head and neck, liver, lung, and prostate test patients, respectively. The average dose conversion time for a single field was less than 4 s. The trained model can be adapted to new datasets through transfer learning. Our deep learning-based approach can quickly boost the accuracy of PB dose to that of MC dose. The developed model can be added to the clinical workflow of proton treatment planning to improve dose calculation accuracy.

CBCT-Based Adaptive Assessment Workflow for Intensity Modulated Proton Therapy for Head and Neck Cancer.

PurposeAnatomical changes and patient setup uncertainties during intensity modulated proton therapy (IMPT) of head and neck (HN) cancers demand frequent evaluation of delivered dose. This work investigated a cone-beam computed tomography (CBCT) and deformable image registration based therapy workflow to demonstrate the feasibility of proton dose calculation on synthetic computed tomography (sCT) for adaptive IMPT treatment of HN cancer.Materials and MethodsTwenty-one patients with HN cancer were enrolled in this study, a retrospective institutional review board protocol. They had previously been treated with volumetric modulated arc therapy and had daily iterative CBCT. For each patient, robust optimization (RO) IMPT plans were generated using ±3 mm patient setup and ±3% proton range uncertainties. The sCTs were created and the weekly delivered dose was recalculated using an adaptive dose accumulation workflow in which the planning computed tomography (CT) was deformably registered to CBCTs and Hounsfield units transferred from the planning CT. Accumulated doses from ±3 mm/±3% RO-IMPT plans were evaluated using clinical dose-volume constraints for targets (clinical target volume, or CTV) and organs at risk.ResultsEvaluation of weekly recalculated dose on sCTs showed that most of the patient plans maintained target dose coverage. The primary CTV remained covered by the V95 > 95% (95% of the volume receiving more than 95% of the prescription dose) worst-case scenario for 84.5% of the weekly fractions. The oral cavity accumulated mean dose remained lower than the worst-case scenario for all patients. Parotid accumulated mean dose remained within the uncertainty bands for 18 of the 21 patients, and all were kept lower than RO-IMPT worst-case scenario for 88.7% and 84.5% for left and right parotids, respectively.ConclusionThis study demonstrated that RO-IMPT plans account for most setup and anatomical uncertainties, except for large weight-loss changes that need to be tracked throughout the treatment course. We showed that sCTs could be a powerful decision tool for adaptation of these cases in order to reduce workload when using repeat CTs.

Dual-storage phosphor proton therapy dosimetry: Simultaneous quantification of dose and linear energy transfer.

To investigate the feasibility of using the high Zeff storage phosphor material BaFBrI:Eu2+ in conjunction with the low Zeff storage phosphor material KCl:Eu2+ for simultaneous proton dose and linear energy transfer (LET) measurements by (a) measuring the fundamental optical and dosimetric properties of BaFBrI:Eu2+ , (b) evaluating its compatibility in being readout simultaneously with KCl:Eu2+ dosimeters, and (c) modeling and validating its LET dependence under elevated proton LET irradiation. A commercial BaFBrI:Eu2+ storage phosphor detector (Model ST-VI, Fujifilm) was characterized with energy dispersive x-ray spectroscopy (EDS) analysis to obtain its elemental composition. The dosimeters were irradiated using both a Mevion S250 proton therapy unit (at the center of a spread-out Bragg peak, SOBP) and a Varian Clinac iX linear accelerator with the latter being a low LET irradiation. The photostimulated luminescence (PSL) emission spectra, excitation spectra, and luminescent lifetimes of the detector were measured after proton and photon irradiations. Dosimetric properties including dose linearity, dose rate dependence, radiation hardness, temporal, and readout stabilities were studied using a laboratory optical reader after proton irradiations. In addition, its proton energy dependence was analytically modeled and experimentally validated by irradiating the detectors at various depths within the SOBP (Range: 15.0g/cm2 , Modulation: 10.0g/cm2 ). The active detector composition for the high Zeff storage phosphor detector was found to be BaFBr0.85 I0.15 :Eu2+ . The BaFBr0.85 I0.15 :Eu2+ material's excitation and emission spectra were in agreement under proton and photon irradiations, with peaks of 586±1nm and 400±1nm, respectively, with a full width at half maximum (FWHM) of 119±3nm and 30±2nm, respectively. As dosimeter response under photon irradiation is generally believed to be free from LET effect, these results suggest LET independence of charge storage center types resulted from ionizing radiations. There is sufficient spectral overlaps with KCl:Eu2+ dosimeters allowing both dosimeters to be readout under equivalent readout conditions, that is, 594nm stimulation and 420nm detection wavelengths. Its PSL characteristic lifetime was found to be less than 5 microseconds which would make it suitable for fast 2D readout post irradiation. Its 420nm emission band intensity was found to be linear up to 10Gy absolute proton dose under the same irradiation conditions, dose rate independent, stable in time and under multiple readouts, and with high radiation hardness under cumulative proton dose histories up to 200Gy as tested in this study. BaFBr0.85 I0.15 :Eu2+ showed significant proton energy-dependent dose under-response in regions of high LET which could be modeled by stopping power ratio calculations with an accuracy of 3% in low LET regions and a distance-to-agreement (DTA) of 1mm in high LET regions (>5keV/μm). We have proven the feasibility of dual-storage phosphor proton dosimetry for simultaneous proton dose and LET measurements. BaFBr0.85 I0.15 :Eu2+ has shown equally excellent dosimetry performance as its low Zeff complement KCl:Eu2+ with distinctive LET dependence merely as a result of its higher Zeff . These promising results pave the way for future studies involving simultaneous proton dose and LET measurements using this novel approach.

Double-strand breaks measured along a 160 MeV proton Bragg curve using a novel FIESTA-DNA probe in a cell-free environment

Proton radiotherapy treatment planning systems use a constant relative biological effectiveness (RBE) = 1.1 to convert proton absorbed dose into biologically equivalent high-energy photon dose. This method ignores linear energy transfer (LET) distributions, and RBE is known to change as a function of LET. Variable RBE approaches have been proposed for proton planning optimization. Experimental validation of models underlying these approaches is a pre-requisite for their clinical implementation. This validation has to probe every level in the evolution of radiation-induced biological damage leading to cell death, starting from DNA double-strand breaks (DSB). Using a novel FIESTA-DNA probe, we measured the probability of double-strand break (P DSB) along a 160 MeV proton Bragg curve at two dose levels (30 and 60 Gy (RBE)) and compared it to measurements in a 6 MV photon beam. A machined setup that held an Advanced Markus parallel plate chamber for proton dose verification alongside the probes was fabricated. Each sample set consisted of five 10 μl probes suspended inside plastic microcapillary tubes. These were irradiated with protons to 30 Gy (RBE) at depths of 5–17.5 cm and 60 Gy (RBE) at depths of 10–17.2 cm with 1 mm resolution around Bragg peak. Sample sets were also irradiated using 6MV photons to 20, 40, 60, and 80 Gy. For the 30 Gy (RBE) measurements, increases in P DSB/Gy were observed at 17.0 cm followed by decreases at larger depth. For the 60 Gy (RBE) measurements, no increase in P DSB/Gy was observed, but there was a decrease after 17.0 cm. Dose-response for P DSB between 30 and 60 Gy (RBE) showed less than doubling of P DSB when dose was doubled. Proton RBE effect from DSB, RBEP,DSB, was <1 except at the Bragg peak. The experiment showed that the novel probe can be used to perform DNA DSB measurements in a proton beam. To establish relevance to clinical environment, further investigation of the probe’s chemical scavenging needs to be performed.