Nominal Plan Research Articles

Robustness assessment using probabilistic scenarios of intensity modulated proton therapy and volumetric arc therapy in non-small-cell lung cancer: an in-silico radiotherapy planning study

BackgroundRadiotherapy is an essential treatment component for patients with stage III non-small-cell lung cancer. Despite advances, survival remains poor. Proton beam therapy holds the promise of improving cure rates without increasing treatment-related toxicity. However, precision in dose delivery is sensitive to setup uncertainties. The conventional method of adding a margin to account for this problem can be inadequate. We aimed to use the probabilistic scenarios methodology to assess the robustness of intensity modulated proton therapy (IMPT) and volumetric arc therapy (VMAT). MethodsPlans were optimised by minimax robust optimisation (MM) and margin-based (planning target volume [PTV]) methods (MM–IMPT, PTV–IMPT, and VMAT). Robustness was assessed with probabilistically simulated setup errors. 35 perturbed doses were summed to model a treatment course. The CTV-D98 (dose to 98% of the clinical target volume) of each summed dose distribution was compared with the nominal plan and considered robust if within 5%. The variance of the CTV-D98 in IMPT and VMAT plans were compared using Levene's Test. Findings700 simulations from 20 plans were analysed. Despite dose variation over a simulated course of treatment, the robustness of each summed plan was within clinical limits. There was significantly less variance in the perturbed CTV-D98 in the MM–IMPT than in PTV–IMPT plans (4·43 cGy2vs 16·17, F=50·993, p<0·0001). There was no statistically significant difference between the variance in VMAT and MM–IMPT plans (2·23 cGy2vs 4·04, F=0·312, p=0·577). Target conformality improved with increasing number of beams and robust optimisation. All summed plans met normal tissue dose constraints. InterpretationInitial results showed that fractionation reduced uncertainties in dose distribution due to setup errors. Robustness of MM–IMPT and VMAT plans were similar. Although the present analysis has not considered range uncertainties and organ motion, the simulations highlight differences in plan qualities with different optimisation strategies. The probabilistic scenarios methodology might be used to estimate robustness of IMPT plans in stage III non-small-cell lung cancer. FundingCancer Research UK.

Refueling station location problem with traffic deviation considering route choice and demand uncertainty

Construction of refueling stations in a traffic network is a major step toward the promotion of hydrogen fuel vehicles in the metropolitan areas. This research provides a framework for the refueling demand uncertainty and the effect of travelers' deviation to refuel considerations in the network. First, considering the refueling demand uncertainty of the hydrogen fuel vehicles market, we propose a discrete, robust optimization model in which refueling demand is formulated as an uncertainty set during planning horizon. A cutting plane algorithm is adopted to solve this robust centralized planning model. Numerical results demonstrate that the robust model can lead to more reliable design compared to the nominal plan. Second, a link-based bi-level program is proposed in which the lower level problem describes the user equilibrium traffic condition characterized by the locations of refueling stations. This model is solved using a computationally efficient genetic algorithm. Numerical examples indicate that as the refueling demand share increases, total system travel time, for both refueling and non-refueling users, increases. This increase is more pronounced in low levels of refueling demand share compared to high levels.

Robust treatment planning with conditional value at risk chance constraints in intensity-modulated proton therapy.

Intensity-modulated proton therapy (IMPT) is highly sensitive to range uncertainties and uncertainties caused by setup variation. The conventional inverse treatment planning of IMPT based on the planning target volume (PTV) is not often sufficient to ensure robustness of treatment plans. We applied a probabilistic framework (chance-constrained optimization) in IMPT planning to hedge against the influence of uncertainties. We retrospectively selected one patient with lung cancer, one patient with head and neck (H&N) cancer, and one with prostate cancer for this analysis. Using their original images and prescriptions, we created new IMPT plans using two methods: (1) a robust chance-constrained treatment planning method with the clinical target volume (CTV) as the target; (2) the margin-based method with PTV as the target, which was solved by commercial software, CPLEX, using linear programming. For the first method, we reformulated the model into a tractable mixed-integer programming problem and sped up the calculation using Benders decomposition. The dose-volume histograms (DVHs) from the nominal and perturbed dose distributions were used to assess and compare plan quality. DVHs for all uncertain scenarios along with the nominal DVH were plotted. The width of the "bands" of DVHs was used to quantify the plan sensitivity to uncertainty. The newly developed Benders decomposition method was compared with a commercial solution to demonstrate its computational efficiency. The trade-off between nominal plan quality and plan robustness was investigated. Our chance-constrained model outperformed the PTV method in terms of tumor coverage, tumor dose homogeneity, and plan robustness. Our model was shown to produce IMPT plans to meet the dose-volume constraints of organs at risk (OARs) and had better sparing of OARs than the PTV method in the three clinical cases included in this study. The chance-constrained model provided a flexible tool for users to balance between plan robustness and plan quality. In addition, our in-house developed method was found to be much faster than the commercial solution. With explicit control of plan robustness, the chance-constrained robust optimization model generated superior IMPT plans compared to the PTV-based method.

Mobile Network Planing Process Case Study - 3G Network

Third Generation cellular networks (3G) were developed with the aim of offering high data rates up to 2Mbps and 384Kbps for stationary and mobile users respectively which allows the operators to offer a multimedia connectivity and other data services to the end customers. In this work we apply techniques to design a 3G radio network, in particular we study the planning and implementation in developing countries, and state of Palestine as a case study. In order to carry a 3G radio network planning for a selected regions, we must follow a roadmap consists of set of phases; First of all, we must determine the region under study on the digitized map in order to obtain some useful information, such as the area distribution; thus using digital maps gives a good clearness for areas classification, land use, land terrain, heights, vectors, etc. Also we must forecast subscriber profile to perform coverage and capacity dimensioning process to achieve nominal cell plan. This paper work studies Nablus as one of the major Palestinian cities. then, subscriber forecast profile is applied in order to calculate the service traffic demand, the capacity and and coverage requirements, this study is carried in corporation with Wataniya which is one of the leading mobile telecommunication service provider in Palestine. For Nablus city we’ve found that 28 sites are required to be installed to meet the given capacity requirements, on the other hand 46 sites are for coverage. At this point we should make decision about how many site will be implemented. In general we have to select number of sites relative to coverage requirement; so to serve Nablus city by 3G services we should implement 46 sites. At final stage, we have to be sure that our proposed 3G network is suitable not only for the first year of running the 3G services over the deployed network, our design takes into consideration the growth of subscribers number and their demands, so periodically, the networking administrators and the network planning department, assess the network current status and upgrade the network to meet the future demands.

Limited Impact of Setup and Range Uncertainties, Breathing Motion, and Interplay Effects in Robustly Optimized Intensity Modulated Proton Therapy for Stage III Non-small Cell Lung Cancer

To investigate the impact of setup and range uncertainties, breathing motion, and interplay effects using scanning pencil beams in robustly optimized intensity modulated proton therapy (IMPT) for stage III non-small cell lung cancer (NSCLC). Three-field IMPT plans were created using a minimax robust optimization technique for 10 NSCLC patients. The plans accounted for 5- or 7-mm setup errors with ±3% range uncertainties. The robustness of the IMPT nominal plans was evaluated considering (1) isotropic 5-mm setup errors with ±3% range uncertainties; (2) breathing motion; (3) interplay effects; and (4) a combination of items 1 and 2. The plans were calculated using 4-dimensional and average intensity projection computed tomography images. The target coverage (TC, volume receiving 95% of prescribed dose) and homogeneity index (D2-D98, where D2 and D98 are the least doses received by 2% and 98% of the volume) for the internal clinical target volume, and dose indexes for lung, esophagus, heart and spinal cord were compared with that of clinical volumetric modulated arc therapy plans. The TC and homogeneity index for all plans were within clinical limits when considering the breathing motion and interplay effects independently. The setup and range uncertainties had a larger effect when considering their combined effect. The TC decreased to <98% (clinical threshold) in 3 of 10 patients for robust 5-mm evaluations. However, the TC remained >98% for robust 7-mm evaluations for all patients. The organ at risk dose parameters did not significantly vary between the respective robust 5-mm and robust 7-mm evaluations for the 4 error types. Compared with the volumetric modulated arc therapy plans, the IMPT plans showed better target homogeneity and mean lung and heart dose parameters reduced by about 40% and 60%, respectively. In robustly optimized IMPT for stage III NSCLC, the setup and range uncertainties, breathing motion, and interplay effects have limited impact on target coverage, dose homogeneity, and organ-at-risk dose parameters.

WE‐AB‐209‐03: Adaptive SBRT Planning for Interfraction Motion

Purpose:Interfraction changes in abdominal SBRT patient anatomy are challenging to address with image guidance alone because avoidance of an overlapping high‐priority gastrointestinal normal structure may come at the expense of tumor coverage. This work investigates the benefit of anticipating interfraction motion and exploiting favorable geometries at the time of treatment through dose adaptive planning.Methods:Beyond no change, six scenarios of duodenum shifts per fraction are generated (±1 cm XYZ) and sample five‐fraction paths (combinations of no and/or the indicated changes) are simulated. Under the baseline (nominal) plan, generated assuming no uncertainty, three scenarios result in overdosing the duodenum while the others result in safe or reduced dose. The nominal plan under‐doses the PTV (36.1 Gy‐EQD2) due to duodenum proximity. Three adaptive strategies are considered: i) Standard IGRT: for duodenum overdose, patient's isocenter is shifted to satisfy the duodenum dose tolerance; nominal plan is delivered otherwise; ii) Scaling: nominal plan scaled up/down in favorable/unfavorable patient geometries; iii) Mixed: shifting as in i) but boosting otherwise. If max duodenum dose (limit 6 Gy/Fx) is exceeded, dose distributions are shifted or scaled down, depending on the strategy considered. In all adaptive fractions, critical structure dose limits are satisfied, even if the PTVs are under‐dosed.Results:Generally, scaling dose allows better PTV dose (gEUD in Gy‐EQD2); however, in some scenarios, shifting is better than scaling down dose. In a path with 2 fractions of the duodenum not moving and 3 fractions of an unfavorable duodenum position, scaling dose results in the best coverage, with 36.8 Gy‐EQD2. In another path with 2 favorable and 3 unfavorable duodenum positions, the mixed strategy achieves the highest coverage with 41.0 Gy‐EQD2.Conclusions:Anticipating interfraction motion and exploiting favorable geometries through dose adaptive scaling can improve overall tumor coverage by compensating for conservative IGRT in unfavorable fractions.NIH‐P01‐CA059827

TH‐CD‐209‐05: Impact of Spot Size and Spacing On the Quality of Robustly‐Optimized Intensity‐Modulated Proton Therapy Plans for Lung Cancer

Purpose:To investigate how spot size and spacing affect plan quality, especially, plan robustness and the impact of interplay effect, of robustly‐optimized intensity‐modulated proton therapy (IMPT) plans for lung cancer.Methods:Two robustly‐optimized IMPT plans were created for 10 lung cancer patients: (1) one for a proton beam with in‐air energy dependent large spot size at isocenter (σ: 5–15 mm) and spacing (1.53σ); (2) the other for a proton beam with small spot size (σ: 2–6 mm) and spacing (5 mm). Both plans were generated on the average CTs with internal‐gross‐tumor‐volume density overridden to irradiate internal target volume (ITV). The root‐mean‐square‐dose volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under RVH curves were used to evaluate plan robustness. Dose evaluation software was developed to model time‐dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Patient anatomy voxels were mapped from phase to phase via deformable image registration to score doses. Dose‐volume‐histogram indices including ITV coverage, homogeneity, and organs‐at‐risk (OAR) sparing were compared using Student‐t test.Results:Compared to large spots, small spots resulted in significantly better OAR sparing with comparable ITV coverage and homogeneity in the nominal plan. Plan robustness was comparable for ITV and most OARs. With interplay effect considered, significantly better OAR sparing with comparable ITV coverage and homogeneity is observed using smaller spots.Conclusion:Robust optimization with smaller spots significantly improves OAR sparing with comparable plan robustness and similar impact of interplay effect compare to larger spots. Small spot size requires the use of larger number of spots, which gives optimizer more freedom to render a plan more robust. The ratio between spot size and spacing was found to be more relevant to determine plan robustness and the impact of interplay effect than spot size alone.This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant, and by The Kemper Marley Foundation.

SU‐E‐T‐683: Robustness Analysis of Multiple Filed Optimized IMPT Plans for Head &amp; Neck Patients Treated at MD Anderson Cancer Center

Purpose:Our center's clinical outcome data so far indicated that excellent local control for the head and neck patients treated using multiple field optimized (MFO) IMPT technique have been achieved. The purpose is to determine the robustness of those IMPT plans and provide the clinician the knowledge of the degree of the robustness which will not compromise the local control and is safe for the normal tissue.Methods:A fast and approximate dose calculation method is developed to calculate the dose for the IMPT plan under different setup and range uncertainties. The dosimetric index evaluated using this method are compared with those calculated using the dose calculation model in TPS. A worst case scenario robustness analysis method is implemented using the fast dose calculation method. 100 head neck plans treated using MFO IMPT were retrospectively analyzed using implemented robustness analysis method. The lowest dose received by 95% target (D95) and the highest dose received by 5% target (D5) of GTV, CTV1, CTV2, CTV3, mean dose of parotid glands, cochlea and brain and the minimum dose in the most radiated 1 cm3 volume (D1cc) of spinal cord and brain stem were compared between nominal plans and plans in the worst case scenario.Results:For GTV, CTV1 CTV2 and CTV3, D95 in worst scenario are lower by 2.08, 4.59, 5.25 and 5.46 Gy than nominal plan, while D5 are higher by 1.14, 0.98, 0.85 and 1.21 Gy. D1cc of brain stem and spinal in worst scenario are higher by 3.37 and 1.95 Gy than nominal plan. The mean dose of parotid glands, cochlea and brain are higher by 3.52, 3.69 and 0.64 Gy respectively.Conclusion:The robustness analysis data from the clinically treated patients enables the clinician to gauge the degree of robustness in their clinical practice when adopting MFO IMPT technique for patient treatment.

SU‐E‐T‐110: An Investigation On Monitor Unit Threshold and Effects On IMPT Delivery in Proton Pencil Beam Planning System

Purpose:An approved proton pencil beam scanning (PBS) treatment plan might not be able to deliver because of existed extremely low monitor unit per beam spot. A dual hybrid plan with higher efficiency of higher spot monitor unit and the efficacy of less number of energy layers were searched and optimized. The range of monitor unit threshold setting was investigated and the plan quality was evaluated by target dose conformity.Methods:Certain limitations and requirements need to be checks and tested before a nominal proton PBS treatment plan can be delivered. The plan needs to be met the machine characterization, specification in record and verification to deliver the beams. Minimal threshold of monitor unit, e.g. 0.02, per spot was set to filter the low counts and plan was re‐computed. Further MU threshold increment was tested in sequence without sacrificing the plan quality. The number of energy layer was also alternated due to elimination of low count layer(s).Results:Minimal MU/spot threshold, spot spacing in each energy layer and total number of energy layer and the MU weighting of beam spots of each beam were evaluated. Plan optimization between increases of the spot MU (efficiency) and less energy layers of delivery (efficacy) was adjusted. 5% weighting limit of total monitor unit per beam was feasible. Scarce spreading of beam spots was not discouraging as long as target dose conformity within 3% criteria.Conclusion:Each spot size is equivalent to the relative dose in the beam delivery system. The energy layer is associated with the depth of the targeting tumor. Our work is crucial to maintain the best possible quality plan. To keep integrity of all intrinsic elements such as spot size, spot number, layer number and the carried weighting of spots in each layer is important in this study.

SU‐E‐T‐684: Robustness Versus Plan Quality for IMPT

Purpose:Range and set‐up uncertainties in intensity‐modulated proton therapy cannot be addressed with margins. Instead, several robust optimization (RO) models have been developed that explicitly take uncertainty into account. RO optimizes the worst case at the cost of the treatment outcome in more likely scenarios. The goal is to provide insight in the trade‐off between robustness and plan quality and the behavior of different trade‐off methods.Methods:We present four methods to trade‐off robustness with plan quality that can be applied to any of the worst case methods found in literature. Each trade‐off is a mixture between worst case, expected value, and non‐robust planning, which effectively corresponds to assigning different importance weights to error scenarios. Each method is tested on several worst case methods for a sarcoma case, a paraspinal case and a benchmark case from literature.Results:Each trade‐off method yields a unique dose distribution in the border region between target volume and adjacent normal tissues, corresponding to a specific trade‐off between robustness and nominal plan quality. The fully robust solutions perform badly when the realized errors are smaller than the maximum projected errors. Compared to fully robust solutions, significant improvements are possible for non‐extreme scenarios while only slightly deteriorating plan quality at an extreme scenario. It is further observed that trade‐off methods cannot be mimicked by putting different weights on objectives for the tumor and the normal tissue.Conclusion:The method to trade‐off robustness with plan quality should be chosen carefully, as each method has a different impact on plan quality. Two of the methods can directly be implemented in any framework for multicriteria optimization, hopefully leading to their quick dissemination.

SU‐E‐T‐493: Analysis of the Impact of Range and Setup Uncertainties On the Dose to Brain Stem and Whole Brain in the Passively Scattered Proton Therapy Plans

Purpose:To quantify the impact of range and setup uncertainties on various dosimetric indices that are used to assess normal tissue toxicities of patients receiving passive scattering proton beam therapy (PSPBT).Methods:Robust analysis of sample treatment plans of six brain cancer patients treated with PSPBT at our facility for whom the maximum brain stem dose exceeded 5800 CcGE were performed. The DVH of each plan was calculated in an Eclipse treatment planning system (TPS) version 11 applying ±3.5% range uncertainty and ±3 mm shift of the isocenter in x, y and z directions to account for setup uncertainties. Worst‐case dose indices for brain stem and whole brain were compared to their values in the nominal plan to determine the average change in their values. For the brain stem, maximum dose to 1 cc of volume, dose to 10%, 50%, 90% of volume (D10, D50, D90) and volume receiving 6000, 5400, 5000, 4500, 4000 CcGE (V60, V54, V50, V45, V40) were evaluated. For the whole brain, maximum dose to 1 cc of volume, and volume receiving 5400, 5000, 4500, 4000, 3000 CcGE (V54, V50, V45, V40 and V30) were assessed.Results:The average change in the values of these indices in the worst scenario cases from the nominal plan were as follows. Brain stem; Maximum dose to 1 cc of volume: 1.1%, D10: 1.4%, D50: 8.0%, D90:73.3%, V60:116.9%, V54:27.7%, V50: 21.2%, V45:16.2%, V40:13.6%,Whole brain; Maximum dose to 1 cc of volume: 0.3%, V54:11.4%, V50: 13.0%, V45:13.6%, V40:14.1%, V30:13.5%.Conclusion:Large to modest changes in the dosiemtric indices for brain stem and whole brain compared to nominal plan due to range and set up uncertainties were observed. Such potential changes should be taken into account while using any dosimetric parameters for outcome evaluation of patients receiving proton therapy.

SU-E-T-551: PTV Is the Worst-Case of CTV in Photon Therapy

Purpose: To examine the supposition of the static dose cloud and adequacy of the planning target volume (PTV) dose distribution as the worst-case representation of clinical target volume (CTV) dose distribution for photon therapy in head and neck (H&N) plans. Methods: Five diverse H&N plans clinically delivered at our institution were selected. Isocenter for each plan was shifted positively and negatively in the three cardinal directions by a displacement equal to the PTV expansion on the CTV (3 mm) for a total of six shifted plans per original plan. The perturbed plan dose was recalculated in Eclipse (AAA v11.0.30) using the same, fixed fluence map as the original plan. The dose distributions for all plans were exported from the treatment planning system to determine the worst-case CTV dose distributions for each nominal plan. Two worst-case distributions, cold and hot, were defined by selecting the minimum or maximum dose per voxel from all the perturbed plans. The resulting dose volume histograms (DVH) were examined to evaluate the worst-case CTV and nominal PTV dose distributions. Results: Inspection demonstrates that the CTV DVH in the nominal dose distribution is indeed bounded by the CTV DVHs in the worst-case dose distributions. Furthermore, comparison of the D95% for the worst-case (cold) CTV and nominal PTV distributions by Pearson's chi-square test shows excellent agreement for all plans. Conclusion: The assumption that the nominal dose distribution for PTV represents the worst-case dose distribution for CTV appears valid for the five plans under examination. Although the worst-case dose distributions are unphysical since the dose per voxel is chosen independently, the cold worst-case distribution serves as a lower bound for the worst-case possible CTV coverage. Minor discrepancies between the nominal PTV dose distribution and worst-case CTV dose distribution are expected since the dose cloud is not strictly static. This research was supported by the NCI through grant K25CA168984, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, and by the Fraternal Order of Eagles Cancer Research Fund, the Career Development Award Program at Mayo Clinic.

The INTErnational Gamma Ray Astrophysics Laboratory: INTEGRAL Highlights

The INTEGRAL Space Observatory was selected as the second Medium size mission (M2) of the ESAs Horizon 2000 vision programme. INTEGRAL is the first high angular and spectral resolution hard X-ray and soft γ-ray observatory with a wide band spectral response ranging from 3keV up to 10MeV energy band. This capability is supplemented by an unprecedented sensitivity enhanced by the 3 days orbit allowing long and uninterrupted observations over very wide field of view (up to ~1000 squared degrees to zero response) and sub-ms time resolution. Part of the observatory success is due to its capability to link the high energy sky with the lower energy band. The complementarity and synergy with pointing soft X-ray missions such as XMM-Newton and CHANDRA and more recently with NuSTAR is a strategic feature to link the “thermal” and the “non-thermal” Universe observed at higher energies by space missions such as Fermi and AGILE and ground based TeV observatories sensitive to extremely high energies.INTEGRAL was launched on 17 October 2002 from the Baikonur Cosmodrome (Kazakistan) aboard a Proton rocket as part of the Russian contribution to the mission, and has successfully spent almost 11 years in orbit. In view of its successful science outcome the ESA Space Programme Committee haw recently approved its scientific operation till the end of 2016.To date the spacecraft, ground segment and scientific payload are in excellent state-of-health, and INTEGRAL is continuing its scientific operations, originally planned for a 5-year technical design and scientific nominal operation plan. This paper summarizes the current INTEGRAL scientific achievements and future prospects, with particular regard to the high energy domain.

Preliminary evaluation of multifield and single-field optimization for the treatment planning of spot-scanning proton therapy of head and neck cancer

Spot-scanning proton therapy (SSPT) using multifield optimization (MFO) can generate highly conformal dose distributions, but it is more sensitive to setup and range uncertainties than SSPT using single-field optimization (SFO). The authors compared the two optimization methods for the treatment of head and neck cancer with bilateral targets and determined the superior method on the basis of both the plan quality and the plan robustness in the face of setup and range uncertainties. Four patients with head and neck cancer with bilateral targets who received SSPT treatment in the authors' institution were studied. The patients had each been treated with a MFO plan using three fields. A three-field SFO plan (3F-SFO) and a two-field SFO plan (2F-SFO) with the use of a range shifter in the beam line were retrospectively generated for each patient. The authors compared the plan quality and robustness to uncertainties of the SFO plans with the MFO plans. Robustness analysis of each plan was performed to generate the two dose distributions consisting of the highest and the lowest possible doses (worst-case doses) from the spatial and range perturbations at every voxel. Dosimetric indices from the nominal and worst-case plans were compared. The 3F-SFO plans generally yielded D95 and D5 values in the targets that were similar to those of the MFO plans. 3F-SFO resulted in a lower dose to the oral cavity than MFO in all four patients by an average of 9.9 Gy, but the dose to the two parotids was on average 6.7 Gy higher for 3F-SFO than for MFO. 3F-SFO plans reduced the variations of dosimetric indices under uncertainties in the targets by 22.8% compared to the MFO plans. Variations of dosimetric indices under uncertainties in the organs at risk (OARs) varied between organs and between patients, although they were on average 9.2% less for the 3F-SFO plans than for the MFO plans. Compared with the MFO plans, the 2F-SFO plans showed a reduced dose to the parotids for both the nominal dose and in the worst-case scenario, but the plan robustness in the target of the 2F-SFO plans was not notably greater than that of the MFO plans. Compared with MFO, 3F-SFO improves plan robustness in the targets but degrades dose sparing in the parotids in both the nominal and worst-case scenarios. Although 2F-SFO improves parotid sparing compared with MFO, it produces little improvement in plan robustness. Therefore, considering its tolerable target coverage and sparing of OARs in worst-case scenarios, the authors recommend MFO as the planning method for the treatment of head and neck cancer with bilateral targets.

SU‐E‐T‐589: A Robust 4D Treatment Planning Approach for Lung Radiotherapy

Purpose: 4D treatment planning optimizes the cumulative dose delivered over the whole respiratory cycle to generate a plan that compensates for a patients individual respiratory motion. However, changes in the time spent in the each respiratory state may render a 4D plan invalid. We introduced and evaluate two robust treatment planning approaches to compensate for respiratory motion. Methods: A 4D optimization method was developed which optimizes the phase‐weighted dose distribution. Two robust 4D treatment planning approaches were tested: (1) planning on the average motion pdf (AVE_PDF); and (2) combining 4D plans designed on the “worst case” pdfs (WC_PDF). The sensitivity of nominal and robust 4D treatment plans to respiratory motion variations was tested for two scenarios where respiratory phase weights were modified to model changes in amplitude as well as the relative proportion of the respiratory cycle spent inhaling vs. exhaling. Results: The DVHs of robust plans show less sensitivity to variation in breathing pattern. Compared to the nominal 4D plan, robust plans improve the V95 by 2 to 6 Gy and CTV min dose by 1 to 5 Gy. Conclusion: Robust 4D plan can be designed either using average pdf approach or worst case pdf approach. We find that nominal 4D plans are very sensitive to the variation in respiration pattern while robust 4D plans are less sensitive under the similar changes. As compared to static 4D plan, healthy tissue sparing is also better in robust plan. This research is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).

SU‐E‐T‐444: A Comparison of Single‐Field Vs Multi‐Field Delivery Uncertainty in Proton Therapy

Purpose: To evaluate of the impact of uncertainty on proton plan delivery when one field per fraction treatment regimes (SFPF) are used rather than delivering all planned fields for every fraction (MFPF). Methods: A nominal proton treatment plan (NP) was created in Eclipse (Varian) to treat a spherical target to 54Gy using parallel‐opposed fields. The fields created in the NP were applied to geometries with uncertainties introduced. Uncertainty was simulated for four scenarios: a 1cm shift in one of the fields for 10 of 30 fractions, a 5° rotation of the patient for 10 of 30 fractions, and unilateral introduction of 3cm of bone or air for 10 of 30 fractions. The full treatment was calculated using summed plans for the SFPF case is delivered and the MFPF case. The results of the SFPF and MFPF plan sums were compared to each other and the NP by calculating Dmax/min/mean along with V90,95,98,99,100%. Dmax/min/mean were also compared for an OAR placed contralateral to the introduced uncertainty. Results: The cases for 5° rotations introduced, showed no significant difference from the NP. In all other cases, the introduced uncertainty degraded the treatment delivery with the most significant difference in the target Dmin. The SFPF treatments consistently showed a decrease in Dmin compared to the MFPF treatment. For the introduction of air and bone the SFPF treatments exhibit increases of 1.5% and 20% respectively. With bone introduced, V95 and V90 suffered an additional 3% and 4% for SFPF treatments. With air introduced, dose to the Dmax, Dmin, and Dmean were increased by 14, 16, and 20% respectively for SFPF treatments. Conclusion: Tumor response and minimum target dose can be correlated. In the presence of uncertainty, SFPF treatment regimes may Result in a decreased tumor response and increased OAR dose.

WE-G-BRCD-03: Improvement in Robustness and Delivery Efficiency of Intensity-Modulated Proton Therapy Using Single-Field Optimization with Energy Absorber.

Intensity-modulated proton therapy (IMPT) using multi-field optimization (MFO) could generate highly conformal dose distributions but it is more sensitive to setup and proton range uncertainties than IMPT using single-field optimization (SFO). This work evaluates the effectiveness of SFO treatment plans with the use of energy absorbers (EAs) to improve the robustness and delivery efficiency of IMPT for head and neck cancers. IMPT treatment plans were generated using 2-field SFO with an EA in each field (EA-SFO) for four patients with head and neck cancers. We compared the plan quality, robustness, and delivery efficiency of the EA- SFO plan with a 3-field MFO plan that was used to treat the patient. Robustness analysis of each plan was performed to generate two dose distributions, consisting of the highest and the lowest possible doses from spatial and range perturbations at every voxel. Dosimetric indices and the numbers of energy layers required in the EA-SFO and MFO plans were compared. All the nominal EA-SFO plans are clinically acceptable. They achieved similar levels of target coverage compared to the MFO plans; the differences in D95 of the GTV and CTVs between the two plans were within 3.5%. Although some of the OARs received higher dose in the EA- SFO plan, they were all within tolerance. The EA-SFO plans yielded an average of 38.5% reduction of plan sensitivity to uncertainties in the targets and 18.5% overall. The EA-SFO plans used an average of 79 (46%) fewer energy layers than the MFO plans, which corresponds to nearly 3 minutes shorter delivery time. The use of energy absorber greatly facilitated the design of clinically acceptable SFO treatment plans. Compared to MFO, EA-SFO not only improved the robustness to setup and range uncertainties, but also reduced the time required for delivery and patient QA.

SU-E-T-616: Efficacy of Biological Dose Painting for Head and Neck Cancer.

Study the feasibility and planning robustness of a novel biological dose painting approach prescribing biological effect instead of dose. Prescribed'effect maps' were generated using models relating FMISO-PET tracer uptake to hypoxia reduction factors (HRF). HRFs decrease the LQ-model radio response parameters a and β and therefore the delivered biological effect. The model is driven by four parameters (m, K, p50, Imax), whose values have been determined through a comprehensive literature search. A planning study on ten previously treated patients with oropharyngeal cancer was conducted. Dose-painted plans were generated with the KonRad inverse planning system (DKFZ, Heidelberg). Simulated FMISO-PET images were generated by defining clinically relevant hypoxic sub-volumes within the GTV. Tracer uptake values were derived from various PET imaging studies for head and neck cancer. Each treatment plan was developed in four steps: 1) Simulate hypoxia tracer distribution in GTV. 2) Prescribe biological effect. 3) Optimize dose-painted plan under the same normal tissue constraints of the nominal clinical plan. 4) Conduct robustness analysis by evaluation of the dose-painted plan for 27 parameters combinations of K, m, p50 (mean ± 1SD). The predicted biological effect of clinical plans under normoxic conditions overestimates the delivered effect due to decreased radio-sensitivity in hypoxic tumours. Biological dose painting compensates for hypoxia by delivering a higher dose to hypoxic sub-volumes while still maintaining all critical structure dose limits. Model parameter uncertainties clearly affect robustness. The high uncertainty on p50 (pO2 for which tracer concentration is half of maximum uptake) was found to cause the largest variations in the delivered biological effect. Clinically acceptable dose-painted plans can be generated without sacrificing the normal tissue constraints. Planning robustness suffers from the high uncertainty on the p50 value. Improved methods to determine the model parameters would be desirable. Financial support provided by Ryerson University, Toronto, Ontario, Canada.

TH‐A‐213AB‐08: Robust Multi‐Criteria IMPT Optimization

Purpose: We present a method to include robustness in a multi‐criteria optimization (MCO) framework for intensity‐modulated proton therapy (IMPT). The approach allows one to simultaneously explore the trade‐off between different objectives including robustness and nominal plan quality. Methods: A database of plans each emphasizing different treatment planning objectives, is pre‐computed to approximate the Pareto surface. An IMPT treatment plan that strikes the best balance between the different objectives can be selected by navigating on the Pareto surface. We integrate robustness into MCO by adding robustified objectives and constraints. Uncertainties are modeled by pre‐calculated dose‐influence matrices for a nominal scenario and a number of pre‐defined error scenarios (shifted patient positions, proton beam undershoot and overshoot). A robustified objective represents the worst objective function value that can be realized for any of the error scenarios and thus provides a measure of plan robustness. The optimization method uses a linear projection solver and is capable of handling large problem sizes resulting from a fine dose grid resolution, many scenarios, and a large number of proton pencil beams. Results: A base‐of‐skull case is used to demonstrate that the robust optimization method reduces the sensitivity of the treatment plan to setup and range errors to a degree that is not achieved by a safety margin approach. A chordoma case is analyzed in more detail to demonstrate the involved trade‐offs between target underdose and brainstem sparing as well as robustness and nominal plan quality. The robust optimization for each Pareto optimal plan takes less than 5 min on a standard computer. Conclusions: The uncertainty pertinent to the IMPT procedure can be reduced during treatment planning by optimizing a database of plans that emphasize different treatment objectives, including robustness. The planner can then interactively explore all convex combinations of database plans to decide on the most‐preferred trade‐off.

Including robustness in multi-criteria optimization for intensity-modulated proton therapy

We present a method to include robustness in a multi-criteria optimization (MCO) framework for intensity-modulated proton therapy (IMPT). The approach allows one to simultaneously explore the trade-off between different objectives as well as the trade-off between robustness and nominal plan quality. In MCO, a database of plans each emphasizing different treatment planning objectives, is pre-computed to approximate the Pareto surface. An IMPT treatment plan that strikes the best balance between the different objectives can be selected by navigating on the Pareto surface. In our approach, robustness is integrated into MCO by adding robustified objectives and constraints to the MCO problem. Uncertainties (or errors) of the robust problem are modeled by pre-calculated dose-influence matrices for a nominal scenario and a number of pre-defined error scenarios (shifted patient positions, proton beam undershoot and overshoot). Objectives and constraints can be defined for the nominal scenario, thus characterizing nominal plan quality. A robustified objective represents the worst objective function value that can be realized for any of the error scenarios and thus provides a measure of plan robustness. The optimization method is based on a linear projection solver and is capable of handling large problem sizes resulting from a fine dose grid resolution, many scenarios, and a large number of proton pencil beams. A base-of-skull case is used to demonstrate the robust optimization method. It is demonstrated that the robust optimization method reduces the sensitivity of the treatment plan to setup and range errors to a degree that is not achieved by a safety margin approach. A chordoma case is analyzed in more detail to demonstrate the involved trade-offs between target underdose and brainstem sparing as well as robustness and nominal plan quality. The latter illustrates the advantage of MCO in the context of robust planning. For all cases examined, the robust optimization for each Pareto optimal plan takes less than 5 min on a standard computer, making a computationally friendly interface possible to the planner. In conclusion, the uncertainty pertinent to the IMPT procedure can be reduced during treatment planning by optimizing plans that emphasize different treatment objectives, including robustness, and then interactively seeking for a most-preferred one from the solution Pareto surface.