Proton Range Uncertainty Research Articles

Field-Specific Intensity-modulated Proton Therapy Optimization Technique for Breast Cancer Patients with Tissue Expanders Containing Metal Ports.

This report aims to propose and present an evaluation of a robust pencil beam scanning proton multi-field optimized treatment planning technique for postmastectomy radiation of breast cancer patients with implanted tissue expanders containing an internal metal port. Field-specific split targets were created for optimization to prevent spots from traveling through the metal port, while providing uniform coverage of the target with the use of a multi-field intensity modulated optimization approach. Two beam angles were strategically selected to provide complementary target coverage and plan robustness. The plan was compared with an independently developed photon plan and evaluated for robustness with respect to isocenter shifts, range shifts, and variation of the water-equivalent thickness of the port. The proton plan resulted in clinically acceptable target coverage and dosage to neighboring normal tissues. The D95% coverage was 95.3% in the nominal proton plan, with a worst-case coverage of 90.1% (when considering 0.3 cm isocenter shifts combined with 3.5% range uncertainty), and the coverage varied less than 1% under a hypothetically extreme variation of the port density. The proton plan had improved dose homogeneity compared with the photon plan, and reduced ipsilateral lung and mean heart doses. We demonstrated that a practical, field-specific intensity-modulated proton therapy (IMPT) optimization technique can be used to deal with the challenge of metal port in breast cancer patients with tissue expanders. The resulting proton plan has superior dosimetric characteristics over the best-case scenario photon plan, and is also robust to setup and proton range uncertainties.

Registration of pencil beam proton radiography data with X-ray CT.

Proton radiography seems to be a promising tool for assessing the quality of the stopping power computation in proton therapy. However, range error maps obtained on the basis of proton radiographs are very sensitive to small misalignment between the planning CT and the proton radiography acquisitions. In order to be able to mitigate misalignment in postprocessing, the authors implemented a fast method for registration between pencil proton radiography data obtained with a multilayer ionization chamber (MLIC) and an X-ray CT acquired on a head phantom. The registration was performed by optimizing a cost function which performs a comparison between the acquired data and simulated integral depth-dose curves. Two methodologies were considered, one based on dual orthogonal projections and the other one on a single projection. For each methodology, the robustness of the registration algorithm with respect to three confounding factors (measurement noise, CT calibration errors, and spot spacing) was investigated by testing the accuracy of the method through simulations based on a CT scan of a head phantom. The present registration method showed robust convergence towards the optimal solution. For the level of measurement noise and the uncertainty in the stopping power computation expected in proton radiography using a MLIC, the accuracy appeared to be better than 0.3° for angles and 0.3 mm for translations by use of the appropriate cost function. The spot spacing analysis showed that a spacing larger than the 5 mm used by other authors for the investigation of a MLIC for proton radiography led to results with absolute accuracy better than 0.3° for angles and 1 mm for translations when orthogonal proton radiographs were fed into the algorithm. In the case of a single projection, 6 mm was the largest spot spacing presenting an acceptable registration accuracy. For registration of proton radiography data with X-ray CT, the use of a direct ray-tracing algorithm to compute sums of squared differences and corrections of range errors showed very good accuracy and robustness with respect to three confounding factors: measurement noise, calibration error, and spot spacing. It is therefore a suitable algorithm to use in the in vivo range verification framework, allowing to separate in postprocessing the proton range uncertainty due to setup errors from the other sources of uncertainty.

An analysis of beam parameters on proton-acoustic waves through an analytic approach

It has been reported that acoustic waves are generated when a high-energy pulsed proton beam is deposited in a small volume within tissue. One possible application of proton-induced acoustics is to get real-time feedback for intra-treatment adjustments by monitoring such acoustic waves. A high spatial resolution in ultrasound imaging may reduce proton range uncertainty. Thus, it is crucial to understand the dependence of the acoustic waves on the proton beam characteristics. In this manuscript, firstly, an analytic solution for the proton-induced acoustic wave is presented to reveal the dependence of the signal on the beam parameters; then it is combined with an analytic approximation of the Bragg curve. The influence of the beam energy, pulse duration and beam diameter variation on the acoustic waveform are investigated. Further analysis is performed regarding the Fourier decomposition of the proton-acoustic signals. Our results show that the smaller spill time of the proton beam upsurges the amplitude of the acoustic wave for a constant number of protons, which is hence beneficial for dose monitoring. The increase in the energy of each individual proton in the beam leads to the spatial broadening of the Bragg curve, which also yields acoustic waves of greater amplitude. The pulse duration and the beam width of the proton beam do not affect the central frequency of the acoustic wave, but they change the amplitude of the spectral components.

Estimating patient specific uncertainty parameters for adaptive treatment re-planning in proton therapy using in vivo range measurements and Bayesian inference: application to setup and stopping power errors

In proton therapy, quantification of the proton range uncertainty is important to achieve dose distribution compliance. The promising accuracy of prompt gamma imaging (PGI) suggests the development of a mathematical framework using the range measurements to convert population based estimates of uncertainties into patient specific estimates with the purpose of plan adaptation. We present here such framework using Bayesian inference. The sources of uncertainty were modeled by three parameters: setup bias m, random setup precision r and water equivalent path length bias u. The evolution of the expectation values E(m), E(r) and E(u) during the treatment was simulated. The expectation values converged towards the true simulation parameters after 5 and 10 fractions, for E(m) and E(u), respectively. E(r) settle on a constant value slightly lower than the true value after 10 fractions. In conclusion, the simulation showed that there is enough information in the frequency distribution of the range errors measured by PGI to estimate the expectation values and the confidence interval of the model parameters by Bayesian inference. The updated model parameters were used to compute patient specific lateral and local distal margins for adaptive re-planning.

SU-F-T-598: Robotic Radiosurgery System Versus Pencil Beam Scanning Proton Therapy for Definitive Intracranial Treatments

Purpose: To characterize the dose distributions of Cyberknife and intensity-modulated-proton-therapy (IMPT). Methods: A total of 20 patients previously treated with Cyberknife were selected. The original planning-target-volume (PTV) was used in the ‘IMPT-ideal’ plan assuming a comparable image-guidance with Cyberknife. A 3mm expansion was made to create the proton-PTV for the ‘IMPT-3mm’ plan representing the current proton-therapy where a margin of 3mm is used to account for the inferior image-guidance. The proton range uncertainty was taken-care in beam-design by adding the proximal- and distal-margins (3%water-equivalent-depth+1mm) for both proton plans. The IMPT plans were generated to meet the same target coverage as the Cyberknife-plans. The plan quality of IMPT-ideal and IMPT-3mm were compared to the Cyberknife-plan. To characterize plan quality, we defined the ratio(R) of volumes encompassed by the selected isodose surfaces for Cyberknife and IMPT plans (VCK/VIMPT). Comparisons were made for both Cyberknife versus IMPT-ideal and Cyberknife versusIMPT-3mm to further discuss the impact of setup error margins used in proton therapy and the correlation with target size and location. Results: IMPT-ideal plans yield comparable plan quality as CK plans and slightly better OAR sparing while the IMPT-3mm plan results in a higher dose to the OARs, especially for centralized tumors. Comparing to the IMPT-ideal plans, a slightly larger 80% (Ravg=1.05) dose cloud and significantly larger 50% (Ravg=1.3) and 20% (Ravg=1.60) dose clouds are seen in CK plans. However, the 3mm expansion results in a larger high and medium dose clouds in IMPT-3mm plans (Ravg=0.65 for 80%-isodose; Ravg=0.93 for 50%-isodose). The trend increases with the size of the target and the distance from the brainstem to the center of target. Conclusion: Cyberknife is more preferable for treating centralized targets and proton therapy is advantageous for the large and peripheral targets. Advanced image guidance would improve the efficacy of proton therapy for intracranial treatments.

SU‐F‐T‐186: A Treatment Planning Study of Normal Tissue Sparing with Robustness Optimized IMPT, 4Pi IMRT, and VMAT for Head and Neck Cases

Purpose:We performed a retrospective dosimetric comparison study between the robustness optimized Intensity Modulated Proton Therapy (RO‐IMPT), volumetric‐modulated arc therapy (VMAT), and the non‐coplanar 4? intensity modulated radiation therapy (IMRT). These methods represent the most advanced radiation treatment methods clinically available. We compare their dosimetric performance for head and neck cancer treatments with special focus on the OAR sparing near the tumor volumes.Methods:A total of 11 head and neck cases, which include 10 recurrent cases and one bilateral case, were selected for the study. Different dose levels were prescribed to tumor target depending on disease and location. Three treatment plans were created on commercial TPS systems for a novel noncoplanar 4π method (20 beams), VMAT, and RO‐IMPT technique (maximum 4 fields). The maximum patient positioning error was set to 3 mm and the maximum proton range uncertainty was set to 3% for the robustness optimization. Line dose profiles were investigated for OARs close to tumor volumes.Results:All three techniques achieved 98% coverage of the CTV target and most photon plans had less than 110% of the hot spots. The RO‐IMPT plans show superior tumor dose homogeneity than 4? and VMAT plans. Although RO‐IMPT has greater R50 dose spillage to the surrounding normal tissue than 4π and VMAT, the RO‐IMPT plans demonstrate better or comparable OAR (parotid, mandible, carotid, oral cavity, pharynx, and etc.) sparing for structures closely abutting tumor targets.Conclusion:The RO‐IMPT's ability of OAR sparing is benchmarked against the C‐arm linac based non‐coplanar 4π technique and the standard VMAT method. RO‐IMPT consistently shows better or comparable OAR sparing even for tissue structures closely abutting treatment target volume. RO‐IMPT further reduces treatment uncertainty associated with proton therapy and delivers robust treatment plans to both unilateral and bilateral head and neck cancer patients with desirable treatment time.

Fast and accurate sensitivity analysis of IMPT treatment plans using Polynomial Chaos Expansion

The highly conformal planned dose distribution achievable in intensity modulated proton therapy (IMPT) can severely be compromised by uncertainties in patient setup and proton range. While several robust optimization approaches have been presented to address this issue, appropriate methods to accurately estimate the robustness of treatment plans are still lacking. To fill this gap we present Polynomial Chaos Expansion (PCE) techniques which are easily applicable and create a meta-model of the dose engine by approximating the dose in every voxel with multidimensional polynomials. This Polynomial Chaos (PC) model can be built in an automated fashion relatively cheaply and subsequently it can be used to perform comprehensive robustness analysis. We adapted PC to provide among others the expected dose, the dose variance, accurate probability distribution of dose-volume histogram (DVH) metrics (e.g. minimum tumor or maximum organ dose), exact bandwidths of DVHs, and to separate the effects of random and systematic errors. We present the outcome of our verification experiments based on 6 head-and-neck (HN) patients, and exemplify the usefulness of PCE by comparing a robust and a non-robust treatment plan for a selected HN case. The results suggest that PCE is highly valuable for both research and clinical applications.

Evaluation of Single Field Uniform Dose (SFUD) Proton Pencil Beam Scanning (PBS) Planning Strategy for Lung Mobile Tumor Using a Digital Phantom

Purpose: To quantitatively evaluate four different Proton SFUD PBS initial planning strategies for lung mobile tumor. Methods and Materials: A virtual lung patient’s four-dimensional computed tomography (4DCT) was generated in this study. To avoid the uncertainties from target delineation and imaging artifacts, a sphere with diameter of 3 cm representing a rigid mobile target (GTV) was inserted into the right side of the lung. The target motion is set in superior-inferior (SI) direction from ?5 mm to 5 mm. Four SFUD planning strategies were used based on: 1) Maximum-In-tensity-Projection Image (MIP-CT); 2) CT_average with ITV overridden to muscle density (CTavg_muscle); 3) CT_average with ITV overridden to tumor density (CTavg_tumor); 4) CT_average without any override density (CTavg_only). Dose distributions were recalculated on each individual phase and accumulated together to assess the “actual” treatment. To estimate the impact of proton range uncertainties, +/?3.5% CT calibration curve was applied to the 4DCT phase images. Results: Comparing initial plan to the dose accumulation: MIP-CT based GTV D98 degraded 2.42 Gy (60.10 Gy vs 57.68 Gy). Heart D1 increased 6.19 Gy (1.88 Gy vs 8.07 Gy); CTavg_tumor based GTV D98 degraded 0.34 Gy (60.07 Gy vs 59.73 Gy). Heart D1 increased 2.24 Gy (3.74 Gy vs 5.98 Gy); CTavg_muscle based initial GTV D98 degraded 0.31 Gy (60.4 Gy vs 60.19 Gy). Heart D1 increased 3.44 Gy (4.38 Gy vs 7.82 Gy); CTavg_only based Initial GTV D98 degraded 6.63 Gy (60.11 Gy vs 53.48 Gy). Heart D1 increased 0.30 Gy (2.69 Gy vs 2.96 Gy); in the presence of ±3.5% range uncertainties, CTavg_tumor based plan’s accumulated GTV D98 degraded to 57.99 Gy (+3.5%) 59.38 Gy (?3.5%), and CTavg_muscle based plan’s accumulated GTV D98 degraded to 59.37 Gy (+3.5%) 59.37 Gy (?3.5%). Conclusion: This study shows that CTavg_Tumor and CTavg_Muscle based planning strategies provide the most robust GTV coverage. However, clinicians need to be aware that the actual dose to OARs at distal end of target may increase. The study also indicates that the current SFUD PBS planning strategy might not be sufficient to compensate the CT calibration uncertainty.

Passive proton therapy vs. IMRT planning study with focal boost for prostate cancer.

BackgroundExploiting biologic imaging, studies have been performed to boost dose to gross intraprostatic tumor volumes (GTV) while reducing dose elsewhere in the prostate. Interest in proton beams has increased due to superior normal-tissue sparing they afford. Our goal was to dosimetrically compare 3D conformal proton boost plans with intensity-modulated radiation therapy (IMRT) plans with respect to target coverage and avoiding organs at risk.MethodsTreatment planning computer tomography scans of ten patients were selected. For each patient, two hypothetical but realistic GTVs each with a fixed volume were contoured in different anatomical locations of the prostate. IMRT and proton beam plans were created with a prescribed dose of 50.4 Gy to the initial planning target volume (PTV) including the PTV of the seminal vesicles (PSV), 70.2 Gy to the PTV of the prostate (PPS), and 90 Gy to the PTV of the gross tumor volumes (PGTVs). For proton plans, uncertainties of range and patient setup were accounted for; apertures were adjusted until the dose-volume coverage of PTVs matched that of the IMRT plan. For both plans, prescribed PTV doses were made identical to allow for comparing normal-tissue doses.ResultsProtons delivered more homogeneous but less conformal doses to PGTVs than IMRT did and comparable doses to PSV and PPS. Volumes of bladder and rectum receiving doses higher than 65 Gy were similar for both plans. However, volumes receiving less than 65 Gy were significantly reduced, i.e., protons reduced integral dose by 45.6 % and 26.5 % for rectum and bladder, respectively. This volume-sparing was also seen in femoral heads and penile bulb.ConclusionsProtons delivered comparable doses to targets in dose homogeneity and conformity and spared normal tissues from intermediate-to-low doses better than IMRT did. Further improvement of dose sparing and changes in homogeneity and conformity may be achieved by reducing proton range uncertainties and from implementing intensity modulation.

SU‐F‐BRD‐05: Robustness of Dose Painting by Numbers in Proton Therapy

Purpose:Proton range uncertainties may cause important dose perturbations within the target volume, especially when steep dose gradients are present as in dose painting. The aim of this study is to assess the robustness against setup and range errors for high heterogeneous dose prescriptions (i.e., dose painting by numbers), delivered by proton pencil beam scanning.Methods:An automatic workflow, based on MATLAB functions, was implemented through scripting in RayStation (RaySearch Laboratories). It performs a gradient‐based segmentation of the dose painting volume from 18FDG‐PET images (GTVPET), and calculates the dose prescription as a linear function of the FDG‐uptake value on each voxel. The workflow was applied to two patients with head and neck cancer. Robustness against setup and range errors of the conventional PTV margin strategy (prescription dilated by 2.5 mm) versus CTV‐based (minimax) robust optimization (2.5 mm setup, 3% range error) was assessed by comparing the prescription with the planned dose for a set of error scenarios.Results:In order to ensure dose coverage above 95% of the prescribed dose in more than 95% of the GTVPET voxels while compensating for the uncertainties, the plans with a PTV generated a high overdose. For the nominal case, up to 35% of the GTVPET received doses 5% beyond prescription. For the worst of the evaluated error scenarios, the volume with 5% overdose increased to 50%. In contrast, for CTV‐based plans this 5% overdose was present only in a small fraction of the GTVPET, which ranged from 7% in the nominal case to 15% in the worst of the evaluated scenarios.Conclusion:The use of a PTV leads to non‐robust dose distributions with excessive overdose in the painted volume. In contrast, robust optimization yields robust dose distributions with limited overdose.RaySearch Laboratories is sincerely acknowledged for providing us with RayStation treatment planning system and for the support provided.

TU-F-CAMPUS-J-01: Dosimetric Effects of HU Changes During the Course of Proton Therapy for Lung Cancer

Purpose: To characterize the changes in Hounsfield unit (HU) in lung radiotherapy with proton beams during the course of treatment and to study the effect on the proton plan dose distribution. Methods: Twenty consecutive patients with non-small cell lung cancer treated with proton radiotherapy who underwent multiple CT scans including the planning CT and weekly verification CTs were studied. HU histograms were computed for irradiated lung volumes in beam paths for all scans using the same treatment plan. Histograms for un-irradiated lung volume were used as control to characterize inter-scan variations. HU statistics were calculated for both irradiated and un-irradiated lung volumes for each patient scan. Further, multiple CT scans based on the same planning CT were generated by replacing the HU of the lung based on the verification CT scans HU values. Using the same beam arrangement, we created plans for each of the altered CT scans to study the dosimetric effect using the dose volume histogram. Results: Lung HU decreased for irradiated lung volume during the course of radiotherapy. The magnitude of this change increased with total irradiation dose. On average, HU changed by −53.8 in the irradiated volume. This change resulted in less than 0.5mm of beam overshoot in tissue for every 1cm beam traversed in the irradiated lung. The dose modification is about +3% for the lung, and less than +1% for the primary tumor. Conclusion: HU of the lung decrease throughout the course of radiation therapy. This change results in a beam overshoot (e.g. 3mm for 6cm of lung traversed) and causes a small dose modification in the overall plan. However, this overshoot does not affect the quality of plans since the margins used in planning, based on proton range uncertainty, are greater. HU needs to change by 150 units before re-planning is warranted.

SU‐E‐T‐681: Robust and Monte Carlo‐Based Intensity Modulated Proton Therapy Optimization with GPU Acceleration

Purpose:Accuracy of dose calculation models and robustness under various uncertainties are key factors influencing the quality of intensity modulated proton therapy (IMPT) plans. In this work, a robust IMPT optimization based on accurate Monte Carlo (MC) dose calculation is developed.Methods:We used an in‐house developed and graphics processing unit (GPU) accelerated MC for dose calculation. For robust optimization, dose volume histograms (DVHs) were computed for each uncertainty scenario at each optimization iteration. A gradient based adaptive method was used to improve the DVHs with adjustable scenario weights. GPUs were employed to accelerate the optimization process. Uncertainties in patient setup and proton range were considered in all cases studied. Additionally, the uncertainty of intra‐fraction relative shift between fields was considered for craniospinal irradiation cases. The adaptive robust optimization method was compared with for clinical cases at several different disease sites.Results:Comparing with the traditional optimization target volume (OTV) based method, the adaptive robust optimization spared critical structures better while maintain the target coverage in clinical cases. For example, the right parotid hot spot dose was reduced from 78.5Gy to 74.5Gy as shown in Fig. 1. For craniospinal irradiation, the adaptive method found the robust solution at field junctions without manual feathering of the match lines. Even for relatively large head‐and‐neck cases and craniospinal cases, the whole process of MC dose calculation and robust optimization can be done within 30 minutes on a system of 100 Nvidia GeForce GTX Titan cards.Conclusion:A robust IMPT treatment planning system is developed utilizing an adaptive method. The treatment planning optimization is based on MC dose calculation and is accelerated by GPU to be clinically viable.This work is supported in part by Varian Medical Systems.

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

Purpose: Breathing motion and approximate dose calculation engines may increase proton range uncertainties. We address these two issues using a comprehensive 4D robustness evaluation tool based on an efficient Monte Carlo (MC) engine, which can simulate breathing with no significant increase in computation time. Methods: To assess the robustness of the treatment plan, multiple scenarios of uncertainties are simulated, taking into account the systematic and random setup errors, range uncertainties, and organ motion. Our fast MC dose engine, called MCsquare, implements optimized models on a massively-parallel computation architecture and allows us to accurately simulate a scenario in less than one minute. The deviations of the uncertainty scenarios are then reported on a DVH-band and compared to the nominal plan.The robustness evaluation tool is illustrated in a lung case by comparing three 60Gy treatment plans. First, a plan is optimized on a PTV obtained by extending the CTV with an 8mm margin, in order to take into account systematic geometrical uncertainties, like in our current practice in radiotherapy. No specific strategy is employed to correct for tumor and organ motions. The second plan involves a PTV generated from the ITV, which encompasses the tumor volume in all breathing phases. The last plan results from robust optimization performed on the ITV, with robustness parameters of 3% for tissue density and 8 mm for positioning errors. Results: The robustness test revealed that the first two plans could not properly cover the target in the presence of uncertainties. CTV-coverage (D95) in the three plans ranged respectively between 39.4–55.5Gy, 50.2–57.5Gy, and 55.1–58.6Gy. Conclusion: A realistic robustness verification tool based on a fast MC dose engine has been developed. This test is essential to assess the quality of proton therapy plan and very useful to study various planning strategies for mobile tumors. This work is partly funded by IBA (Louvain-la-Neuve, Belgium)

Impact of respiratory motion on worst-case scenario optimized intensity modulated proton therapy for lung cancers

PurposeWe compared conventionally optimized intensity modulated proton therapy (IMPT) treatment plans against worst-case scenario optimized treatment plans for lung cancer. The comparison of the 2 IMPT optimization strategies focused on the resulting plans’ ability to retain dose objectives under the influence of patient setup, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods and materialsFor each of the 9 lung cancer cases, 2 treatment plans were created that accounted for treatment uncertainties in 2 different ways. The first used the conventional method: delivery of prescribed dose to the planning target volume that is geometrically expanded from the internal target volume (ITV). The second used a worst-case scenario optimization scheme that addressed setup and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of changes in patient anatomy attributable to respiratory motion were investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the 2 groups were compared with 2-sided paired Student t tests. ResultsWithout respiratory motion considered, we affirmed that worst-case scenario optimization is superior to planning target volume–based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, worst-case scenario optimization still achieved more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality (D95% ITV, 96.6% vs 96.1% [P = .26]; D5%− D95% ITV, 10.0% vs 12.3% [P = .082]; D1% spinal cord, 31.8% vs 36.5% [P = .035]). ConclusionsWorst-case scenario optimization led to superior solutions for lung IMPT. Despite the fact that worst-case scenario optimization did not explicitly account for respiratory motion, it produced motion-resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization.

The influence of patient positioning uncertainties in proton radiotherapy on proton range and dose distributions.

Proton radiotherapy allows radiation treatment delivery with high dose gradients. The nature of such dose distributions increases the influence of patient positioning uncertainties on their fidelity when compared to photon radiotherapy. The present work quantitatively analyzes the influence of setup uncertainties on proton range and dose distributions. Thirty-eight clinical passive scattering treatment fields for small lesions in the head were studied. Dose distributions for shifted and rotated patient positions were Monte Carlo-simulated. Proton range uncertainties at the 50%- and 90%-dose falloff position were calculated considering 18 arbitrary combinations of maximal patient position shifts and rotations for two patient positioning methods. Normal tissue complication probabilities (NTCPs), equivalent uniform doses (EUDs), and tumor control probabilities (TCPs) were studied for organs at risk (OARs) and target volumes of eight patients. The authors identified a median 1σ proton range uncertainty at the 50%-dose falloff of 2.8 mm for anatomy-based patient positioning and 1.6 mm for fiducial-based patient positioning as well as 7.2 and 5.8 mm for the 90%-dose falloff position, respectively. These range uncertainties were correlated to heterogeneity indices (HIs) calculated for each treatment field (38%<R2<50%). A NTCP increase of more than 10% (absolute) was observed for less than 2.9% (anatomy-based positioning) and 1.2% (fiducial-based positioning) of the studied OARs and patient shifts. For target volumes TCP decreases by more than 10% (absolute) occurred in less than 2.2% of the considered treatment scenarios for anatomy-based patient positioning and were nonexistent for fiducial-based patient positioning. EUD changes for target volumes were up to 35% (anatomy-based positioning) and 16% (fiducial-based positioning). The influence of patient positioning uncertainties on proton range in therapy of small lesions in the human brain as well as target and OAR dosimetry were studied. Observed range uncertainties were correlated with HIs. The clinical practice of using multiple fields with smeared compensators while avoiding distal OAR sparing is considered to be safe.

Beam-specific planning volumes for scattered-proton lung radiotherapy

This work describes the clinical implementation of a beam-specific planning treatment volume (bsPTV) calculation for lung cancer proton therapy and its integration into the treatment planning process. Uncertainties incorporated in the calculation of the bsPTV included setup errors, machine delivery variability, breathing effects, inherent proton range uncertainties and combinations of the above. Margins were added for translational and rotational setup errors and breathing motion variability during the course of treatment as well as for their effect on proton range of each treatment field. The effect of breathing motion and deformation on the proton range was calculated from 4D computed tomography data. Range uncertainties were considered taking into account the individual voxel HU uncertainty along each proton beamlet. Beam-specific treatment volumes generated for 12 patients were used: a) as planning targets, b) for routine plan evaluation, c) to aid beam angle selection and d) to create beam-specific margins for organs at risk to insure sparing. The alternative planning technique based on the bsPTVs produced similar target coverage as the conventional proton plans while better sparing the surrounding tissues. Conventional proton plans were evaluated by comparing the dose distributions per beam with the corresponding bsPTV. The bsPTV volume as a function of beam angle revealed some unexpected sources of uncertainty and could help the planner choose more robust beams. Beam-specific planning volume for the spinal cord was used for dose distribution shaping to ensure organ sparing laterally and distally to the beam.

SU‐E‐T‐324: The Influence of Patient Positioning Uncertainties in Proton Radiotherapy On Proton Range and Dose Distributions

Purpose:Proton radiotherapy allows radiation treatment delivery with high dose gradients. The nature of such dose distributions increases the influence of patient positioning uncertainties on their fidelity when compared to photon radiotherapy. The present work quantitatively analyzes the influence of setup uncertainties on proton range and dose distributions.Methods:38 clinical passive scattering treatment fields for small lesions in the head were studied. Dose distributions for shifted and rotated patient positions were Monte Carlo‐simulated. Proton range uncertainties at the 50% and 90%‐dose falloff position were calculated considering 18 arbitrary combinations of maximal patient position shifts and rotations for two patient positioning methods. Normal tissue complication probabilities (NTCPs), equivalent uniform doses (EUDs) and tumor control probabilities (TCPs) were studied for organs at risk (OARs) and target volumes of eight patients.Results:We identified a median 1σ proton range uncertainty at the 50%‐dose falloff of 2.8 mm for anatomy‐based patient positioning and 1.6 mm for fiducial‐based patient positioning as well as 7.2 mm and 5.8 mm for the 90%‐dose falloff position respectively. These range uncertainties were correlated to heterogeneity indices (HIs) calculated for each treatment field (38% &lt; R2 &lt; 50%). A NTCP increase of more than 10% (absolute) was observed for less than 2.9% (anatomy‐based positioning) and 1.2% (fiducial‐based positioning) of the studied OARs and patient shifts. TCP decreases larger than 10% (absolute) were seen for less than 2.2% of the target volumes or non‐existent. EUD changes were up to 178% for OARs and 35% for target volumes.Conclusion:The influence of patient positioning uncertainties on proton range in therapy of small lesions in the human brain and target and OAR dosimetry were studied. Observed range uncertainties were correlated with HIs. The clinical practice of using multiple compensator‐smeared treatment beams selected to avoid distal OAR sparing is considered to be safe.J. L. was supported by a scholarship of the University of Vienna

SU‐E‐J‐125: Classification of CBCT Noises in Terms of Their Contribution to Proton Range Uncertainty

Purpose:This study assesses the potential use of CBCT images in adaptive protontherapy by estimating the contribution of the main sources of noise and calibration errors to the proton range uncertainty.Methods:Measurements intended to highlight each particular source have been achieved by adapting either the testbench configuration, e.g. use of filtration, fan‐beam collimation, beam stop arrays, phantoms and detector reset light, or the sequence of correction algorithms including water precorrection. Additional Monte‐Carlo simulations have been performed to complement these measurements, especially for the beam hardening and the scatter cases. Simulations of proton beams penetration through the resulting images have then been carried out to quantify the range change due to these effects. The particular case of a brain irradiation is considered mainly because of the multiple effects that the skull bones have on the internal soft tissues.Results:On top of the range error sources is the undercorrection of scatter. Its influence has been analyzed from a comparison of fan‐beam and full axial FOV acquisitions. In this case, large range errors of about 12 mm can be reached if the assumption is made that the scatter has only a constant contribution over the projection images. Even the detector lag, which a priori induces a much smaller effect, has been shown to contribute for up to 2 mm to the overall error if its correction only aims at reducing the skin artefact. This last result can partially be understood by the larger interface between tissues and bones inside the skull.Conclusion:This study has set the basis of a more systematical analysis of the effect CBCT noise on range uncertainties based on a combination of measurements, simulations and theoretical results. With our method, even more subtle effects such as the cone‐beam artifact or the detector lag can be assessed.SBR and JOR are financed by iMagX, a public‐private partnership between the region Wallone of Belgium and IBA under convention #1217662

SU‐E‐T‐452: Impact of Respiratory Motion On Robustly‐Optimized Intensity‐Modulated Proton Therapy to Treat Lung Cancers

Purpose:We compared conventionally optimized intensity‐modulated proton therapy (IMPT) treatment plans against the worst‐case robustly optimized treatment plans for lung cancer. The comparison of the two IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient set‐up, inherent proton range uncertainty, and dose perturbation caused by respiratory motion.Methods:For each of the 9 lung cancer cases two treatment plans were created accounting for treatment uncertainties in two different ways: the first used the conventional Method: delivery of prescribed dose to the planning target volume (PTV) that is geometrically expanded from the internal target volume (ITV). The second employed the worst‐case robust optimization scheme that addressed set‐up and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of the changes in patient anatomy due to respiratory motion was investigated for both strategies by comparing the corresponding plan evaluation metrics at the end‐inspiration and end‐expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the two groups were compared using two‐sided paired t‐tests.Results:Without respiratory motion considered, we affirmed that worst‐case robust optimization is superior to PTV‐based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, robust optimization still leads to more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality [D95% ITV: 96.6% versus 96.1% (p=0.26), D5% – D95% ITV: 10.0% versus 12.3% (p=0.082), D1% spinal cord: 31.8% versus 36.5% (p =0.035)].Conclusion:Worst‐case robust optimization led to superior solutions for lung IMPT. Despite of the fact that robust optimization did not explicitly account for respiratory motion it produced motion‐resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization.

Practical considerations in the calibration of CT scanners for proton therapy.

Treatment planning systems for proton therapy require a CT calibration curve relating Hounsfield units to proton stopping powers. An understanding of the accuracy of this curve, together with its limitations, is of utmost importance because the calibration underpins the calculated dose distribution of every patient preparing to undergo proton therapy, independent of delivery technique. The most common approach to the calibration is the stoichiometric method, which is well‐defined and, in principle, straightforward to perform. Nevertheless, care must be taken when implementing it in the clinic in order to avoid introducing proton range uncertainties into treatment plans that are larger than the 3.5% that target margins are typically designed to account for. This work presents a variety of aspects related to the user‐specific implementation of the stoichiometric calibration, from both a measurement setup and a data‐handling point of view, and evaluates the potential impact of each for treatment planning purposes. We demonstrate that two alternative commercial vendors' tissue phantoms yield consistent results, that variable CT slice thickness is unimportant, and that, for a given cross‐sectional size, all phantom data can, with today's state‐of‐the‐art beam hardening‐related artifact reduction software, be acquired quickly and easily with a single scan, such that the resulting curve describes the calibration well at different positions across the imaging plane. We also show that one should be cautious of using metals in the calibration procedure and of using a single curve for anatomical sites differing widely in size. Further, we suggest that the quality of the parametric fit to the measurement data can be improved by performing a constrained, weighted linear regression. These observations, based on the 40 separate curves that were calculated, should help the medical physicist at any new proton therapy facility in deciding which considerations are worth particular attention.PACS numbers: 87.53.Bn, 87.55.‐x, 87.57.Q‐, 87.59.bd