Adaptive Intensity Modulated Proton Therapy Research Articles

Adaptive intensity modulated proton therapy using 4D robust planning: a proof-of-concept for the application of dose mimicking approach

Objective.A four-dimensional robust optimisation (4DRO) is usually employed when the tumour respiratory motion needs to be addressed. However, it is computationally demanding, and an automated method is preferable for adaptive planning to avoid manual trial-and-error. This study proposes a 4DRO technique based on dose mimicking for automated adaptive planning.Approach.Initial plans for 4DRO intensity modulated proton therapy were created on an average CT for four patients with clinical target volume (CTV) in the lung, oesophagus, or pancreas, respectively. These plans were robustly optimised using three phases of four-dimensional computed tomography (4DCT) and accounting for setup and density uncertainties. Weekly 4DCTs were used for adaptive replanning, using a constant relative biological effectiveness (cRBE) of 1.1. Two methods were used: (1) template-based adaptive (TA) planning and (2) dose-mimicking-based adaptive (MA) planning. The plans were evaluated using variable RBE (vRBE) weighted doses and biologically consistent dose accumulation (BCDA).Main results.MA and TA plans had comparable CTV coverage except for one patient where the MA plan had a higher D98 and lower D2 but with an increased D2 in few organs at risk (OARs). CTV D98 deviations in non-adaptive plans from the initial plans were up to -7.2 percentage points (p.p.) in individual cases and -1.8 p.p. when using BCDA. For the OARs, MA plans showed a reduced mean dose and D2 compared to the TA plans, with few exceptions. The vRBE-weighted accumulated doses had a mean dose and D2 difference of up to 0.3 Gy and 0.5 Gy, respectively, in the OARs with respect to cRBE-weighted doses.Significance.MA plans indicate better performance in target coverage and OAR dose sparing compared to the TA plans in 4DRO adaptive planning. Moreover, MA method is capable of handling both forms of anatomical variation, namely, changes in density and relative shifts in the position of OARs.

A fast and robust constraint-based online re-optimization approach for automated online adaptive intensity modulated proton therapy in head and neck cancer

Objective. In head-and-neck cancer intensity modulated proton therapy, adaptive radiotherapy is currently restricted to offline re-planning, mitigating the effect of slow changes in patient anatomies. Daily online adaptations can potentially improve dosimetry. Here, a new, fully automated online re-optimization strategy is presented. In a retrospective study, this online re-optimization approach was compared to our trigger-based offline re-planning (offlineTB re-planning) schedule, including extensive robustness analyses. Approach. The online re-optimization method employs automated multi-criterial re-optimization, using robust optimization with 1 mm setup-robustness settings (in contrast to 3 mm for offlineTB re-planning). Hard planning constraints and spot addition are used to enforce adequate target coverage, avoid prohibitively large maximum doses and minimize organ-at-risk doses. For 67 repeat-CTs from 15 patients, fraction doses of the two strategies were compared for the CTVs and organs-at-risk. Per repeat-CT, 10.000 fractions with different setup and range robustness settings were simulated using polynomial chaos expansion for fast and accurate dose calculations. Main results. For 14/67 repeat-CTs, offlineTB re-planning resulted in <50% probability of D 98% ≥ 95% of the prescribed dose (D pres) in one or both CTVs, which never happened with online re-optimization. With offlineTB re-planning, eight repeat-CTs had zero probability of obtaining D 98% ≥ 95%D pres for CTV7000, while the minimum probability with online re-optimization was 81%. Risks of xerostomia and dysphagia grade ≥ II were reduced by 3.5 ± 1.7 and 3.9 ± 2.8 percentage point [mean ± SD] (p < 10−5 for both). In online re-optimization, adjustment of spot configuration followed by spot-intensity re-optimization took 3.4 min on average. Significance. The fast online re-optimization strategy always prevented substantial losses of target coverage caused by day-to-day anatomical variations, as opposed to the clinical trigger-based offline re-planning schedule. On top of this, online re-optimization could be performed with smaller setup robustness settings, contributing to improved organs-at-risk sparing.

Cone beam CT-based adaptive intensity modulated proton therapy assessment using automated planning for head-and-neck cancer

BackgroundTo assess the feasibility of CBCT-based adaptive intensity modulated proton therapy (IMPT) using automated planning for treatment of head and neck (HN) cancers.MethodsTwenty HN cancer patients who received radiotherapy and had pretreatment CBCTs were included in this study. Initial IMPT plans were created using automated planning software for all patients. Synthetic CTs (sCT) were then created by deforming the planning CT (pCT) to the pretreatment CBCTs. To assess dose calculation accuracy on sCTs, repeat CTs (rCTs) were deformed to the pretreatment CBCT obtained on the same day to create deformed rCT (rCTdef), serving as gold standard. The dose recalculated on sCT and on rCTdef were compared by using Gamma analysis. The accuracy of DIR generated contours was also assessed. To explore the potential benefits of adaptive IMPT, two sets of plans were created for each patient, a non-adapted IMPT plan and an adapted IMPT plan calculated on weekly sCT images. The weekly doses for non-adaptive and adaptive IMPT plans were accumulated on the pCT, and the accumulated dosimetric parameters of two sets were compared.ResultsGamma analysis of the dose recalculated on sCT and rCTdef resulted in a passing rate of 97.9% ± 1.7% using 3 mm/3% criteria. With the physician-corrected contours on the sCT, the dose deviation range of using sCT to estimate mean dose for the most organ at risk (OARs) can be reduced to (− 2.37%, 2.19%) as compared to rCTdef, while for V95 of primary or secondary CTVs, the deviation can be controlled within (− 1.09%, 0.29%). Comparison of the accumulated doses from the adaptive planning against the non-adaptive plans reduced mean dose to constrictors (− 1.42 Gy ± 2.79 Gy) and larynx (− 2.58 Gy ± 3.09 Gy). The reductions result in statistically significant reductions in the normal tissue complication probability (NTCP) of larynx edema by 7.52% ± 13.59%. 4.5% of primary CTVs, 4.1% of secondary CTVs, and 26.8% tertiary CTVs didn’t meet the V95 > 95% constraint on non-adapted IMPT plans. All adaptive plans were able to meet the coverage constraint.ConclusionsCTs can be a useful tool for accurate proton dose calculation. Adaptive IMPT resulted in better CTV coverage, OAR sparing and lower NTCP for some OARs as compared with non-adaptive IMPT.

Comparison of MR-guided radiotherapy accumulated doses for central lung tumors with non-adaptive and online adaptive proton therapy.

Stereotactic body radiation therapy (SBRT) of central lung tumors with photon or proton therapy has a risk of increased toxicity. Treatment planning studies comparing accumulated doses for state-of-the-art treatment techniques, such as MR-guided radiotherapy (MRgRT) and intensity modulated proton therapy (IMPT), are currently lacking. We conducted a comparison of accumulated doses for MRgRT, robustly optimized non-adaptive IMPT, and online adaptive IMPT for central lung tumors. A special focus was set on analyzing the accumulated doses to the bronchial tree, a parameter linked to high-grade toxicities. Data of 18 early-stage central lung tumor patients, treated at a 0.35T MR-linac in eight or five fractions, were analyzed. Three gated treatment scenarios were compared: (S1) online adaptive MRgRT, (S2) non-adaptive IMPT, and (S3) online adaptive IMPT. The treatment plans were recalculated or reoptimized on the daily imaging data acquired during MRgRT, and accumulated over all treatment fractions. Accumulated dose-volume histogram (DVH) parameters of the gross tumor volume (GTV), lung, heart, and organs-at-risk (OARs) within 2cm of the planning target volume (PTV) were extracted for each scenario and compared in Wilcoxon signed-rank tests between S1 & S2, and S1 & S3. The accumulated GTV D98% was above the prescribed dose for all patients and scenarios. Significant reductions (p < 0.05) of the mean ipsilateral lung dose (S2: -8%; S3: -23%) and mean heart dose (S2: -79%; S3: -83%) were observed for both proton scenarios compared to S1. The bronchial tree D0.1cc was significantly lower for S3 (S1: 48.1 Gy; S3: 39.2 Gy; p = 0.005), but not significantly different for S2 (S2: 45.0 Gy; p = 0.094), compared to S1. The D0.1cc for S2 and S3 compared to S1 was significantly (p < 0.05) smaller for OARs within 1-2cm of the PTV (S1: 30.2 Gy; S2: 24.6 Gy; S3: 23.1 Gy), but not significantlydifferent for OARs within 1cm of the PTV. A significant dose sparing potential of non-adaptive and online adaptive proton therapy compared to MRgRT for OARs in close, but not direct proximity of central lung tumors was identified. The near-maximum dose to the bronchial tree was not significantly different for MRgRT and non-adaptive IMPT. Online adaptive IMPT achieved significantly lower doses to the bronchial tree compared to MRgRT.

Improving workflow for adaptive proton therapy with predictive anatomical modelling: A proof of concept

PurposeTo demonstrate predictive anatomical modelling for improving the clinical workflow of adaptive intensity-modulated proton therapy (IMPT) for head and neck cancer. Methods10 radiotherapy patients with nasopharyngeal cancer were included in this retrospective study. Each patient had a planning CT, weekly verification CTs during radiotherapy and predicted weekly CTs from our anatomical model. Predicted CTs were used to create predicted adaptive plans in advance with the aim of maintaining clinically acceptable dosimetry. Adaption was triggered when the increase in mean dose (Dmean) to the parotid glands exceeded 3 Gy(RBE). We compared the accumulated dose of two adaptive IMPT strategies: 1) Predicted plan adaption: One adaptive plan per patient was optimised on a predicted CT triggered by replan criteria. 2) Standard replan: One adaptive plan was created reactively in response to the triggering weekly CT. ResultsStatistical analysis demonstrates that the accumulated dose differences between two adaptive strategies are not significant (p > 0.05) for CTVs and OARs. We observed no meaningful differences in D95 between the accumulated dose and the planned dose for the CTVs, with mean differences to the high-risk CTV of −1.20 %, −1.23 % and −1.25 % for no adaption, standard and predicted plan adaption, respectively. The accumulated parotid Dmean using predicted plan adaption is within 3 Gy(RBE) of the planned dose and 0.31 Gy(RBE) lower than the standard replan approach on average. ConclusionPrediction-based replanning could potentially enable adaptive therapy to be delivered without treatment gaps or sub-optimal fractions, as can occur during a standard replanning strategy, though the benefit of using predicted plan adaption over the standard replan was not shown to be statistically significant with respect to accumulated dose in this study. Nonetheless, a predictive replan approach can offer advantages in improving clinical workflow efficiency.

First Application of Predictive Model to Assist Adaptive Proton Therapy

<h3>Purpose/Objective(s)</h3> To assess a model to predict anatomical changes in head and neck cancer patients and explore the applicability of the model as a tool for adaptive replanning in intensity-modulated proton therapy (IMPT). <h3>Materials/Methods</h3> 20 radiotherapy patients with nasopharyngeal cancer were included in this retrospective study. Each patient had a planning CT and weekly CTs during radiotherapy. To build the anatomical model, we deform the weekly CTs to planning CTs of our training population (n = 19) and obtain the average anatomical change per week. To predict a deformation for the remaining patient, the average deformation of the training population is applied to the patient's planning CT. The model is updated based on the patient's progression during treatment. K-fold cross validation (n = 5) was used to obtain a sample of 5 patients. For those 5 patients, we compare the accumulated dose of two adaptive IMPT strategies. 1) Predictive replan (PR): Replans were optimized on predicted images of weeks 3 and 5 and applied to week 3/4 and week 5/6 respectively. 2) Best-case replan (BcR): Adaptive replan on weekly CT is triggered when target coverage D95% criteria are not met and parotid gland mean dose deviation > 3 Gy (RBE). All plans (original plan, PR, BcR) were robustly optimized (+/-3 mm setup and +/-3.5% range uncertainty). Dosimetric goals: CTV D95(%) > 95% prescription dose in robust evaluation; maximum dose to spinal cord and brainstem < 45 Gy (RBE) and < 55 Gy (RBE), respectively. To ensure fairness of comparison, we kept dosimetric parameters between BcR and PR consistent. <h3>Results</h3> Accumulated dose differences from two adaptive strategies (PR-BcR) of our 5 testing patients are shown (tab 1). We observe a maximum dose difference of 2.2% in the CTV D₉₅, -1.35 Gy (RBE) in the brainstem D_max, and -1.24 Gy (RBE) in the parotid D_mean. The parentheses indicate the dose difference of the replans only (no accumulation). <h3>Conclusion</h3> A predictive model was applied to the replanning process for adaptive proton therapy and compared to a best-case replan strategy. Our suggested PR produces clinically acceptable plans, comparable to the best-case replan strategy, suggesting that the predictive models can be used for adaptive replanning. Application of predictive replanning provides the possibility to prepare adaptive plans in advance, streamlining the clinical workflow.

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

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

Evaluation of an Open Source Registration Package for Automatic Contour Propagation in Online Adaptive Intensity-Modulated Proton Therapy of Prostate Cancer.

Objective: Our goal was to investigate the performance of an open source deformable image registration package, elastix, for fast and robust contour propagation in the context of online-adaptive intensity-modulated proton therapy (IMPT) for prostate cancer.Methods: A planning and 7–10 repeat CT scans were available of 18 prostate cancer patients. Automatic contour propagation of repeat CT scans was performed using elastix and compared with manual delineations in terms of geometric accuracy and runtime. Dosimetric accuracy was quantified by generating IMPT plans using the propagated contours expanded with a 2 mm (prostate) and 3.5 mm margin (seminal vesicles and lymph nodes) and calculating dosimetric coverage based on the manual delineation. A coverage of V95% ≥ 98% (at least 98% of the target volumes receive at least 95% of the prescribed dose) was considered clinically acceptable.Results: Contour propagation runtime varied between 3 and 30 s for different registration settings. For the fastest setting, 83 in 93 (89.2%), 73 in 93 (78.5%), and 91 in 93 (97.9%) registrations yielded clinically acceptable dosimetric coverage of the prostate, seminal vesicles, and lymph nodes, respectively. For the prostate, seminal vesicles, and lymph nodes the Dice Similarity Coefficient (DSC) was 0.87 ± 0.05, 0.63 ± 0.18, and 0.89 ± 0.03 and the mean surface distance (MSD) was 1.4 ± 0.5 mm, 2.0 ± 1.2 mm, and 1.5 ± 0.4 mm, respectively.Conclusion: With a dosimetric success rate of 78.5–97.9%, this software may facilitate online adaptive IMPT of prostate cancer using a fast, free and open implementation.

Plan Selection in Proton Therapy of Locally Advanced Prostate Cancer with Simultaneous Treatment of Multiple Targets

Intensity modulated proton therapy (IMPT) of locally advanced prostate cancer can spare the bowel considerably compared with modern photon therapy, but simultaneous treatment of the prostate (p), seminal vesicles (sv), and lymph nodes is challenging owing to day-to-day organ motion and range uncertainties. Our purpose was, therefore, to generate a plan library for use in adaptive IMPT to mitigate these uncertainties. We retrospectively included 27 patients with a series of computed tomography scans throughout their treatment representing day-to-day variation. In 18 of the patients, target motion was analyzed using rigid shifts of prostate gold markers relative to bony anatomy. A plan library with different p and sv planning target volume (p/sv-PTV) positions was defined from the distribution and direction of these shifts. Delivery of IMPT using plan selection from the library was simulated for image guidance on bony anatomy, in the remaining patients and compared with nonadaptive IMPT. The plan library consisted of 3 small margin p/sv-PTVs: (1) p/sv-PTV shifted 1.5 systematic error (Σ) of the population mean in the anterior and cranial directions, (2) p/sv-PTV shifted 1.5Σ in the posterior and caudal directions, and (3) p/sv-PTV in the planning position. The conventional p/sv-PTV was also available for backup. Plan selection compared with nonadaptive IMPT resulted in a reduction of the rectum volume receiving 60 Gy relative biological effect (RBE) (V60GyRBE) from on average 12 mL to 9 mL. For the bladder the average V45GyRBE was reduced from 36% to 30%. Large and small bowel doses were also reduced, whereas target coverage was comparable or improved compared with nonadaptive IMPT. Plan selection based on a population model of rigid target motion was feasible for all patients. Compared with conventional IMPT, plan selection resulted in significant dosimetric sparing of rectum and bladder without compromising target coverage.

Organ sparing potential and inter-fraction robustness of adaptive intensity modulated proton therapy for lung cancer

Background: The aim of this study was to compare adaptive intensity modulated proton therapy (IMPT) robustness and organ sparing capabilities with that of adaptive volumetric arc photon therapy (VMAT).Material and methods: Eighteen lung cancer patients underwent a planning 4DCT (p4DCT) and 5 weekly repeated 4DCT (r4DCT) scans. Target volumes and organs at risk were manually delineated on the three-dimensional (3D) average scans of the p4DCT (av_p4DCT) and of the r4DCT scans (av_r4DCT). Planning target volume (PTV)-based VMAT plans and internal clinical target volume (ICTV)-based robust IMPT plans were optimized in 3D on the av_p4DCT and re-calculated on the av_r4DCTs. Re-planning on av_r4DCTs was performed when indicated and accumulated doses were evaluated on the av_p4DCT.Results: Adaptive VMAT and IMPT resulted in adequate ICTV coverage on av_r4DCT in all patients and adequate accumulated-dose ICTV coverage on av_p4DCT in 17/18 patients (due to a shrinking target in one patient). More frequent re-planning was needed for IMPT than for VMAT. The average mean heart dose reduction with IMPT compared with VMAT was 4.6 Gy (p = .001) and it was >5 Gy for five patients (6, 7, 8, 15, and 22 Gy). The average mean lung dose reduction was 3.2 Gy (p < .001). Significant reductions in heart and lung V5 Gy were observed with IMPT.Conclusion: Robust-planned IMPT required re-planning more often than VMAT but resulted in similar accumulated ICTV coverage. With IMPT, heart and lung mean dose values and low dose regions were significantly reduced. Substantial cardiac sparing was obtained in a subgroup of five patients (28%).

The Potential Benefit of Adaptive Intensity Modulated Proton Therapy in Nasopharyngeal Carcinoma: Planning Comparison Study

The Potential Benefit of Adaptive Intensity Modulated Proton Therapy in Nasopharyngeal Carcinoma: Planning Comparison Study

Multiple-CT optimization of intensity-modulated proton therapy – Is it possible to eliminate adaptive planning?

Background and purposeWe hypothesized that a plan’s robustness to anatomical changes can be improved by optimizing with multiple CT scans of a patient. The purpose of this study was to determine whether an intensity modulated proton therapy (IMPT) plan could be developed to meet dose criteria on both planning and adaptive CT plans. Material and methodsEight lung cancer patients who underwent adaptive IMPT were retrospectively selected. Each patient had two CTs: a primary planning CT (PCT) and an adaptive planning CT (ACT), and IMPT plans associated with the scans. PCT and ACT were then used in combination to optimize one plan (MCT plan). The doses to the target and organs at risk from the PCT plan, ACT plan, P-ACT plan (PCT plan calculated on ACT data), and MCT plans calculated on both CTs were compared. ResultsThe MCT plan maintained the D95% on both CTs (mean, 65.99 Gy on PCT and 66.02 Gy on ACT). Target dose coverage on ACT was significantly better with the MCT plan than with the P-ACT plan (p = 0.01). MCT plans had slightly higher lung V20 (0.6%, p = 0.02) than did PCT plans. The various plans showed no statistically significant difference in heart and spinal cord dose. ConclusionsThe results of this study indicate that an IMPT plan can meet the dose criteria on both PCT and ACT, and that MCT optimization can improve the plan’s robustness to anatomical change.

Investigating deformable image registration and scatter correction for CBCT‐based dose calculation in adaptive IMPT

This work aims at investigating intensity corrected cone-beam x-ray computed tomography (CBCT) images for accurate dose calculation in adaptive intensity modulated proton therapy (IMPT) for prostate and head and neck (H&N) cancer. A deformable image registration (DIR)-based method and a scatter correction approach using the image data obtained from DIR as prior are characterized and compared on the basis of the same clinical patient cohort for the first time. Planning CT (pCT) and daily CBCT data (reconstructed images and measured projections) of four H&N and four prostate cancer patients have been considered in this study. A previously validated Morphons algorithm was used for DIR of the planning CT to the current CBCT image, yielding a so-called virtual CT (vCT). For the first time, this approach was translated from H&N to prostate cancer cases in the scope of proton therapy. The warped pCT images were also used as prior for scatter correction of the CBCT projections for both tumor sites. Single field uniform dose and IMPT (only for H&N cases) treatment plans have been generated with a research version of a commercial planning system. Dose calculations on vCT and scatter corrected CBCT (CBCTcor) were compared by means of the proton range and a gamma-index analysis. For the H&N cases, an additional diagnostic replanning CT (rpCT) acquired within three days of the CBCT served as additional reference. For the prostate patients, a comprehensive contour comparison of CBCT and vCT, using a trained physician's delineation, was performed. A high agreement of vCT and CBCTcor was found in terms of the proton range and gamma-index analysis. For all patients and indications between 95% and 100% of the proton dose profiles in beam's eye view showed a range agreement of better than 3 mm. The pass rate in a (2%,2 mm) gamma-comparison was between 96% and 100%. For H&N patients, an equivalent agreement of vCT and CBCTcor to the reference rpCT was observed. However, for the prostate cases, an insufficient accuracy of the vCT contours retrieved from DIR was found, while the CBCTcor contours showed very high agreement to the contours delineated on the raw CBCT. For H&N patients, no considerable differences of vCT and CBCTcor were found. For prostate cases, despite the high dosimetric agreement, the DIR yields incorrect contours, probably due to the more pronounced anatomical changes in the abdomen and the reduced soft-tissue contrast in the CBCT. Using the vCT as prior, these inaccuracies can be overcome and images suitable for accurate delineation and dose calculation in CBCT-based adaptive IMPT can be retrieved from scatter correction of the CBCT projections.

SU-G-TeP1-06: Fast GPU Framework for Four-Dimensional Monte Carlo in Adaptive Intensity Modulated Proton Therapy (IMPT) for Mobile Tumors

Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) treatment planning and verification using four-dimensional CT (4DCT) for adaptive IMPT for lung cancer patients. Methods: A validated GPU MC code, gPMC, has been linked to the patient database at our institution and employed to compute the dose-influence matrices (Dij) on the planning CT (pCT). The pCT is an average of the respiratory motion of the patient. The Dijs and patient structures were fed to the optimizer to calculate a treatment plan. To validate the plan against motion, a 4D dose distribution averaged over the possible starting phases is calculated using the 4DCT and a model of the time structure of the delivered spot map. The dose is accumulated using vector maps created by a GPU-accelerated deformable image registration program (DIR) from each phase of the 4DCT to the reference phase using the B-spline method. Calculation of the Dij matrices and the DIR are performed on a cluster, with each field and vector map calculated in parallel. Results: The Dij production takes ∼3.5s per beamlet for 10e6 protons, depending on the energy and the CT size. Generating a plan with 4D simulation of 1000 spots in 4 fields takes approximately 1h. To test the framework, IMPT plans for 10 lung cancer patients were generated for validation. Differences between the planned and the delivered dose of 19% in dose to some organs at risk and 1.4/21.1% in target mean dose/homogeneity with respect to the plan were observed, suggesting potential for improvement if adaptation is considered. Conclusion: A fast MC treatment planning framework has been developed that allows reliable plan design and verification for mobile targets and adaptation of treatment plans. This will significantly impact treatments for lung tumors, as 4D-MC dose calculations can now become part of planning strategies.

SU‐F‐J‐186: Enabling Adaptive IMPT with CBCT‐Based Dose Recalculation for H&amp;N and Prostate Cancer Patients

Purpose:To enable adaptive intensity modulated proton therapy for sites sensitive to inter‐fractional changes on the basis of accurate CBCT‐based proton dose calculations. To this aim two CBCT intensity correction methods are considered: planning CT (pCT) to CBCT DIR and projection correction based on pCT DIR prior.Methods:3 H&amp;N and 3 prostate cancer patients with CBCT images and corresponding projections were used in this study, in addition to pCT and re‐planning CT (rpCT) images (H&amp;N only). A virtual CT (vCT) was generated by pCT to CBCT DIR. In a second approach, the vCT was used as prior for scatter correction of the CBCT projections to yield a CBCTcor image. BEV 2D range maps of SFUD IMPT plans were compared. For the prostate cases, the geometric accuracy of the vCT was also evaluated by contour comparison to physician delineation of the CBCTcor and original CBCT.Results:SFUD dose calculations on vCT and CBCTcor were found to be within 3mm for 97% to 99% of 2D range maps. Median range differences compared to rpCT were below 0.5mm. Analysis showed that the DIR‐based vCT approach exhibits inaccuracies in the pelvic region due to the very low soft‐tissue contrast in the CBCT. The CBCTcor approach yielded results closer to the original CBCT in terms of DICE coefficients than the vCT (median 0.91 vs 0.81) for targets and OARs. In general, the CBCTcor approach was less affected by inaccuracies of the DIR used during the generation of the vCT prior.Conclusion:Both techniques yield 3D CBCT images with intensities equivalent to diagnostic CT and appear suitable for IMPT dose calculation for most sites. For H&amp;N cases, no considerable differences between the two techniques were found, while improved results of the CBCTcor were observed for pelvic cases due to the reduced sensitivity to registration inaccuracies.Deutsche Forschungsgemeinschaft (MAP); Bundesministerium fur Bildung und Forschung (01IB13001)

TU‐C‐BRA‐09: High‐Performance Dose Calculation for Proton Radiotherapy Using GPU

Purpose: To investigate the feasibility and the potential speed gain of GPU accelerated dose calculation for proton pencil beam algorithms with heterogeneity correction and to offer solutions to obstacles in implementing our algorithm. Method and Materials: We implemented our in‐house proton dose calculation system on an NVIDIA GTX 280 graphic card and an Intel Xeon 2.83 GHz processor using the Compute Unified Device Architecture environment. Several key techniques and strategies were employed in order to optimize the performance of the GPU code. (1) Modified the scaling algorithm used to calculate lateral spreading of the proton beam in the presence of tissue inhomogeneities. (2) Used an incremental ray tracing algorithm to reduce the memory requirement for each ray allowing for better parallelization. (3) The penalty of massive non‐coalesced memory reads required for convolution/superposition was alleviated by texture fetching. (4) Parallel algorithms such as reduction and prefix sum were implemented on GPU to help avoid data transfer between the CPU and GPU memory. The performance of both implementations was evaluated on a prostate clinical case. Results: With no loss in accuracy, the dose calculation time per beamlet with our GPU implementation ranges from 200 – 500 ms compared to 15 – 40 s on CPU. Approximately 80 times speed gain is achieved for various number of convolution/superposition steps. Conclusions: GPU‐based proton dose calculation is feasible with adapted algorithms and proper implementation techniques. Close to two magnitude of performance gain can be achieved with typical hardware. We believe GPU‐based fast dose calculation can reduce the routine treatment planning workload as well as provide a feasible solution to the realization of online adaptive intensity modulated proton therapy.