Visualization of a variety of possible dosimetric outcomes in radiation therapy using dose-volume histogram bands

Proton Therapy for Spinal Tumors: A Consensus Statement From the Particle Therapy Cooperative Group

PURPOSE

Proton beam therapy (PBT) plays an important role in the management of primary spine tumors. The purpose of this consensus statement was to summarize safe and optimal delivery of PBT for spinal tumors.

METHODS AND MATERIALS

The Particle Therapy Cooperative Group Skull Base/Central nervous system/Sarcoma Subcommittee consisting of radiation oncologists and medical physicists with specific expertise in spinal irradiation developed expert recommendations discussing treatment planning considerations and current approaches in the treatment of primary spinal tumors.

RESULTS

Computed tomography simulation: factors that require significant consideration include (1) patient comfort, (2) setup reproducibility and stability, and (3) accessibility of appropriate beam angles.

SPINE STABILIZATION HARDWARE

If present, hardware should be placed with cross-links well above/below the level of the primary tumor to reduce the metal burden at the level of the tumor bed. New materials that can reduce uncertainties include polyether-ether-ketone and composite polyether-ether-ketone-carbon fiber implants.

FIELD ARRANGEMENT

Appropriate beam selection is required to ensure robust target coverage and organ at risk sparing. Commonly, 2 to 4 treatment fields, typically from posterior and/or posterior-oblique directions, are used.

TREATMENT PLANNING METHODOLOGY

Robust optimization is recommended for all pencil beam scanning plans (the preferred treatment modality) and should consider setup uncertainty (between 3 and 7 mm) and range uncertainty (3%-3.5%). In the presence of metal hardware, use of an increased range uncertainty up to 5% is recommended.

CONCLUSIONS

The Particle Therapy Cooperative Group Skull Base/Central nervous system/Sarcoma Subcommittee has developed recommendations to enable centers to deliver PBT safely and effectively for the management of primary spinal tumors.

Robust treatment planning for small animal radio-neuromodulation using focused kV x-ray beams

BACKGROUND

In preclinical radio-neuromodulation research, small animal experiments are pivotal for unraveling radiobiological mechanism, investigating prescription and planning techniques, and assessing treatment effects and toxicities. However, the target size inside a rat brain is typically in the order of sub-millimeters. The small target inside the visual cortex neural region in rat brain with a diameter of around 1 mm was focused in this work to observe the physiological change of this region. Delivering uniform doses to the small target while sparing health tissues is challenging. Focused kV x-ray technique based on modern x-ray polycapillary focusing lens is a promising modality for small animal radio-neuromodulation.

PURPOSE

The current manual planning method could lead to sub-optimal plans, and the positioning uncertainties due to mechanical accuracy limitations, animal immobilization, and robotic arm motion are not considered. This work aims to design a robust inverse planning method to optimize the intensities of focused kV x-ray beams located in beam trajectories to irradiate small mm-sized targets in rat brains for radio-neuromodulation.

METHODS

Focused kV x-ray beams were generated through polycapillary x-ray focusing lenses on achieving small (≤0.3 mm) focus perpendicular to the beam. The beam trajectories were manually designed in 3D space in scanning-while-rotating mode. Geant4 Monte Carlo (MC) simulation generated a dose calculation matrix for each focused kV x-ray beam located in beam trajectories. In the proposed robust inverse planning method, an objective function combining a voxel-wise stochastic programming approach and L1 norm regularization was established to overcome the positioning uncertainties and obtain a high-quality plan. The fast iterative shrinkage thresholding algorithm (FISTA) was utilized to solve the objective function and obtain the optimal intensities. Four cases were employed to validate the feasibility and effectiveness of the proposed method. The manual and non-robust inverse planning methods were also implemented for comparison.

RESULTS

The proposed robust inverse planning method achieved superior dose homogeneity and higher robustness against positioning uncertainties. On average, the clinical target volume (CTV) homogeneity index (HI) of robust inverse plan improved to 13.3 from 22.9 in non-robust inverse plan and 53.8 in manual plan if positioning uncertainties were also present. The average bandwidth at D90 was reduced by 6.5 Gy in the robust inverse plan, compared to 9.6 Gy in non-robust inverse plan and 12.5 Gy in manual plan. The average bandwidth at D80 was reduced by 3.4 Gy in robust inverse plan, compared to 5.5 Gy in non-robust inverse plan and 8.5 Gy in manual plan. Moreover, the dose delivery time of manual plan was reduced by an average reduction of 54.7% with robust inverse plan and 29.0% with non-robust inverse plan.

CONCLUSION

Compared to manual and non-robust inverse planning methods, the robust inverse planning method improved the dose homogeneity and delivery efficiency and was resistant to the uncertainties, which are crucial for radio-neuromodulation utilizing focused kV x-rays.

Characterization of Photon Intensity Modulated Radiation Therapy Robustness in Patients With Prostate Cancer as a Proposed Benchmark for Proton Therapy Robustness Evaluation

PURPOSE

Robustness evaluation is increasingly used in particle therapy planning to assess clinical target volume (CTV) coverage in the setting of setup and range uncertainty. However, no clear standard exists as to an acceptable degree of plan robustness. The aim of this study is to quantify x-ray robustness parameters, as this could inform proton planning when held to a similar standard.

METHODS AND MATERIALS

Consecutive patients with prostate adenocarcinoma treated with definitive x-irradiation to the prostate alone at a single institution in 2019 were retrospectively reviewed. CTV to planned target volume (PTV) margins of 7 mm in all directions, except 4 mm posteriorly, were used in the main cohort. Plans were normalized to PTV V100% ≥ 95%. Patient setup errors were simulated by shifting the isocenter relative to the patient in each of the cardinal directions. The magnitude of each shift equaled the magnitude of the CTV to PTV expansion in that direction. Range uncertainty was set to 0%.

RESULTS

A total of 27 patients were evaluated. The mean (SD) nominal plan CTV V100% was 99.6% (1.1%). The mean (SD) worst-case shift CTV V100% was 97.2% (2.8%). The mean (SD) nominal and worst-case CTV V95% were 100% (0%) and 99.7% (0.5%), respectively. A worst-case CTV V100% > 90% and a worst-case CTV V95% > 99% were achieved in over 95% of plans. The mean (SD) nominal and worst-case rectal V70 Gy were 2.37 cc (1.00 cc) and 11.60 cc (3.16 cc), respectively. The mean (SD) nominal and worst-case bladder V60 Gy were 7.8% (4.8%) and 14.5% (9.3%), respectively. Paired 2-tailed t tests comparing the nominal to worst-case dose-volume histograms were significant for each dosimetric parameter (P < .01).

CONCLUSIONS

X-ray planning uses PTV margins to inherently provide robustness to patient setup errors. Although the prostate remains well covered in various setup uncertainty scenarios, organs at risk routinely exceeded nominal treatment plan institutional constraints in the worst-case scenarios. Robustness metrics obtained from x-ray plans could serve as a benchmark for proton therapy robust optimization and evaluation.

Reformulated McNamara RBE-weighted beam orientation optimization for intensity modulated proton therapy

PURPOSE

Empirical relative biological effectiveness (RBE) models have been used to estimate the biological dose in proton therapy but do not adequately capture the factors influencing RBE values for treatment planning. We reformulate the McNamara RBE model such that it can be added as a linear biological dose fidelity term within our previously developed sensitivity-regularized and heterogeneity-weighted beam orientation optimization (SHBOO) framework.

METHODS

Based on our SHBOO framework, we formulated the biological optimization problem to minimize total McNamara RBE dose to OARs. We solve this problem using two optimization algorithms: FISTA (McNam-FISTA) and Chambolle-Pock (McNam-CP). We compare their performances with a physical dose optimizer assuming RBE = 1.1 in all structures (PHYS-FISTA) and an LET-weighted dose model (LET-FISTA). Three head and neck patients were planned with the four techniques and compared on dosimetry and robustness.

RESULTS

Compared to Phys-FISTA, McNam-CP was able to match CTV [HI, Dmax, D95%, D98%] by [0.00, 0.05%, 1.4%, 0.8%]. McNam-FISTA and McNam-CP were able to significantly improve overall OAR [Dmean, Dmax] by an average of [36.1%,26.4%] and [29.6%, 20.3%], respectively. Regarding CTV robustness, worst [Dmax, V95%, D95%, D98%] improvement of [-6.6%, 6.2%, 6.0%, 4.8%] was reported for McNam-FISTA and [2.7%, 2.7%, 5.3%, -4.3%] for McNam-CP under combinations of range and setup uncertainties. For OARs, worst [Dmax, Dmean] were improved by McNam-FISTA and McNam-CP by an average of [25.0%, 19.2%] and [29.5%, 36.5%], respectively. McNam-FISTA considerably improved dosimetry and CTV robustness compared to LET-FISTA, which achieved better worst-case OAR doses.

CONCLUSION

The four optimization techniques deliver comparable biological doses for the head and neck cases. Besides modest CTV coverage and robustness improvement, OAR biological dose and robustness were substantially improved with both McNam-FISTA and McNam-CP, showing potential benefit for directly incorporating McNamara RBE in proton treatment planning.

Report of AAPM Task Group 290: Respiratory motion management for particle therapy

Dose uncertainty induced by respiratory motion remains a major concern for treating thoracic and abdominal lesions using particle beams. This Task Group report reviews the impact of tumor motion and dosimetric considerations in particle radiotherapy, current motion‐management techniques, and limitations for different particle‐beam delivery modes (i.e., passive scattering, uniform scanning, and pencil‐beam scanning). Furthermore, the report provides guidance and risk analysis for quality assurance of the motion‐management procedures to ensure consistency and accuracy, and discusses future development and emerging motion‐management strategies. This report supplements previously published AAPM report TG76, and considers aspects of motion management that are crucial to the accurate and safe delivery of particle‐beam therapy. To that end, this report produces general recommendations for commissioning and facility‐specific dosimetric characterization, motion assessment, treatment planning, active and passive motion‐management techniques, image guidance and related decision‐making, monitoring throughout therapy, and recommendations for vendors. Key among these recommendations are that: (1) facilities should perform thorough planning studies (using retrospective data) and develop standard operating procedures that address all aspects of therapy for any treatment site involving respiratory motion; (2) a risk‐based methodology should be adopted for quality management and ongoing process improvement.

Accurate assessment of a Dutch practical robustness evaluation protocol in clinical PT with pencil beam scanning for neurological tumors

BACKGROUND AND PURPOSE

Scenario-based robust optimization and evaluation is commonly used in proton therapy (PT) with pencil beam scanning (PBS) to ensure adequate dose to the clinical target volume (CTV). However, a statistically accurate assessment of the clinical application of this approach is lacking. In this study, we assess target dose in a clinical cohort of neuro-oncological patients, planned according to the DUPROTON robustness evaluation consensus, using polynomial chaos expansion (PCE).

MATERIALS AND METHODS

A cohort of the first 27 neuro-oncological patients treated at HollandPTC was used, including realistic error distributions derived from geometrical and stopping-power prediction (SPP) errors. After validating the model, PCE-based robustness evaluations were performed by simulating 100.000 complete fractionated treatments per patient to obtain accurate statistics on clinically relevant dosimetric parameters and population-dose histograms.

RESULTS

Treatment plans that were robust according to clinical protocol and treatment plans in which robustness was sacrificed are easily identified. For robust treatment plans on average, a CTV dose of 3 percentage points (p.p.) more than prescribed was realized (range +2.7 p.p. - +3.5 p.p.) for 98% of the sampled fractionated treatments. For the entire patient cohort on average, a CTV dose of 0.1 p.p. less than prescribed was achieved (range -2.4 p.p. - +0.5 p.p.). For the 6 treatment plans in which robustness was clinically sacrificed, normalized CTV doses of 0.98, 0.94(7)¹², 0.94, 0.91, 0.90 and 0.89 were realized. The first of these was clinically borderline non-robust.

CONCLUSION

The clinical robustness evaluation protocol is safe in terms of CTV dose as all plans that fulfilled the clinical robustness criteria were also robust in the PCE evaluation. Moreover, for plans that were non-robust in the PCE-based evaluation, CTV dose was also lower than prescribed in the clinical evaluation.

A Review of the Robust Optimization Process and Advances with Monte Carlo in the Proton Therapy Management of Head and Neck Tumors

In intensity-modulated proton therapy, robust optimization processes have been developed to manage uncertainties associated with (1) range, (2) setup, (3) anatomic changes, (4) dose calculation, and (5) biological effects. Here we review our experience using a robust optimization technique that directly incorporates range and setup uncertainties into the optimization process to manage those sources of uncertainty. We also review procedures for implementing adaptive planning to manage the anatomic uncertainties. Finally, we share some early experiences regarding the impact of uncertainties in dose calculation and biological effects, along with techniques to manage and potentially reduce these uncertainties.

Feasibility Study of Robust Optimization to Reduce Dose Delivery Uncertainty by Potential Applicator Displacements for a Cervix Brachytherapy

Brachytherapy is an important technique to increase the overall survival of cervical cancer patients. However, a possible shift of the applicators in relation to the target and organs at risk may occur between imaging and treatment. Without daily adaptive brachytherapy planning, these applicator displacements can lead to a significant change in dose distribution. In order to resolve it, a robust optimization method had been developed using a genetic algorithm combined with a median absolute deviation as a robustness evaluation function. The resulting robustness plans from our strategy might be worth considering according to the GEC-ESTRO guidelines. From the point of view of dose delivery uncertainty from applicator displacement, the robust optimization may be considered with caution in a single-plan approach for High Dose Rate brachytherapy treatment planning and should be confirmed by a more thorough investigation.

Assessment of robustness against setup uncertainties using probabilistic scenarios in lung cancer: a comparison of proton with photon therapy

OBJECTIVE

We compared the sensitivity of intensity modulated proton therapy (IMPT) and photon volumetric modulated arc therapy (VMAT) plans to setup uncertainties in locally advanced non-small cell lung cancer (NSCLC) using probabilistic scenarios.

METHODS

Minimax robust (MM) and planning target volume (PTV) optimised IMPT and VMAT nominal plans were created with physical dose of 70 Gy in 35 fractions in 10 representative patients. Using population data of setup errors, a fractionated treatment course was simulated, summed (Dsum) and compared to the nominal plan. Three treatment-course simulations were done for each plan. Target robustness criteria were: dose deviation of ≤5% to clinical target volume (CTV) D98% and CTV V95% ≥ 99.9%. Voxelwise simulation repeatability was analysed using Bland-Altman plots. Acceptable limits of agreement were 2% of the prescription dose.

RESULTS

All Dsum met target robustness criteria. While fraction VMAT and MM-IMPT doses were excellent, simulated fraction doses in PTV-IMPT were suboptimal. Almost all (>99%) of VMAT and MM-IMPT fraction doses met both target robustness criteria. For PTV-IMPT, only 96.9 and 80.3% of fractions met CTVD98% and V95% criteria respectively. Simulation repeatability was excellent (limits of agreement range: 0.41-1.1 Gy) with strong positive correlations.

CONCLUSION

When considering the whole treatment course, setup errors do not influence robustness irrespective of planning techniques used. However, on a fraction level, VMAT and MM-IMPT plans are superior compared to PTV-IMPT plans.

ADVANCES IN KNOWLEDGE

Probabilistic analysis provides a fast and practical method for evaluating VMAT and IMPT plan sensitivity against setup uncertainty. VMAT and robust-optimised IMPT plans have comparable sensitivity to setup uncertainties in conventionally fractionated treatment for NSCLC.

Robust Optimization for Intensity Modulated Proton Therapy to Redistribute High Linear Energy Transfer from Nearby Critical Organs to Tumors in Head and Neck Cancer

PURPOSE

We propose linear energy transfer (LET)-guided robust optimization in intensity modulated proton therapy for head and neck cancer. This method simultaneously considers LET and physical dose distributions of tumors and organs at risk (OARs) with uncertainties.

METHODS AND MATERIALS

Fourteen patients with head and neck cancer were included in this retrospective study. Cord, brain stem, brain, and oral cavity were considered. Two algorithms, voxel-wise worst-case robust optimization and LET-guided robust optimization (LETRO), were used to generate intensity modulated proton therapy plans for each patient. The latter method directly optimized LET distributions rather than indirectly as in previous methods. LET-volume histograms (LETVHs) were generated, and high LET was redistributed from nearby OARs to tumors in a user-defined way via LET-volume constraints. Dose-volume histogram indices, such as clinical target volume (CTV) D_98% and D_2%-D_98%, cord D_max, brain stem D_max, brain D_max, and oral cavity D_mean, were calculated. Plan robustness was quantified using the worst-case analysis method. LETVH indices analogous to dose-volume histogram indices were used to characterize LET distributions. The Wilcoxon signed rank test was performed to measure statistical significance.

RESULTS

In the nominal scenario, LETRO provided higher LET distributions in the CTV (unit: keV/μm; CTV LET_98%: 1.18 vs 1.08, LETRO vs RO, P = .0031) while preserving comparable physical dose and plan robustness. LETRO achieved significantly reduced LET distributions in the cord, brain stem, and oral cavity compared with RO (cord LET_max: 7.20 vs 8.20, P = .0010; brain stem LET_max: 10.95 vs 12.05, P = .0007; oral cavity LET_mean: 2.11 vs 3.12, P = .0052) and had comparable physical dose and plan robustness in all OARs. In the worst-case scenario, LETRO achieved significantly higher LET_mean in the CTV, reduced LET_max in the brain, and was comparable to other LETVH indices (CTV LET_mean: 3.26 vs 3.35, P = .0012; brain LET_max: 24.80 vs 22.00, P = .0016).

CONCLUSIONS

LETRO robustly optimized LET and physical dose distributions simultaneously. It redistributed high LET from OARs to targets with slightly modified physical dose and plan robustness.

Technical Note: Treatment planning system (TPS) approximations matter - comparing intensity-modulated proton therapy (IMPT) plan quality and robustness between a commercial and an in-house developed TPS for nonsmall cell lung cancer (NSCLC)

PURPOSE

Approximate dose calculation methods were used in the nominal dose distribution and the perturbed dose distributions due to uncertainties in a commercial treatment planning system (CTPS) for robust optimization in intensity-modulated proton therapy (IMPT). We aimed to investigate whether the approximations influence plan quality, robustness, and interplay effect of the resulting IMPT plans for the treatment of locally advanced lung cancer patients.

MATERIALS AND METHODS

Ten consecutively treated locally advanced nonsmall cell lung cancer (NSCLC) patients were selected. Two IMPT plans were created for each patient using our in-house developed TPS, named "Solo," and also the CTPS, Eclipse^TM (Varian Medical Systems, Palo Alto, CA, USA), respectively. The plans were designed to deliver prescription doses to internal target volumes (ITV) drawn by a physician on averaged four-dimensional computed tomography (4D-CT). Solo plans were imported back to CTPS, and recalculated in CTPS for fair comparison. Both plans were further verified for each patient by recalculating doses in the inhalation and exhalation phases to ensure that all plans met clinical requirements. Plan robustness was quantified on all phases using dose-volume-histograms (DVH) indices in the worst-case scenario. The interplay effect was evaluated for every plan using an in-house developed software, which randomized starting phases of each field per fraction and accumulated dose in the exhalation phase based on the patient's breathing motion pattern and the proton spot delivery in a time-dependent fashion. DVH indices were compared using Wilcoxon rank-sum test.

RESULTS

Compared to the plans generated using CTPS on the averaged CT, Solo plans had significantly better target dose coverage and homogeneity (normalized by the prescription dose) in the worst-case scenario [ITV D_95% : 98.04% vs 96.28%, Solo vs CTPS, P = 0.020; ITV D_5% -D_95% : 7.20% vs 9.03%, P = 0.049] while all DVH indices were comparable in the nominal scenario. On the inhalation phase, Solo plans had better target dose coverage and cord D_max in the nominal scenario [ITV D_95% : 99.36% vs 98.45%, Solo vs CTPS, P = 0.014; cord D_max : 20.07 vs 23.71 Gy(RBE), P = 0.027] with better target coverage and cord D_max in the worst-case scenario [ITV D_95% : 97.89% vs 96.47%, Solo vs CTPS, P = 0.037; cord D_max : 24.57 vs 28.14 Gy(RBE), P = 0.037]. On the exhalation phase, similar phenomena were observed in the nominal scenario [ITV D_95% : 99.63% vs 98.87%, Solo vs CTPS, P = 0.037; cord D_max : 19.67 vs 23.66 Gy(RBE), P = 0.039] and in the worst-case scenario [ITV D_95% : 98.20% vs 96.74%, Solo vs CTPS, P = 0.027; cord D_max : 23.47 vs 27.93 Gy(RBE), P = 0.027]. In terms of interplay effect, plans generated by Solo had significantly better target dose coverage and homogeneity, less hot spots, and lower esophageal D_mean , and cord D_max [ITV D_95% : 101.81% vs 98.68%, Solo vs CTPS, P = 0.002; ITV D_5% -D_95% : 2.94% vs 7.51%, P = 0.002; cord D_max : 18.87 vs 22.29 Gy(RBE), P = 0.014].

CONCLUSIONS

Solo-generated IMPT plans provide improved cord sparing, better target robustness in all considered phases, and reduced interplay effect compared with CTPS. Consequently, the approximation methods currently used in commercial TPS programs may have space for improvement in generating optimal IMPT plans for patient cases with locally advanced lung cancer.

Practical robustness evaluation in radiotherapy - A photon and proton-proof alternative to PTV-based plan evaluation

BACKGROUND AND PURPOSE

A planning target volume (PTV) in photon treatments aims to ensure that the clinical target volume (CTV) receives adequate dose despite treatment uncertainties. The underlying static dose cloud approximation (the assumption that the dose distribution is invariant to errors) is problematic in intensity modulated proton treatments where range errors should be taken into account as well. The purpose of this work is to introduce a robustness evaluation method that is applicable to photon and proton treatments and is consistent with (historic) PTV-based treatment plan evaluations.

MATERIALS AND METHODS

The limitation of the static dose cloud approximation was solved in a multi-scenario simulation by explicitly calculating doses for various treatment scenarios that describe possible errors in the treatment course. Setup errors were the same as the CTV-PTV margin and the underlying theory of 3D probability density distributions was extended to 4D to include range errors, maintaining a 90% confidence level. Scenario dose distributions were reduced to voxel-wise minimum and maximum dose distributions; the first to evaluate CTV coverage and the second for hot spots. Acceptance criteria for CTV D98 and D2 were calibrated against PTV-based criteria from historic photon treatment plans.

RESULTS

CTV D98 in worst case scenario dose and voxel-wise minimum dose showed a very strong correlation with scenario average D98 (R² > 0.99). The voxel-wise minimum dose visualised CTV dose conformity and coverage in 3D in agreement with PTV-based evaluation in photon therapy. Criteria for CTV D98 and D2 of the voxel-wise minimum and maximum dose showed very strong correlations to PTV D98 and D2 (R² > 0.99) and on average needed corrections of -0.9% and +2.3%, respectively.

CONCLUSIONS

A practical approach to robustness evaluation was provided and clinically implemented for PTV-less photon and proton treatment planning, consistent with PTV evaluations but without its static dose cloud approximation.

Robustness Analysis for External Beam Radiation Therapy Treatment Plans: Describing Uncertainty Scenarios and Reporting Their Dosimetric Consequences

PURPOSE

With external beam radiation therapy, uncertainties in treatment planning and delivery can result in an undesirable dose distribution delivered to the patient that can compromise the benefit of treatment. Techniques including geometric margins and probabilistic optimization have been used effectively to mitigate the effects of uncertainties. However, their broad application is inconsistent and can compromise the conclusions derived from cross-technique and cross-modality comparisons.

METHODS AND MATERIALS

Conventional methods to deal with treatment planning and delivery uncertainties are described, and robustness analysis is presented as a framework that is applicable across treatment techniques and modalities.

RESULTS

This report identifies elements that are imperative to include when conducting a robustness analysis and describing uncertainties and their dosimetric effects.

CONCLUSION

The robustness analysis approach described here is presented to promote reliable plan evaluation and dose reporting, particularly during clinical trials conducted across institutions and treatment modalities.

Robust beam orientation optimization for intensity-modulated proton therapy

PURPOSE

Dose conformality and robustness are equally important in intensity modulated proton therapy (IMPT). Despite the obvious implication of beam orientation on both dosimetry and robustness, an automated, robust beam orientation optimization algorithm has not been incorporated due to the problem complexity and paramount computational challenge. In this study, we developed a novel IMPT framework that integrates robust beam orientation optimization (BOO) and robust fluence map optimization (FMO) in a unified framework.

METHODS

The unified framework is formulated to include a dose fidelity term, a heterogeneity-weighted group sparsity term, and a sensitivity regularization term. The L2, 1/2-norm group sparsity is used to reduce the number of active beams from the initial 1162 evenly distributed noncoplanar candidate beams, to between two and four. A heterogeneity index, which evaluates the lateral tissue heterogeneity of a beam, is used to weigh the group sparsity term. With this index, beams more resilient to setup uncertainties are encouraged. There is a symbiotic relationship between the heterogeneity index and the sensitivity regularization; the integrated optimization framework further improves beam robustness against both range and setup uncertainties. This Sensitivity regularization and Heterogeneity weighting based BOO and FMO framework (SHBOO-FMO) was tested on two skull-base tumor (SBT) patients and two bilateral head-and-neck (H&N) patients. The conventional CTV-based optimized plans (Conv) with SHBOO-FMO beams (SHBOO-Conv) and manual beams (MAN-Conv) were compared to investigate the beam robustness of the proposed method. The dosimetry and robustness of SHBOO-FMO plan were compared against the manual beam plan with CTV-based voxel-wise worst-case scenario approach (MAN-WC).

RESULTS

With SHBOO-FMO method, the beams with superior range robustness over manual beams were selected while the setup robustness was maintained or improved. On average, the lowest [D95%, V95%, V100%] of CTV were increased from [93.85%, 91.06%, 70.64%] in MAN-Conv plans, to [98.62%, 98.61%, 96.17%] in SHBOO-Conv plans with range uncertainties. With setup uncertainties, the average lowest [D98%, D95%, V95%, V100%] of CTV were increased from [92.06%, 94.83%, 94.31%, 78.93%] in MAN-Conv plans, to [93.54%, 96.61%, 97.01%, 91.98%] in SHBOO-Conv plans. Compared with the MAN-WC plans, the final SHBOO-FMO plans achieved comparable plan robustness and better OAR sparing, with an average reduction of [Dmean, Dmax] of [6.31, 6.55] GyRBE for the SBT cases and [1.89, 5.08] GyRBE for the H&N cases from the MAN-WC plans.

CONCLUSION

We developed a novel method to integrate robust BOO and robust FMO into IMPT optimization for a unified solution of both BOO and FMO, generating plans with superior dosimetry and good robustness.

An evaluation method of clinical impact with setup, range, and radiosensitivity uncertainties in fractionated carbon-ion therapy

In light ion therapy, the dose concentration is highly sensitive to setup and range errors. Here we propose a method for evaluating the effects of these errors by using the correlation between fractions on tumour control probability (TCP) in carbon-ion therapy. This method incorporates the concept of equivalent stochastic dose (Cranmer-Sargison and Zavgorodni 2005 Phys. Med. Biol. 50 4097-109), which was defined as a dose that gives the mean expected survival fraction (SF) for the stochastically variable dose. The mean expected SFs were calculated while considering the correlation between fractions for setup and range errors. By using this SF, equivalent stochastic clinical doses (ESCD), which are weighted by relative biological effectiveness, of lung and prostate cases with varying errors were derived. To account for spatial dose heterogeneity, equivalent uniform stochastic clinical doses (EUSCD) were obtained by using the mean expected SF in the volume of interest. TCP curves were calculated for each assumed error considering inter-patient sensitivity variation with a fractionation effect. ESCD distributions, EUSCD, and TCP curves were affected by the inter-fraction correlation and the contribution of setup and range errors. Irradiated areas that could be affected by these errors can be visualized quantitatively by using the ESCD distribution. TCP curves for the errors of various conditions converged around the TCP curve in nominal conditions by using the EUSCD. EUSCD correlated well with TCP in setup and range errors when the errors were not large and was comparatively stably insensitive to uncertain biological parameters. The proposed evaluation method with EUSCD and TCP calculations will be useful to indicate tumour doses to improve realistic dose distributions in carbon-ion therapy.

Isodose feature-preserving voxelization (IFPV) for radiation therapy treatment planning

PURPOSE

Inverse planning involves iterative optimization of a large number of parameters and is known to be a labor-intensive procedure. To reduce the scale of computation and improve characterization of isodose plan, this paper presents an isodose feature-preserving voxelization (IFPV) framework for radiation therapy applications and demonstrates an implementation of inverse planning in the IFPV domain.

METHODS

A dose distribution in IFPV scheme is characterized by partitioning the voxels into subgroups according to their geometric and dosimetric values. Computationally, the isodose feature-preserving (IFP) clustering combines the conventional voxels that are spatially and dosimetrically close into physically meaningful clusters. A K-means algorithm and support vector machine (SVM) runs sequentially to group the voxels into IFP clusters. The former generates initial clusters according to the geometric and dosimetric information of the voxels and SVM is invoked to improve the connectivity of the IFP clusters. To illustrate the utility of the formalism, an inverse planning framework in the IFPV domain is implemented, and the resultant plans of three prostate IMRT and one head-and-neck cases are compared quantitatively with that obtained using conventional inverse planning technique.

RESULTS

The IFPV generates models with significant dimensionality reduction without compromising the spatial resolution seen in traditional downsampling schemes. The implementation of inverse planning in IFPV domain is demonstrated. In addition to the improved computational efficiency, it is found that, for the cases studied here, the IFPV-domain inverse planning yields better treatment plans than that of DVH-based planning, primarily because of more effective use of both geometric and dose information of the system during plan optimization.

CONCLUSIONS

The proposed IFPV provides a low parametric representation of isodose plan without compromising the essential characteristics of the plan, thus providing a practically valuable framework for various applications in radiation therapy.

Robust optimization in IMPT using quadratic objective functions to account for the minimum MU constraint

PURPOSE

Currently, in clinical practice of intensity-modulated proton therapy (IMPT), the influence of the minimum monitor unit (MU) constraint is taken into account through postprocessing after the optimization is completed. This may degrade the plan quality and plan robustness. This study aims to mitigate the impact of the minimum MU constraint directly during the plan robust optimization.

METHODS AND MATERIALS

Cao et al. have demonstrated a two-stage method to account for the minimum MU constraint using linear programming without the impact of uncertainties considered. In this study, we took the minimum MU constraint into consideration using quadratic optimization and simultaneously had the impact of uncertainties considered using robust optimization. We evaluated our method using seven cancer patients with different machine settings.

RESULT

The new method achieved better plan quality than the conventional method. The D_95% of the clinical target volume (CTV) normalized to the prescription dose was (mean [min-max]): (99.4% [99.2%-99.6%]) vs. (99.2% [98.6%-99.6%]). Plan robustness derived from these two methods was comparable. For all seven patients, the CTV dose-volume histogram band gap (narrower band gap means more robust plans) at D_95% normalized to the prescription dose was (mean [min-max]): (1.5% [0.5%-4.3%]) vs. (1.2% [0.6%-3.8%]).

CONCLUSION

Our new method of incorporating the minimum MU constraint directly into the plan robust optimization can produce machine-deliverable plans with better tumor coverage while maintaining high-plan robustness.

Adding another dimension to plan evaluation: visualising the dose–volume histogram band in head and neck radiotherapy and exploring its utility

Background

To introduce a method to generate a ‘dose–volume histogram (DVH) band’ for plan evaluation of photon therapy and explore its various potentials.

Materials and methods

Intensity-modulated radiotherapy (IMRT) plans for head and neck cancer patients were analysed, retrospectively, for setup errors noted during treatment. From the maximum observed random errors, absolute displacement was calculated using Euclidian formula. The original plan with same beam parameters and leaf sequence were used to generate six plans with shifts applied in three axes in six directions. The DVH curves from these six plans were superimposed to form the DVH band. Plans were reviewed with set tolerance criteria.

Results

Method to generate and visualise DVH band was developed. DVH bands were created for 20 patients with head and neck cancer who underwent treatment with IMRT. It was found that seven out these 20 plans were rejected as they crossed the set tolerance criteria using DVH band as an evaluation tool.

Conclusions

DVH band in photon therapy can help the clinician visualise the impact of setup errors at planning and may help select the plan with lesser influence of setup errors over another.

Impact of robust treatment planning on single- and multi-field optimized plans for proton beam therapy of unilateral head and neck target volumes

BACKGROUND

Proton beam therapy is promising for the treatment of head and neck cancer (HNC), but it is sensitive to uncertainties in patient positioning and particle range. Studies have shown that the planning target volume (PTV) concept may not be sufficient to ensure robustness of the target coverage. A few planning studies have considered irradiation of unilateral HNC targets with protons, but they have only taken into account the dose on the nominal plan, without considering anatomy changes occurring during the treatment course.

METHODS

Four pencil beam scanning (PBS) proton therapy plans were calculated for 8 HNC patients with unilateral target volumes: single-field (SFO) and multi-field optimized (MFO) plans, either using the PTV concept or clinical target volume (CTV)-based robust optimization. The dose was recalculated on computed tomography (CT) scans acquired during the treatment course. Doses to target volumes and organs at risk (OARs) were compared for the nominal plans, cumulative doses considering anatomical changes, and additional setup and range errors in each fraction. If required, the treatment plan was adapted, and the dose was compared with the non-adapted plan.

RESULTS

All nominal plans fulfilled the clinical specifications for target coverage, but significantly higher doses on the ipsilateral parotid gland were found for both SFO approaches. MFO PTV-based plans had the lowest robustness against range and setup errors. During the treatment course, the influence of the anatomical variation on the dose has shown to be patient specific, mostly independent of the chosen planning approach. Nine plans in four patients required adaptation, which led to a significant improvement of the target coverage and a slight reduction in the OAR dose in comparison to the cumulative dose without adaptation.

CONCLUSIONS

The use of robust MFO optimization is recommended for ensuring plan robustness and reduced doses in the ipsilateral parotid gland. Anatomical changes occurring during the treatment course might degrade the target coverage and increase the dose in the OARs, independent of the chosen planning approach. For some patients, a plan adaptation may be required.

Efficacy of robust optimization plan with partial-arc VMAT for photon volumetric-modulated arc therapy: A phantom study

This study investigated position dependence in planning target volume (PTV)-based and robust optimization plans using full-arc and partial-arc volumetric modulated arc therapy (VMAT). The gantry angles at the periphery, intermediate, and center CTV positions were 181°-180° (full-arc VMAT) and 181°-360° (partial-arc VMAT). A PTV-based optimization plan was defined by 5 mm margin expansion of the CTV to a PTV volume, on which the dose constraints were applied. The robust optimization plan consisted of a directly optimized dose to the CTV under a maximum-uncertainties setup of 5 mm. The prescription dose was normalized to the CTV D_99% (the minimum relative dose that covers 99% of the volume of the CTV) as an original plan. The isocenter was rigidly shifted at 1 mm intervals in the anterior-posterior (A-P), superior-inferior (S-I), and right-left (R-L) directions from the original position to the maximum-uncertainties setup of 5 mm in the original plan, yielding recalculated dose distributions. It was found that for the intermediate and center positions, the uncertainties in the D_99% doses to the CTV for all directions did not significantly differ when comparing the PTV-based and robust optimization plans (P > 0.05). For the periphery position, uncertainties in the D_99% doses to the CTV in the R-L direction for the robust optimization plan were found to be lower than those in the PTV-based optimization plan (P < 0.05). Our study demonstrated that a robust optimization plan's efficacy using partial-arc VMAT depends on the periphery CTV position.

Comparison of linear and nonlinear programming approaches for "worst case dose" and "minmax" robust optimization of intensity-modulated proton therapy dose distributions

Robust optimization of intensity‐modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so‐called “worst case dose” and “minmax” robust optimization approaches and conventional planning target volume (PTV)‐based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull‐based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP‐PTV‐based, NLP‐PTV‐based, LP‐worst case dose, NLP‐worst case dose, LP‐minmax, and NLP‐minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP‐based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP‐based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP‐based methods was superior for the skull‐based and head and neck cancer patients. Overall, LP‐based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet tight dose limits. For robust optimization, the worst case dose approach was less sensitive to uncertainties than was the minmax approach for the prostate and skull‐based cancer patients, whereas the minmax approach was superior for the head and neck cancer patients. The robustness of the IMPT plans was remarkably better after robust optimization than after PTV‐based optimization, and the NLP‐PTV‐based optimization outperformed the LP‐PTV‐based optimization regarding robustness of clinical target volume coverage. In addition, plans generated using LP‐based methods had notably fewer scanning spots than did those generated using NLP‐based methods.

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.

Validation of an in-vivo proton beam range check method in an anthropomorphic pelvic phantom using dose measurements

PURPOSE

In-vivo dosimetry and beam range verification in proton therapy could play significant role in proton treatment validation and improvements. In-vivo beam range verification, in particular, could enable new treatment techniques one of which could be the use of anterior fields for prostate treatment instead of opposed lateral fields as in current practice. This paper reports validation study of an in-vivo range verification method which can reduce the range uncertainty to submillimeter levels and potentially allow for in-vivo dosimetry.

METHODS

An anthropomorphic pelvic phantom is used to validate the clinical potential of the time-resolved dose method for range verification in the case of prostrate treatment using range modulated anterior proton beams. The method uses a 3 × 4 matrix of 1 mm diodes mounted in water balloon which are read by an ADC system at 100 kHz. The method is first validated against beam range measurements by dose extinction measurements. The validation is first completed in water phantom and then in pelvic phantom for both open field and treatment field configurations. Later, the beam range results are compared with the water equivalent path length (WEPL) values computed from the treatment planning system XIO.

RESULTS

Beam range measurements from both time-resolved dose method and the dose extinction method agree with submillimeter precision in water phantom. For the pelvic phantom, when discarding two of the diodes that show sign of significant range mixing, the two methods agree with ±1 mm. Only a dose of 7 mGy is sufficient to achieve this result. The comparison to the computed WEPL by the treatment planning system (XIO) shows that XIO underestimates the protons beam range. Quantifying the exact XIO range underestimation depends on the strategy used to evaluate the WEPL results. To our best evaluation, XIO underestimates the treatment beam range between a minimum of 1.7% and maximum of 4.1%.

CONCLUSIONS

Time-resolved dose measurement method satisfies the two basic requirements, WEPL accuracy and minimum dose, necessary for clinical use, thus, its potential for in-vivo protons range verification. Further development is needed, namely, devising a workflow that takes into account the limits imposed by proton range mixing and the susceptibility of the comparison of measured and expected WEPLs to errors on the detector positions. The methods may also be used for in-vivo dosimetry and could benefit various proton therapy treatments.

Bone marrow sparing in intensity modulated proton therapy for cervical cancer: Efficacy and robustness under range and setup uncertainties

BACKGROUND AND PURPOSE

This study evaluates the potential efficacy and robustness of functional bone marrow sparing (BMS) using intensity-modulated proton therapy (IMPT) for cervical cancer, with the goal of reducing hematologic toxicity.

MATERIAL AND METHODS

IMPT plans with prescription dose of 45 Gy were generated for ten patients who have received BMS intensity-modulated X-ray therapy (IMRT). Functional bone marrow was identified by (18)F-flourothymidine positron emission tomography. IMPT plans were designed to minimize the volume of functional bone marrow receiving 5-40 Gy while maintaining similar target coverage and healthy organ sparing as IMRT. IMPT robustness was analyzed with ±3% range uncertainty errors and/or ±3 mm translational setup errors in all three principal dimensions.

RESULTS

In the static scenario, the median dose volume reductions for functional bone marrow by IMPT were: 32% for V(5Gy), 47% for V(10Gy), 54% for V(20Gy), and 57% for V(40Gy), all with p<0.01 compared to IMRT. With assumed errors, even the worst-case reductions by IMPT were: 23% for V(5Gy), 37% for V(10Gy), 41% for V(20Gy), and 39% for V(40Gy), all with p<0.01.

CONCLUSIONS

The potential sparing of functional bone marrow by IMPT for cervical cancer is significant and robust under realistic systematic range uncertainties and clinically relevant setup errors.

Effectiveness of robust optimization in intensity-modulated proton therapy planning for head and neck cancers

PURPOSE

Intensity-modulated proton therapy (IMPT) is highly sensitive to uncertainties in beam range and patient setup. Conventionally, these uncertainties are dealt using geometrically expanded planning target volume (PTV). In this paper, the authors evaluated a robust optimization method that deals with the uncertainties directly during the spot weight optimization to ensure clinical target volume (CTV) coverage without using PTV. The authors compared the two methods for a population of head and neck (H&N) cancer patients.

METHODS

Two sets of IMPT plans were generated for 14 H&N cases, one being PTV-based conventionally optimized and the other CTV-based robustly optimized. For the PTV-based conventionally optimized plans, the uncertainties are accounted for by expanding CTV to PTV via margins and delivering the prescribed dose to PTV. For the CTV-based robustly optimized plans, spot weight optimization was guided to reduce the discrepancy in doses under extreme setup and range uncertainties directly, while delivering the prescribed dose to CTV rather than PTV. For each of these plans, the authors calculated dose distributions under various uncertainty settings. The root-mean-square dose (RMSD) for each voxel was computed and the area under the RMSD-volume histogram curves (AUC) was used to relatively compare plan robustness. Data derived from the dose volume histogram in the worst-case and nominal doses were used to evaluate the plan optimality. Then the plan evaluation metrics were averaged over the 14 cases and were compared with two-sided paired t tests.

RESULTS

CTV-based robust optimization led to more robust (i.e., smaller AUCs) plans for both targets and organs. Under the worst-case scenario and the nominal scenario, CTV-based robustly optimized plans showed better target coverage (i.e., greater D95%), improved dose homogeneity (i.e., smaller D5% - D95%), and lower or equivalent dose to organs at risk.

CONCLUSIONS

CTV-based robust optimization provided significantly more robust dose distributions to targets and organs than PTV-based conventional optimization in H&N using IMPT. Eliminating the use of PTV and planning directly based on CTV provided better or equivalent normal tissue sparing.

Clinical controversies: proton therapy for prostate cancer

Proton therapy has been used in the treatment of prostate cancer for several decades, and interest surrounding its use continues to grow. Proton-based treatment techniques have evolved significantly over this period, and several centers now routinely use technologies such as pencil-beam scanning. However, whether the theoretical dosimetric advantages of the proton beam translate into clinically meaningful improvements for prostate cancer patients is unknown, and outcomes from single-arm experiences using whole courses of proton beam therapy in the treatment of early-stage prostate cancer have shown mixed results when compared with contemporary intensity-modulated radiotherapy. A randomized trial comparing proton beam therapy with intensity-modulated radiotherapy in early-stage disease has been launched and will be important in defining the role for proton therapy in this setting. We review the available evidence and present the current state of proton beam therapy for prostate cancer.

PTV-based IMPT optimization incorporating planning risk volumes vs robust optimization

PURPOSE

Robust optimization leads to intensity-modulated proton therapy (IMPT) plans that are less sensitive to uncertainties and superior in terms of organs-at-risk (OARs) sparing, target dose coverage, and homogeneity compared to planning target volume (PTV)-based optimized plans. Robust optimization incorporates setup and range uncertainties, which implicitly adds margins to both targets and OARs and is also able to compensate for perturbations in dose distributions within targets and OARs caused by uncertainties. In contrast, the traditional PTV-based optimization considers only setup uncertainties and adds a margin only to targets but no margins to the OARs. It also ignores range uncertainty. The purpose of this work is to determine if robustly optimized plans are superior to PTV-based plans simply because the latter do not assign margins to OARs during optimization.

METHODS

The authors retrospectively selected from their institutional database five patients with head and neck (H&N) cancer and one with prostate cancer for this analysis. Using their original images and prescriptions, the authors created new IMPT plans using three methods: PTV-based optimization, optimization based on the PTV and planning risk volumes (PRVs) (i.e., "PTV+PRV-based optimization"), and robust optimization using the "worst-case" dose distribution. The PRVs were generated by uniformly expanding OARs by 3 mm for the H&N cases and 5 mm for the prostate case. The dose-volume histograms (DVHs) from the worst-case dose distributions were used to assess and compare plan quality. Families of DVHs for each uncertainty for all structures of interest were plotted along with the nominal DVHs. The width of the "bands" of DVHs was used to quantify the plan sensitivity to uncertainty.

RESULTS

Compared with conventional PTV-based and PTV+PRV-based planning, robust optimization led to a smaller bandwidth for the targets in the face of uncertainties {clinical target volume [CTV] bandwidth: 0.59 [robust], 3.53 [PTV+PRV], and 3.53 [PTV] Gy (RBE)}. It also resulted in higher doses to 95% of the CTV {D(95%): 60.8 [robust] vs 59.3 [PTV+PRV] vs 59.6 [PTV] Gy (RBE)}, smaller D(5%) (doses to 5% of the CTV) minus D(95%) {D(5%) - D(95%): 13.2 [robust] vs 17.5 [PTV+PRV] vs 17.2 [PTV] Gy (RBE)}. At the same time, the robust optimization method irradiated OARs less {maximum dose to 1 cm(3) of the brainstem: 48.3 [robust] vs 48.8 [PTV+PRV] vs 51.2 [PTV] Gy (RBE); mean dose to the oral cavity: 22.3 [robust] vs 22.9 [PTV+PRV] vs 26.1 [PTV] Gy (RBE); maximum dose to 1% of the normal brain: 66.0 [robust] vs 68.0 [PTV+PRV] vs 69.3 [PTV] Gy (RBE)}.

CONCLUSIONS

For H&N cases studied, OAR sparing in PTV+PRV-based optimization was inferior compared to robust optimization but was superior compared to PTV-based optimization; however, target dose robustness and homogeneity were comparable in the PTV+PRV-based and PTV-based optimizations. The same pattern held for the prostate case. The authors' data suggest that the superiority of robust optimization is not due simply to its inclusion of margins for OARs, but that this is due mainly to the ability of robust optimization to compensate for perturbations in dose distributions within target volumes and normal tissues caused by uncertainties.

Statistical assessment of proton treatment plans under setup and range uncertainties

PURPOSE

To evaluate a method for quantifying the effect of setup errors and range uncertainties on dose distribution and dose-volume histogram using statistical parameters; and to assess existing planning practice in selected treatment sites under setup and range uncertainties.

METHODS AND MATERIALS

Twenty passively scattered proton lung cancer plans, 10 prostate, and 1 brain cancer scanning-beam proton plan(s) were analyzed. To account for the dose under uncertainties, we performed a comprehensive simulation in which the dose was recalculated 600 times per given plan under the influence of random and systematic setup errors and proton range errors. On the basis of simulation results, we determined the probability of dose variations and calculated the expected values and standard deviations of dose-volume histograms. The uncertainties in dose were spatially visualized on the planning CT as a probability map of failure to target coverage or overdose of critical structures.

RESULTS

The expected value of target coverage under the uncertainties was consistently lower than that of the nominal value determined from the clinical target volume coverage without setup error or range uncertainty, with a mean difference of -1.1% (-0.9% for breath-hold), -0.3%, and -2.2% for lung, prostate, and a brain cases, respectively. The organs with most sensitive dose under uncertainties were esophagus and spinal cord for lung, rectum for prostate, and brain stem for brain cancer.

CONCLUSIONS

A clinically feasible robustness plan analysis tool based on direct dose calculation and statistical simulation has been developed. Both the expectation value and standard deviation are useful to evaluate the impact of uncertainties. The existing proton beam planning method used in this institution seems to be adequate in terms of target coverage. However, structures that are small in volume or located near the target area showed greater sensitivity to uncertainties.

Early clinical outcomes using proton radiation for children with central nervous system atypical teratoid rhabdoid tumors

PURPOSE

Atypical teratoid/rhabdoid tumor (AT/RT) is an uncommon and aggressive tumor that often affects infants. Irradiation improves survival but has traditionally been avoided in patients under the age of 3 due to the increasing risk of neurocognitive side effects. We report the first cohort of AT/RT patients treated with proton therapy.

METHODS AND MATERIALS

All patients with AT/RT treated at Massachusetts General Hospital (MGH) Frances H. Burr Proton Beam Therapy Benter between July 2004 and November 2011 were included in this study. All patients were treated with 3-dimensional conformal proton therapy (3D-CPT).

RESULTS

Ten consecutive patients of a median 2.3 years of age and with a median follow-up of 27.3 months (range, 11.3-99.4 months) were identified. Two patients suffered distant relapse; 1 patient was successfully treated with involved field irradiation and chemotherapy, while the second patient died of disease. At last follow-up, 9 patients were alive without evidence of disease. Proton radiation demonstrated increasing sparing of the cerebrum, temporal lobe, cochlea, and hypothalamus.

CONCLUSIONS

Initial clinical outcomes with proton therapy are favorable. The advantages of proton therapy are particularly suited to the treatment of AT/RT, a tumor that often requires irradiation treatment at an age when avoiding irradiation to healthy tissues is most desirable.

Fast range-corrected proton dose approximation method using prior dose distribution

For robust plan optimization and evaluation purposes, one needs a computationally efficient way to calculate dose distributions and dose-volume histograms (DVHs) under various changes in the variables associated with beam delivery and images. In this study, we report an approximate method for rapid calculation of dose when setup errors and anatomical changes occur during proton therapy. This fast dose approximation method calculates new dose distributions under various circumstances based on the prior knowledge of dose distribution from a reference setting. In order to validate the method, we calculated and compared the dose distributions from our approximation method to the dose distributions calculated from a clinically commissioned treatment planning system which was used as the ground truth. The overall accuracy of the proposed method was tested against varying degrees of setup error and anatomical deformation for selected patient cases. The setup error was simulated by rigid shifts of the patient; while the anatomical deformation was introduced using weekly acquired repeat CT data sets. We evaluated the agreement between the dose approximation method and full dose recalculation using a 3D gamma index and the root-mean-square (RMS) and maximum deviation of the cumulative dose volume histograms (cDVHs). The average passing rate of 3D gamma analysis under 3% dose and 3 mm distance-to-agreement criteria were 96% and 89% for setup errors and severe anatomy changes, respectively. The average of RMS and maximum deviation of the cDVHs under the setup error was 0.5% and 1.5%, respectively for all structures considered. Similarly, the average of RMS and maximum deviations under the weekly anatomical change were 0.6% and 2.7%, respectively. Our results show that the fast dose approximation method was able to account for the density variation of the patient due to the setup and anatomical changes with acceptable accuracy while significantly improving the computation time.