Proton Dose Distributions Research Articles

Evaluation of proton and photon dose distributions recalculated on 2D and 3D Unet-generated pseudoCTs from T1-weighted MR head scans

Introduction: The recent developments of magnetic resonance (MR) based adaptive strategies for photon and, potentially for proton therapy, require a fast and reliable conversion of MR images to X-ray computed tomography (CT) values. CT values are needed for photon and proton dose calculation. The improvement of conversion results employing a 3D deep learning approach is evaluated.Material and methods: A database of 89 T1-weighted MR head scans with about 100 slices each, including rigidly registered CTs, was created. Twenty-eight validation patients were randomly sampled, and four patients were selected for application. The remaining patients were used to train a 2D and a 3D U-shaped convolutional neural network (Unet). A stack size of 32 slices was used for 3D training. For all application cases, volumetric modulated arc therapy photon and single-field uniform dose pencil-beam scanning proton plans at four different gantry angles were optimized for a generic target on the CT and recalculated on 2D and 3D Unet-based pseudoCTs. Mean (absolute) error (MAE/ME) and a gradient sharpness estimate were used to quantify the image quality. Three-dimensional gamma and dose difference analyses were performed for photon (gamma criteria: 1%, 1 mm) and proton dose distributions (gamma criteria: 2%, 2 mm). Range (80% fall off) differences for beam’s eye view profiles were evaluated for protons.Results: Training 36 h for 1000 epochs in 3D (6 h for 200 epochs in 2D) yielded a maximum MAE of 147 HU (135 HU) for the application patients. Except for one patient gamma pass rates for photon and proton dose distributions were above 96% for both Unets. Slice discontinuities were reduced for 3D training at the cost of sharpness.Conclusions: Image analysis revealed a slight advantage of 2D Unets compared to 3D Unets. Similar dose calculation performance was reached for the 2D and 3D network.

A theoretical investigation of adequate range uncertainty margins in proton treatment planning to preserve tumor control probability

Background: Proton dose distributions are sensitive to range uncertainties, resulting in margins added to ensure adequate tumor control probability (TCP). We investigated the required margin and dose shape needed to ensure adequate TCP, for representative tumor cell distributions in the clinical target volume (CTV).Material and methods: A mechanistic tumor response model, validated for lung tumors, was used to estimate TCP. The tumor cell distribution () was assumed to decrease exponentially in the CTV with decay parameter toward the outer border (). It was investigated if a gradual dose fall-off could reduce the dose to normal tissues outside the CTV, while achieving adequate TCP. For various values of and we derived adequate uniform dose margins (), coupled to linear dose fall-off regions ( cm), that ensured while delivering the least mean dose outside the CTV. To account for variabilities in patients and tumor types, variable probabilities () of finding tumor cells in the non-GTV part of the CTV for a given patient were also tested. Dose from a single beam or two opposing beams was simulated under the influence of a typical stopping power ratio uncertainty of 3.5%.Results: For large and a dose distribution with a shallower dose fall-off () was advantageous, and could be smaller than In the case of small values, however, a conventional dose distribution () would generally perform better. For no CTV, cm in the case of two opposing beams, while it was 0.7 cm for a single beam, however, for two opposing beams cm ( cm), while it was zero for a single beam.Conclusion: The details of the underlying cancer cell distribution characteristics do impact the adequate dose arrangements, and for opposing beams a non-conventional dose distribution shape is often advantageous.

OC-0567 Reconstructing the 3-D proton dose distribution from the modelled iono-acoustic wave field

OC-0567 Reconstructing the 3-D proton dose distribution from the modelled iono-acoustic wave field

Robust optimization for intensity-modulated proton therapy with soft spot sensitivity regularization.

Proton dose distribution is sensitive to uncertainties in range estimation and patient positioning. Currently, the proton robustness is managed by worst-case scenario optimization methods, which are computationally inefficient. To overcome these challenges, we develop a novel intensity-modulated proton therapy (IMPT) optimization method that integrates dose fidelity with a sensitivity term that describes dose perturbation as the result of range and positioning uncertainties. In the integrated optimization framework, the optimization cost function is formulated to include two terms: a dose fidelity term and a robustness term penalizing the inner product of the scanning spot sensitivity and intensity. The sensitivity of an IMPT scanning spot to perturbations is defined as the dose distribution variation induced by range and positioning errors. To evaluate the sensitivity, the spatial gradient of the dose distribution of a specific spot is first calculated. The spot sensitivity is then determined by the total absolute value of the directional gradients of all affected voxels. The fast iterative shrinkage-thresholding algorithm is used to solve the optimization problem. This method was tested on three skull base tumor (SBT) patients and three bilateral head-and-neck (H&N) patients. The proposed sensitivity-regularized method (SenR) was implemented on both clinic target volume (CTV) and planning target volume (PTV). They were compared with conventional PTV-based optimization method (Conv) and CTV-based voxel-wise worst-case scenario optimization approach (WC). Under the nominal condition without uncertainties, the three methods achieved similar CTV dose coverage, while the CTV-based SenR approach better spared organs at risks (OARs) compared with the WC approach, with an average reduction of [Dmean, Dmax] of [4.72, 3.38] GyRBE for the SBT cases and [2.54, 3.33]GyRBE for the H&N cases. The OAR sparing of the PTV-based SenR method was comparable with the WC method. The WC method, and SenR approaches all improved the plan robustness from the conventional PTV-based method. On average, under range uncertainties, the lowest [D95%, V95%, V100%] of CTV were increased from [93.75%, 88.47%, 47.37%] in the Conv method, to [99.28%, 99.51%, 86.64%] in the WC method, [97.71%, 97.85%, 81.65%] in the SenR-CTV method and [98.77%, 99.30%, 85.12%] in the SenR-PTV method, respectively. Under setup uncertainties, the average lowest [D95%, V95%, V100%] of CTV were increased from [95.35%, 94.92%, 65.12%] in the Conv method, to [99.43%, 99.63%, 87.12%] in the WC method, [96.97%, 97.13%, 77.86%] in the SenR-CTV method, and [98.21%, 98.34%, 83.88%] in the SenR-PTV method, respectively. The runtime of the SenR optimization is eight times shorter than that of the voxel-wise worst-case method. We developed a novel computationally efficient robust optimization method for IMPT. The robustness is calculated as the spot sensitivity to both range and shift perturbations. The dose fidelity term is then regularized by the sensitivity term for the flexibility and trade-off between the dosimetry and the robustness. In the stress test, SenR is more resilient to unexpected uncertainties. These advantages in combination with its fast computation time make it a viable candidate for clinical IMPT planning.

Dose distribution of protons and flux of secondary particles in breast proton therapy.

Introduction: Proton therapy is newer therapeutic method for early stage breast cancer. Proton beams release most of their energy in the Bragg peak and then will be a rapid decline in their end. When protons interact with matter, produce secondary particles like neutrons and gammas, and these unwanted radiation has no beneficial effect and also is believed to increase the risk of secondary cancers, so it’s necessary to assess these secondary particles. Monte Carlo algorithm is the most accurate calculation method in the dosimetry. MCNPX is a modern, general purpose Monte Carlo code that were used to model the transport and interactions of particles in patient’s body, also is currently the most commonly used MC codes for proton therapy. In this study, calculated flux of secondary particles like neutron and photon in vital organs and dose distribution of Proton in energy range of 40 to 70 with 10 single step. Materials and Methods: Analytical phantom of the human body, ORNL used to create the input files and Protons as pencil beam modeled in front of left breast with energy of 40 to 70 MeV for covering the left breast, eventually Counting sensors for tracking the trajectory of secondary particles and provide the necessary data were used. Results: the dose distribution of protons shows they can have covered the exact shape of tumor with high accuracy and release most of their energy on it, so it’s best feature of proton therapy also flux of secondary particles shows the most important organs are Heart-left ventricle and left lung in left breast proton therapy because of the most flux of secondary particles reach to them. Conclusion: flux of secondary particles in vital organs shows that even though proton therapy is a good option Due to the favorable Bragg peak radiation and delivers high dose to a small volume of cancerous tissue while the healthy structures will be spared during proton radiation therapy and flux of secondary particles are low but they are not low enough to be negligible.

Proton-induced displacement damage in ZnO thin film transistors: Impact of damage location

We have investigated the displacement damage (DD) effect on the electrical characteristics of ZnO thin film transistors (TFTs) based on its location of origin in the device structure. The area subjected to the maximum proton dose induces a maximum DD effect in that particular location. ZnO TFTs with two different passivation layer thicknesses were prepared to obtain maximum proton dose distribution in either the ZnO channel layer or ZnO/SiO2 interface. The devices were irradiated by a proton beam with an energy 200 keV and 1 × 1014 protons/cm2 fluence. Transport of Ions in Matter (TRIM) simulation, followed by calculation of depth distribution of the nonionizing energy loss (NIEL), illustrated different proton dose distribution profiles and NIEL profiles along the depth of the device for these two types of samples. The sample with the maximum proton dose peaks at the ZnO/SiO2 interface exhibited a significant degradation in device electrical characteristics as compared to the negligible degradation of the sample when the maximum proton dose was absorbed in the ZnO layer. Therefore, the investigation into the radiation hardness of proton-irradiated ZnO TFTs is non-trivial since the displacement damage induces drastic changes on the device characteristics based on the damage location.

Investigation on Patient/Compensator Scatter Factor for Monitor Unit Calculation in Proton Therapy.

Purpose:It is the goal of this study to use both Monte Carlo (MC) simulation and the pencil beam dose algorithm (PBA) in the treatment planning system to investigate Patient scatter factor (PSF) and Compensator scatter factor (CSF) for calibrating the dose per monitor unit (DMU) for a passive scattering proton therapy system.Materials and Methods: PSFs and CSFs for brain, lung, pancreas, and prostate treatment sites were calculated by using MC simulation and PBA from the treatment planning software to evaluate the agreement between the two.Results:This study shows that the CSF values are always greater than 1, with some reaching nearly 4% above unity, and depending strongly on the shape of the compensator. Monte Carlo and PBA-calculated CSF factors agree very well, with average differences below 1%. PSF values calculated in this study ranged from 0.919 to 1.023 and are largely dependent on the type of tissue heterogeneities in the treatment field. Monte Carlo and PBA-calculated PSF factors show differences, with the largest discrepancies seen in lung cases, with an average difference of 1.9%. It is also shown that dense bone will drive a PSF to values greater than unity, while large quantities of air decrease the PSF to below unity.Conclusion:We have showed that the compensator and patient anatomy can have a significant impact on clinical proton dose distribution. It is recommended that both Monte Carlo and treatment planning system should be used to take these factors into account in the final DMU calculation.

Power-law relationship in the long-tailed sections of proton dose distributions

The halo portion of a proton therapy dose creates a long tail in proton dose distributions, but so far study of this phenomenon has been limited. We used statistical methods and mathematical models to confirm that the long-tailed portion of proton dose distributions exhibits a power-law relationship. By analyzing 299 measured dose profiles, we found that all proton lateral dose distributions had a significant power-law scaling correlation with a high correlation coefficient in the tail. We set up a dual-mechanism model, containing both direct and indirect impact mechanisms. In the direct impact mechanism, the proximal dose deposition is mainly due to the direct impact of a proton on a particle. In the indirect mechanism, the impact of a proton on a given particle is considered in terms of the proton’s impact on a neighboring particle that then impacts the given particle. We found that the indirect impact mechanism led to a tail in the distribution exhibiting a power-law relationship because the probability of the indirect impacts was proportional to the distance; i.e., the longer the distance, the larger the indirect impact probability. Upon analyzing the experimental data, we observed that the power-law exponent increased with proton energy.

Study on the Dose Uncertainties in the Lung during Passive Proton Irradiation with a Proton Beam Range Compensator

A moving phantom is manufactured for mimicking lung model to study the dose uncertainty from CT number-stopping power conversion and dose calculation in the soft tissue, light lung tissue and bone regions during passive proton irradiation with compensator smearing value. The phantom is scanned with a CT system, and a proton beam irradiation plan is carried out with the use of a treatment planning system (Eclipse). In the case of the moving phantom, a RPM system is used for respiratory gating. The uncertainties in the dose distribution between the measured data and the planned data are investigated by a gamma analysis with 3%-3 mm acceptance criteria. To investigate smearing effect, three smearing values (0.3 cm, 0.7 cm, 1.2 cm) are used to for fixed and moving phantom system. For both fixed and moving phantom, uncertainties in the light lung tissue are severe than those in soft tissue region in which the dose uncertainties are within clinically tolerable ranges. As the smearing value increases, the uncertainty in the proton dose distribution decreases.

Derivation of mean dose tolerances for new fractionation schemes and treatment modalities

Avoiding toxicities in radiotherapy requires the knowledge of tolerable organ doses. For new, experimental fractionation schemes (e.g. hypofractionation) these are typically derived from traditional schedules using the biologically effective dose (BED) model. In this report we investigate the difficulties of establishing mean dose tolerances that arise since the mean BED depends on the entire spatial dose distribution, rather than on the dose level alone.A formula has been derived to establish mean physical dose constraints such that they are mean BED equivalent to a reference treatment scheme. This formula constitutes a modified BED equation where the influence of the spatial dose distribution is summarized in a single parameter, the dose shape factor. To quantify effects we analyzed 24 liver cancer patients for whom both proton and photon IMRT treatment plans were available.The results show that the standard BED equation—neglecting the spatial dose distribution—can overestimate mean dose tolerances for hypofractionated treatments by up to 20%. The shape difference between photon and proton dose distributions can cause 30–40% differences in mean physical dose for plans having identical mean BEDs. Converting hypofractionated, 5/15-fraction proton doses to mean BED equivalent photon doses in traditional 35-fraction regimens resulted in up to 10 Gy higher doses than applying the standard BED formula.The dose shape effect should be accounted for to avoid overestimation of mean dose tolerances, particularly when estimating constraints for hypofractionated regimens. Additionally, tolerances established for one treatment modality cannot necessarily be applied to other modalities with drastically different dose distributions, such as proton therapy. Last, protons may only allow marginal (5–10%) dose escalation if a fraction-size adjusted organ mean dose is constraining instead of a physical dose.

Estimation and correction of produced light from prompt gamma photons on luminescence imaging of water for proton therapy dosimetry

Although the luminescence images of water during proton-beam irradiation using a cooled charge-coupled device camera showed almost the same ranges of proton beams as those measured by an ionization chamber, the depth profiles showed lower Bragg peak intensities than those measured by an ionization chamber. In addition, a broad optical baseline signal was observed in depths that exceed the depth of the Bragg peak. We hypothesize that this broad baseline signal originates from the interaction of proton-induced prompt gamma photons with water. These prompt gamma photons interact with water to form high-energy Compton electrons, which may cause luminescence or Cherenkov emission from depths exceeding the location of the Bragg peak. To clarify this idea, we measured the luminescence images of water during the irradiations of protons in water with minimized parallax errors, and also simulated the produced light by the interactions of prompt gamma photons with water. We corrected the measured depth profiles of the luminescence images by subtracting the simulated distributions of the produced light by the interactions of prompt gamma photons in water. Corrections were also conducted using the estimated depth profiles of the light of the prompt gamma photons, as obtained from the off-beam areas of the luminescence images of water. With these corrections, we successfully obtained depth profiles that have almost identical distributions as the simulated dose distributions for protons. The percentage relative height of the Bragg peak with corrections to that of the simulation data increased to 94% from 80% without correction. Also, the percentage relative offset heights of the deeper part of the Bragg peak with corrections decreased to 0.2%–0.4% from 4% without correction. These results indicate that the luminescence imaging of water has potential for the dose distribution measurements for proton therapy dosimetry.

Efficiency improvement in proton dose calculations with an equivalent restricted stopping power formalism

The equivalent restricted stopping power formalism is introduced for proton mean energy loss calculations under the continuous slowing down approximation. The objective is the acceleration of Monte Carlo dose calculations by allowing larger steps while preserving accuracy. The fractional energy loss per step length ϵ was obtained with a secant method and a Gauss–Kronrod quadrature estimation of the integral equation relating the mean energy loss to the step length. The midpoint rule of the Newton–Cotes formulae was then used to solve this equation, allowing the creation of a lookup table linking ϵ to the equivalent restricted stopping power Leq, used here as a key physical quantity. The mean energy loss for any step length was simply defined as the product of the step length with Leq. Proton inelastic collisions with electrons were added to GPUMCD, a GPU-based Monte Carlo dose calculation code. The proton continuous slowing-down was modelled with the Leq formalism. GPUMCD was compared to Geant4 in a validation study where ionization processes alone were activated and a voxelized geometry was used. The energy straggling was first switched off to validate the Leq formalism alone. Dose differences between Geant4 and GPUMCD were smaller than 0.31% for the Leq formalism. The mean error and the standard deviation were below 0.035% and 0.038% respectively. 99.4 to 100% of GPUMCD dose points were consistent with a 0.3% dose tolerance. GPUMCD 80% falloff positions () matched Geant’s within 1 μm. With the energy straggling, dose differences were below 2.7% in the Bragg peak falloff and smaller than 0.83% elsewhere. The positions matched within 100 μm. The overall computation times to transport one million protons with GPUMCD were 31–173 ms. Under similar conditions, Geant4 computation times were 1.4–20 h. The Leq formalism led to an intrinsic efficiency gain factor ranging between 30–630, increasing with the prescribed accuracy of simulations. The Leq formalism allows larger steps leading to a algorithmic time complexity. It significantly accelerates Monte Carlo proton transport while preserving accuracy. It therefore constitutes a promising variance reduction technique for computing proton dose distributions in a clinical context.

Abstract ID: 96 Feasibility study of in vivo dose verification by analyzing time-structure of the prompt gammas in cancer treatment using proton beam

In the cancer treatment using the proton beam, in vivo dose verification is one of the most important in utilizing the characteristics of the proton beam delivering high dose to the target, called as Bragg peak. Measuring the prompt gammas generated along the beam track with the proton-induced nuclear interaction is one of the most preferred method. However, the detection efficiency is very low with their high energy (2–10 MeV), especially measuring the distal dose edge location is currently challengeable [1] . In the current study, the relationship between the time-structure of the prompt gamma and proton dose distribution was evaluated, and the feasibility of in vivo range verification by measuring the prompt gamma time-structure was evaluated with Geant4 Monte Carlo (MC) simulation. A detection system selectively measuring prompt gammas on 90 deg with tungsten collimators was employed [2] , and the detector measured the time-structure depending on the measurement position along the beam direction. The water phantom and lung phantom representing the homogeneous and the heterogeneous were used, respectively. In the current MC results, the time-structures of the prompt gammas in the both of the water phantom and lung phantom were clearly discriminated according to the detector position within 2 cm. Moreover, the depth resolution of less than 5 mm was achieved in the water phantom. It was observed that the patterns of the time-structures generated by the range modulation wheel step could potentially predict the beam current and the dose distribution. This study verified the feasibility of the in vivo dose verification by measuring the time structure of the prompt gammas. For the clinical use of this method, various background reduction techniques such as time-of-flight and pulse shape discrimination would be required.

Abstract ID: 124 Application expansion of the Monte-Carlo based treatment planning system for BNCT to particle radiotherapy and X-ray therapy

University of Tsukuba is developing an accelerator-based treatment device for boron neutron capture therapy (BNCT). As part of the development, a Monte-Carlo based treatment planning system (developing code: Tsukuba-Plan) is being developed [1] . The Tsukuba-plan has employed PHITS as the Monte-Carlo transport calculation code [2] . PHITS can calculate neutron, photon as well as proton and heavy-ions including carbon-ions. Therefore, Tsukuba-Plan with PHITS enables to perform dose estimations for not only BNCT but also particle radiotherapy and X-ray therapy. In BNCT protocols for malignant brain tumor, X-ray therapy is added after BNCT to enhance the treatment effect. And in the future, proton therapy will be also applied in stead of the X-ray therapy in order to improve therapeutic dose distribution. Therefore, the treatment planning system is required dose estimation for the combined multi-modality therapy. Based on this background, the aim of this study is to expand application field of the Tsukuba-plan to conventional external radiotherapies. University of Tsukuba Hospital has X-ray therapy, proton therapy and BNCT. Thus, first, we have expanded Tsukuba-plan to proton therapy and X-ray therapy. Regarding proton therapy, we have constructed 155 MeV and 200 MeV proton beam source and a geometry struction data for the proton therapy device installed in our Hospital. Verification for calculation accuracy for proton irradiation were performed. Phantom experiments performed using the proton therapy device in advance were represented by the Tsukuba-Plan. The proton dose distributions in the phantom were determined, and the calculations were compared with the experimental values. Calculations for both of proton therapy and X-ray therapy were in good agreement with experimental values, respectively. The results demonstrated that the Tsukuba-Plan enables to estimate accurately doses for proton irradiation and X-ray irradiations. To put Tsukuba-Plan to practical use for proton therapy and X-ray therapy, Tsukuba-Plan is improved further and several verifications are performed. This work was supported by JSPS KAKENHI Grant Nos. JP16K15343.

Abstract ID: 104 Efficiency improvement in proton dose calculations with an equivalent restricted stopping power formalism

To maintain the dose accuracy of Monte Carlo simulations, the mean energy loss calculation usually requires a step restriction (dmax). It leads to a O(n) algorithmic time complexity, where n is the subdivision number imposed by dmax. A new formalism is proposed to accelerate Monte Carlo dose calculations, allowing the removal of dmax in the step selection leading to a O(1) algorithmic time complexity. In this formalism, the midpoint rule of the Newton–Cotes formulae was used to solve the integral equation relating the mean energy loss to the step. The fractional energy loss was obtained with a secant method and a Gauss–Kronrod quadrature, revealing within the midpoint rule the equivalent restricted stopping power (Leq), used here as a key physical quantity. For any step, the mean energy loss was simply defined as the product of the step with Leq. Proton inelastic collisions with electrons were added to GPUMCD, a GPU-based Monte Carlo dose calculation code. The proton continuous slowing-down was modelled with the Leq formalism. First, the dose and time impacts of dmax were studied within Geant4. Second, in voxelized geometries, GPUMCD was compared to Geant4 using a high accuracy simulation setup (dmax = 10 μm). The ionization processes alone were activated and the energy straggling was first switched off to validate alone the Leq formalism. The default settings (dmax = 1 mm) in Geant4 led to an error of up to 16.5% in the falloff region, up to 4.8% elsewhere and the computation times were inversely proportional to the maximal step length allowed. Dose differences between Geant4 and GPUMCD were smaller than 0.31% in the Bragg peak for the Leq formalism. GPUMCD 80% falloff positions (R80) matched Geant R80 within 1 μm. With the energy straggling, dose agreements were within 2.7% in the falloff, below 0.83% elsewhere and R80 positions matched within 100 μm. The overall computation times per million transported protons with GPUMCD were 31–173 ms. Under similar conditions, Geant4 computation times were 1.4–20 h. The Leq formalism allows larger steps while preserving the accuracy. It significantly accelerates Monte Carlo proton transport. The Leq formalism constitutes a promising variance reduction technique for computing proton dose distributions in a clinical context.

Impact of bowel gas and body outline variations on total accumulated dose with intensity-modulated proton therapy in locally advanced cervical cancer patients

Introduction: Density changes occurring during fractionated radiotherapy in the pelvic region may degrade proton dose distributions. The aim of the study was to quantify the dosimetric impact of gas cavities and body outline variations.Material and methods: Seven patients with locally advanced cervical cancer (LACC) were analyzed through a total of 175 daily cone beam computed tomography (CBCT) scans. Four-beams intensity-modulated proton therapy (IMPT) dose plans were generated targeting the internal target volume (ITV) composed of: primary tumor, elective and pathological nodes. The planned dose was 45 Gy [Relative-Biological-Effectiveness-weighted (RBE)] in 25 fractions and simultaneously integrated boosts of pathologic lymph nodes were 55–57.5 Gy (RBE). In total, 475 modified CTs were generated to evaluate the effect of: 1/gas cavities, 2/outline variations and 3/the two combined. The anatomy of each fraction was simulated by propagating gas cavities contours and body outlines from each daily CBCT to the pCT. Hounsfield units corresponding to gas and fat were assigned to the propagated contours. D98 (least dose received by the hottest 98% of the volume) and D99.9 for targets and V43Gy(RBE) (volume receiving ≥43 Gy(RBE)) for organs at risk (OARs) were recalculated on each modified CT, and total dose was evaluated through dose volume histogram (DVH) addition across all fractions.Results: Weight changes during radiotherapy were between −3.1% and 1.2%. Gas cavities and outline variations induced a median [range] dose degradation for ITV45 of 1.0% [0.5–3.5%] for D98 and 2.1% [0.8–6.4%] for D99.9. Outline variations had larger dosimetric impact than gas cavities. Worst nodal dose degradation was 2.0% for D98 and 2.3% for D99.9. The impact on bladder, bowel and rectum was limited with V43Gy(RBE) variations ≤3.5 cm3.Conclusion: Bowel gas cavities and outline variations had minor impact on accumulated dose in targets and OAR of four-field IMPT in a LACC population of moderate weight changes.

Monte Carlo-driven predictions of neurocognitive and hearing impairments following proton and photon radiotherapy for pediatric brain-tumor patients.

As proton radiotherapy (RT) remains a limited resource, predictive estimates of the potential reduction in adverse treatment-related outcomes compared to photon RT could potentially help improve treatment selection. The aim of this study was to predict the magnitude of the neurocognitive and hearing deficits associated with proton and photon RT for children with brain tumors. The existing RT plans for 50 children treated with photon intensity modulated RT were compared with generated intensity modulated proton RT plans. The proton and photon RT dose distribution was used to estimate the Full Scale Intelligence Quotient (IQ) via a Monte Carlo model and the probability of hearing loss per ear, based on previously published dose-risk relationships. Compared to photon plans, the mean brain dose was found to be reduced in all proton plans, translating into a gain of [Formula: see text] IQ points for the whole cohort at 5years post-RT for dose regimens of 54Gy, or [Formula: see text] IQ points for dose regimens of 59.4Gy, where the errors shown represent statistical and systematic uncertainties. The probability of hearing loss ≥20dB per ear was less for proton versus photon RT: overall (9 ± 4) versus (17 ± 6)%, respectively, based on dose regimens of 54Gy, and (13 ± 5) versus (23 ± 9)% for dose regimens of 59.4Gy. Proton RT is thus expected to reduce the detrimental effect of RT upon IQ and hearing as compared to photon RT for pediatric brain tumors.

OC-0343: Experimental setup to measure magnetic field effects of proton dose distributions: simulation study

OC-0343: Experimental setup to measure magnetic field effects of proton dose distributions: simulation study

Prototype system for proton beam range measurement based on gamma electron vertex imaging

In proton therapy, for both therapeutic effectiveness and patient safety, it is very important to accurately measure the proton dose distribution, especially the range of the proton beam. For this purpose, recently we proposed a new imaging method named gamma electron vertex imaging (GEVI), in which the prompt gammas emitting from the nuclear reactions of the proton beam in the patient are converted to electrons, and then the converted electrons are tracked to determine the vertices of the prompt gammas, thereby producing a 2D image of the vertices. In the present study, we developed a prototype GEVI system, including dedicated signal processing and data acquisition systems, which consists of a beryllium plate (= electron converter) to convert the prompt gammas to electrons, two double-sided silicon strip detectors (= hodoscopes) to determine the trajectories of those converted electrons, and a plastic scintillation detector (= calorimeter) to measure their kinetic energies. The system uses triple coincidence logic and multiple energy windows to select only the events from prompt gammas. The detectors of the prototype GEVI system were evaluated for electronic noise level, energy resolution, and time resolution. Finally, the imaging capability of the GEVI system was tested by imaging a 90Sr beta source, a 60Co gamma source, and a 45-MeV proton beam in a PMMA phantom. The overall results of the present study generally show that the prototype GEVI system can image the vertices of the prompt gammas produced by the proton nuclear interactions.

Magnetic field effects on particle beams and their implications for dose calculation in MR-guided particle therapy.

To investigate and model effects of magnetic fields on proton and carbon ion beams for dose calculation. In a first step, Monte Carlo simulations using Gate 7.1/Geant4.10.0.p03 were performed for proton and carbon ion beams in magnetic fields ranging from 0 to 3 T. Initial particle energies ranged from 60 to 250 MeV (protons) and 120 to 400 MeV/u (carbon ions), respectively. The resulting dose distributions were analyzed focusing on beam deflection, dose deformation, as well as the impact of material heterogeneities. In a second step, a numerical algorithm was developed to calculate the lateral beam position. Using the Runge-Kutta method, an iterative solution of the relativistic Lorentz equation, corrected for the changing particle energy during penetration, was performed. For comparison, a γ-index analysis was utilized, using a criteria of 2%/2 mm of the local maximum. A tilt in the dose distribution within the Bragg peak area was observed, leading to non-negligible dose distribution changes. The magnitude was found to depend on the magnetic field strength as well as on the initial beam energy. Comparison of the 3 T dose distribution with non-B field (nominal) dose distributions, resulted in a γmean (mean value of the γ distribution) of 0.6, with 14.4% of the values above 1 and γ1 % (1% of all points have an equal or higher γ value) of 1.8. The presented numerical algorithm calculated the lateral beam offset with maximum errors of less than 2% with calculation times of less than 5 μs. The impact of tissue interfaces on the proton dose distributions was found to be less than 2% for a dose voxel size of 1 × 1 × 1 mm3 . Non-negligible dose deformations at the Bragg peak area were identified for high initial energies and strong magnetic fields. A fast numerical algorithm based on the solution of the energy-corrected relativistic Lorentz equation was able to describe the beam path, taking into account the particle energy, magnetic field, and material.