TriB-RT: Simultaneous optimization of photon, electron and proton beams.

PURPOSE: To develop a novel treatment planning process (TPP) with simultaneous optimization of modulated photon, electron and proton beams for improved treatment plan quality in radiotherapy. METHODS: A framework for fluence map optimization of Monte Carlo (MC) calculated beamlet dose distributions is developed to generate treatment plans consisting of photon, electron and spot scanning proton fields. Initially, in-house intensity modulated proton therapy (IMPT) plans are compared to proton plans created by a commercial treatment planning system (TPS). A triple beam radiotherapy (TriB-RT) plan is generated for an exemplary academic case and the dose contributions of the three particle types are investigated. To investigate the dosimetric potential, a TriB-RT plan is compared to an in-house IMPT plan for two clinically motivated cases. Benefits of TriB-RT for a fixed proton beam line with a single proton field are investigated. RESULTS: In-house optimized IMPT are of at least equal or better quality than TPS-generated proton plans, and MC-based optimization shows dosimetric advantages for inhomogeneous situations. Concerning TriB-RT, for the academic case, the resulting plan shows substantial contribution of all particle types. For the clinically motivated case, improved sparing of organs at risk close to the target volume is achieved compared to IMPT (e.g. myelon and brainstem [Formula: see text] -37%) at cost of an increased low dose bath (healthy tissue V 10% +22%). In the scenario of a fixed proton beam line, TriB-RT plans are able to compensate the loss in degrees of freedom to substantially improve plan quality compared to a single field proton plan. CONCLUSION: A novel TPP which simultaneously optimizes photon, electron and proton beams was successfully developed. TriB-RT shows the potential for improved treatment plan quality and is especially promising for cost-effective single-room proton solutions with a fixed beamline in combination with a conventional linac delivering photon and electron fields.

OPTimizing Irradiation through Molecular Assessment of Lymph node (OPTIMAL): a randomized open label trial.

BACKGROUND: Conservative surgery followed by breast and nodal irradiation is the standard loco-regional early breast cancer (BC) treatment for patients with four or more involved lymph nodes. However, the treatment strategy when fewer nodes are involved remains unclear, especially when lymphadenectomy has not been performed. Sensitive nodal status assessment molecular techniques as the One-Step Nucleic Acid Amplification (OSNA) assay can contribute to the definition and standardization of the treatment strategy. Therefore, the OPTIMAL study aims to demonstrate the feasibility of incidental irradiation of axillary nodes in patients with early-stage BC and limited involvement of the SLN. METHODS: BC patients who underwent conservative surgery and whose SLN total tumour load assessed with OSNA ranged between 250-15,000 copies/µL will be eligible. Patients will be randomized to receive irradiation on the breast, tumour bed, axillary and supraclavicular lymph node areas (intentional arm) or only on the breast and tumour bed (incidental arm). All areas, including the internal mammary chain, will be contoured. The mean, median, D5% and D95% doses received in all volumes will be calculated. The primary endpoint is the non-inferiority of the incidental irradiation of axillary nodes compared to the intentional irradiation in terms of 5-year disease free survival. Secondary endpoints comprise the comparison of acute and chronic toxicity and loco-regional and distant disease recurrence rates. DISCUSSION: Standardizing the treatment and diagnosis of BC patients with few nodes affected is crucial due to the lack of consensus. Hence, the quantitative score for the metastatic burden of SLN provided by OSNA can contribute by improving the discrimination of which BC patients with limited nodal involvement can benefit from incidental radiation as an adjuvant treatment strategy. TRIAL REGISTRATION: ClinicalTrial.gov, NCT02335957; https://clinicaltrials.gov/ct2/show/NCT02335957.

Transitioning from measurement-based to combined patient-specific quality assurance for intensity-modulated proton therapy.

OBJECTIVE: This study is part of ongoing efforts aiming to transit from measurement-based to combined patient-specific quality assurance (PSQA) in intensity-modulated proton therapy (IMPT). A Monte Carlo (MC) dose-calculation algorithm is used to improve the independent dose calculation and to reveal the beam modeling deficiency of the analytical pencil beam (PB) algorithm. METHODS: A set of representative clinical IMPT plans with suboptimal PSQA results were reviewed. Verification plans were recalculated using an MC algorithm developed in-house. Agreements of PB and MC calculations with measurements that quantified by the γ passing rate were compared. RESULTS: The percentage of dose planes that met the clinical criteria for PSQA (>90% γ passing rate using 3%/3 mm criteria) increased from 71.40% in the original PB calculation to 95.14% in the MC recalculation. For fields without beam modifiers, nearly 100% of the dose planes exceeded the 95% γ passing rate threshold using the MC algorithm. The model deficiencies of the PB algorithm were found in the proximal and distal regions of the SOBP, where MC recalculation improved the γ passing rate by 11.27% (p < 0.001) and 16.80% (p < 0.001), respectively. CONCLUSIONS: The MC algorithm substantially improved the γ passing rate for IMPT PSQA. Improved modeling of beam modifiers would enable the use of the MC algorithm for independent dose calculation, completely replacing additional depth measurements in IMPT PSQA program. For current users of the PB algorithm, further improving the long-tail modeling or using MC simulation to generate the dose correction factor is necessary. ADVANCES IN KNOWLEDGE: We justified a change in clinical practice to achieve efficient combined PSQA in IMPT by using the MC algorithm that was experimentally validated in almost all the clinical scenarios in our center. Deficiencies in beam modeling of the current PB algorithm were identified and solutions to improve its dose-calculation accuracy were provided.

VMAT Optimization and Dose Calculation in the Presence of Metallic Hip Prostheses.

INTRODUCTION: This research quantifies and compares the effect of hip prostheses on dose distributions calculated using collapsed cone convolution superposition and Monte Carlo (with and without correcting for the density of the implant and surrounding tissues). The use of full volumetric modulated arc therapy arcs versus volumetric modulated arc therapy arcs avoiding the hip implants (skip arcs) was also studied. MATERIALS AND METHODS: Six prostate patients with hip prostheses were included in this study. The hip prostheses and the streaking artifacts on the computed tomography images were contoured by a single physician, and full volumetric modulated arc therapy arcs were created in the Pinnacle3 TPS. Copies of each plan were made, and the doses were recalculated with the densities of the prostheses and surrounding tissues overridden. The plans were then exported to Monaco and recalculated using a Monte Carlo dose calculation algorithm, with and without densities of the prosthesis and surrounding tissues overridden. RESULTS: With density overrides, Pinnacle3 had a 4.4% error for ion chamber measurements. Monaco was within 0.2% of ion chamber measurement when density overrides were used. On average, when density overrides were used in Pinnacle3 for patient dose calculations, the planning target volume D95 value dropped from 99.3% to 82.7%. Monaco also showed decreased planning target volume coverage when plans were recalculated with correct density information. Full arc plans (with density overrides) for the patient with a bilateral prosthesis provided significant bladder sparing and some rectal sparing compared to skip arc plans. CONCLUSION: When planning for prostate patients with hip prostheses, correct density information for implants and surrounding tissues should be used to optimize the plan and ensure optimal accuracy. If available, a Monte Carlo algorithm should be used as a second check. Full arcs could be used to spare dose to organs at risk, while maintaining adequate planning target volume coverage, when using a Monte Carlo dose calculation algorithm.

Feasibility of a GATE Monte Carlo platform in a clinical pretreatment QA system for VMAT treatment plans using TrueBeam with an HD120 multileaf collimator.

PURPOSE: To evaluate the quality of patient-specific complicated treatment plans, including commercialized treatment planning systems (TPS) and commissioned beam data, we developed a process of quality assurance (QA) using a Monte Carlo (MC) platform. Specifically, we constructed an interface system that automatically converts treatment plan and dose matrix data in digital imaging and communications in medicine to an MC dose-calculation engine. The clinical feasibility of the system was evaluated. MATERIALS AND METHODS: A dose-calculation engine based on GATE v8.1 was embedded in our QA system and in a parallel computing system to significantly reduce the computation time. The QA system automatically converts parameters in volumetric-modulated arc therapy (VMAT) plans to files for dose calculation using GATE. The system then calculates dose maps. Energies of 6 MV, 10 MV, 6 MV flattening filter free (FFF), and 10 MV FFF from a TrueBeam with HD120 were modeled and commissioned. To evaluate the beam models, percentage depth dose (PDD) values, MC calculation profiles, and measured beam data were compared at various depths (Dmax , 5 cm, 10 cm, and 20 cm), field sizes, and energies. To evaluate the feasibility of the QA system for clinical use, doses measured for clinical VMAT plans using films were compared to dose maps calculated using our MC-based QA system. RESULTS: A LINAC QA system was analyzed by PDD and profile according to the secondary collimator and multileaf collimator (MLC). Values for MC calculations and TPS beam data obtained using CC13 ion chamber (IBA Dosimetry, Germany) were consistent within 1.0%. Clinical validation using a gamma index was performed for VMAT treatment plans using a solid water phantom and arbitrary patient data. The gamma evaluation results (with criteria of 3%/3 mm) were 98.1%, 99.1%, 99.2%, and 97.1% for energies of 6 MV, 10 MV, 6 MV FFF, and 10 MV FFF, respectively. CONCLUSIONS: We constructed an MC-based QA system for evaluating patient treatment plans and evaluated its feasibility in clinical practice. We observed robust agreement between dose calculations from our QA system and measurements for VMAT plans. Our QA system could be useful in other clinical settings, such as small-field SRS procedures or analyses of secondary cancer risk, for which dose calculations using TPS are difficult to verify.

The Financial Impact of Fractionation Scheme and Treatment Planning Method for Rectal Cancer in the United States.

BACKGROUND: Preoperative long-course chemoradiotherapy (CRT) and short-course radiotherapy (SCR) for locally advanced rectal cancer (LARC) were found to have equivalent outcomes in 3 randomized trials. SCR has not been widely adopted in the United States (US). Three-dimensional (3D) treatment planning is standard, whereas intensity-modulated radiotherapy (IMRT) is controversial. In this study, we assessed the economic impact of fractionation scheme and planning method for payers in the US. MATERIALS AND METHODS: We performed a population-based analysis of the total cost of radiotherapy for LARC in the US annually. The national annual target population was calculated using the Surveillance, Epidemiology, and End Results database. Radiotherapy costs were based on billing codes and 2018 pricing by Medicare's Hospital Outpatient Prospective Payment System. RESULTS: We estimate that 12,945 patients with LARC are treated with radiotherapy annually in the US. The cost of CRT with 3D or IMRT is US $15,882 and $23,745 per patient, respectively. With SCR, the cost with 3D or IMRT is $5,458 and $7,323 per patient, respectively. The use of SCR would lead to 53% to 77% annual savings of $106,168,871 to $232,105,727 compared with CRT. IMRT increases the total cost of treatment by 34% to 50%, and if adopted widely, would lead to an excess cost of $24,152,134 and $101,784,723 annually with SCR and CRT, respectively. CONCLUSIONS: SCR may have the potential to save approximately US $106 to t232 million annually in the US, likely without impacting outcomes. Lack of evidence showing benefit with costly IMRT should limit its use to clinical trials. It would be reasonable for public and private payers to consider which type of radiation is most suited to reimbursement.

Impact of machine log-files uncertainties on the quality assurance of proton pencil beam scanning treatment delivery.

Irradiation log-files store useful information about the plan delivery, and together with independent Monte Carlo dose engine calculations can be used to reduce the time needed for patient-specific quality assurance (PSQA). Nonetheless, machine log-files carry an uncertainty associated to the measurement of the spot position and intensity that can influence the correct evaluation of the quality of the treatment delivery. This work addresses the problem of the inclusion of these uncertainties for the final verification of the treatment delivery. Dedicated measurements performed in an IBA Proteus Plus gantry with a pencil beam scanning (PBS) dedicated nozzle have been carried out to build a 'room-dependent' model of the spot position uncertainties. The model has been obtained through interpolation of the look-up tables describing the systematic and random uncertainties, and it has been tested for a clinical case of a brain cancer patient irradiated in a dry-run. The delivered dose has been compared with the planned dose with the inclusion of the errors obtained applying the model. Our results suggest that the accuracy of the treatment delivery is higher than the spot position uncertainties obtained from the log-file records. The comparison in terms of DVHs shows that the log-reconstructed dose is compatible with the planned dose within the 95% confidence interval obtained applying our model. The initial mean dose difference between the calculated dose to the patient based on the plan and recorded data is around 1%. The difference is essentially due to the log-file uncertainties and it can be removed with a correct treatment of these errors. In conclusion our new PSQA protocol allows for a fast verification of the dose delivered after every treatment fraction through the use of machine log-files and an independent Monte Carlo dose engine. Moreover, the inclusion of log-file uncertainties in the dose calculation allows for a correct evaluation of the quality of the treatment plan delivery.

Comparison of intensity modulated radiotherapy plan optimisation methods for a 1.5 T MR-Linac.

PURPOSE: For the 1.5 T Elekta MR-Linac it is essential that the optimisation of a treatment plan accounts for the electron return effect on the planned dose distribution. The ability of two algorithms for the first stage fluence optimisation, pencil beam (PB) and Monte Carlo (MC), to produce acceptable plan quality was investigated. Optimisation time for each algorithm was also compared. METHODS: Ten head and neck patients, ten lung patients and five prostate patients were selected from the clinical archive. These were retrospectively planned using a research version of Monaco with both the PB and MC algorithms for the fluence optimisation stage. After full optimisation DVH parameters, optimisation time and the number of Monitor Units (MU) as a measure of plan complexity were extracted. RESULTS: There were no clinically significant differences between any of the DVH parameters studied or the total number of MUs between using PB or MC for stage 1 optimisation across the three patient groups. However, planning time increased by a factor of ten using MC algorithms for stage 1. CONCLUSION: The use of MC calculations compared to PB, for stage 1 fluence optimisation, results in increased planning time without clinical improvement in plan quality or reduction in complexity and is therefore not necessary.

Assessment of the modulation degrees of intensity-modulated radiation therapy plans.

BACKGROUND: To evaluate the modulation indices (MIs) for predicting the plan delivery accuracies of intensity-modulated radiation therapy (IMRT) plans. METHODS: A total of 100 dynamic IMRT plans that used TrueBeam STx and 102 dynamic IMRT plans that used Trilogy were selected. For each plan, various MIs were calculated, which included the modulation complexity score (MCS), plan-averaged beam area (PA), plan-averaged beam irregularity (PI), plan-averaged beam modulation (PM), MI quantifying multi-leaf collimator (MLC) speeds (MIs), MI quantifying MLC acceleration (MIa), and MI quantifying MLC acceleration and segment aperture irregularity (MIc,IMRT). To determine plan delivery accuracy, global gamma passing rates, MLC errors of log files, and dose-volumetric parameter differences between original and log file-reconstructed IMRT plans were obtained. To assess the ability of each MI for predicting plan delivery accuracy, Spearman's rank correlation coefficients (rs) between MIs and plan delivery accuracy measures were calculated. RESULTS: PI showed moderately strong correlations with gamma passing rates in MapCHECK2 measurements of both TrueBeam STx and Trilogy (rs = - 0.591 with p <  0.001 and - 0.427 with p <  0.001 to with gamma criterion of 2%/2 mm, respectively). For ArcCHECK measurements, PI also showed moderately strong correlations with the gamma passing rates in the ArcCHECK measurements of TrueBeam STx and Trilogy (rs = - 0.545 with p <  0.001 and rs = - 0.581 with p <  0.001 with gamma criterion of 2%/2 mm, respectively). The PI showed the second strongest correlation with MLC errors in both TrueBeam STx and Trilogy (rs = 0.861 with p <  0.001 and rs = 0.767 with p <  0.001, respectively). In general, the PI showed moderately strong correlations with every plan delivery accuracy measure. CONCLUSIONS: The PI showed moderately strong correlations with every plan delivery accuracy measure and therefore is a useful predictor of IMRT delivery accuracy.

Assessment of combined use of ArcCheck® detector and portal dosimetry for delivery quality assurance of head and neck and prostate volumetric-modulated arc therapy.

PURPOSE: To assess the efficiency of combined use of ArcCheck® detector (AC) and portal dosimetry (PDIP) for delivery quality assurance of head and neck and prostate volumetric-modulated arc therapy. MATERIALS AND METHODS: Measurement processes were studied with the Gamma index method according to three analysis protocols. The detection sensitivity to technical errors of each individual or combined measurement processes was studied by inserting collimator, dose and MLC opening error into five head and neck and five prostate initial treatment plans. A total of 220 plans were created and 660 analyses were conducted by comparing measurements to error free planned dose matrix. RESULTS: For head and neck localization, collimator errors could be detected from 2° for AC and 3° for PDIP. Dose and MLC errors could be detected from 2% and 0.5 mm for AC and PDIP. Depending on the analysis protocol, the detection sensitivity of total simulated errors ranged from 54% to 88% for AC vs 40% to 74% for PDIP and 58% to 92% for the combined process. For the prostate localization, collimator errors could be detected from 4° for AC while they could not be detected by PDIP. Dose and MLC errors could be detected from 3% and 0.5 mm for AC and PDIP. The detection sensitivity of total simulated errors ranged from 30% to 56% for AC vs 16% to 38% for PDIP and 30% to 58% for combined process. CONCLUSION: The combined use of the two measurement processes did not statistically improve the detectability of technical errors compared to use of single process.

Assessment of accuracy of out-of-field dose calculations by TiGRT treatment planning system in radiotherapy.

AIM: The objective was to quantify the accuracy of dose calculation for out-of-field regions by the commercially available TiGRT version 1.2 (LinaTech, Sunnyvale, CA, USA) treatment planning system (TPS) for a clinical treatment delivered on a Siemens Primus with the single energy of 6 MV. MATERIALS AND METHODS: Two tangential open fields were planned by TiGRT TPS to irradiate the left breast of a RANDO phantom. Dose values to out-of-field points were calculated by TiGRT TPS. A RANDO phantom was then irradiated, and dose values at set points were measured using thermoluminescent detectors-100 (TLDs-100) which were located within the phantom. Finally, the TLD-measured dose was compared to the TPS-calculated dose and the accuracy of TPS calculations at different distances from the field edge was quantified. RESULTS: The measurements showed that TiGRT TPS generally underestimated the dose of out-of-field points and this underestimation worsened for regions relatively close to the treatment field edge. The mean underestimation of out-of-field doses was 39%. Nevertheless, the accuracy of dose calculation by this TPS for most in-field regions was within tolerance. CONCLUSION: This study highlights the limitations of TiGRT TPSs in calculating of the out-of-field dose. It should be noted that out-of-field data for this TPS should only be applied with a certain understanding of the accuracy of calculated dose outside the treatment field. Therefore, using the TPS-calculated dose could lead to an underestimation of secondary cancer risk as well as a weak clinical decision for patients with implantable cardiac pacemakers or pregnant patients.

Monte Carlo tree search -based non-coplanar trajectory design for station parameter optimized radiation therapy (SPORT).

An important yet challenging problem in LINAC-based rotational arc radiation therapy is the design of beam trajectory, which requires simultaneous consideration of delivery efficiency and final dose distribution. In this work, we propose a novel trajectory selection strategy by developing a Monte Carlo tree search (MCTS) algorithm during the beam trajectory selection process. To search through the vast number of possible trajectories, the MCTS algorithm was implemented. In this approach, a candidate trajectory is explored by starting from a leaf node and sequentially examining the next level of linked nodes with consideration of geometric and physical constraints. The maximum Upper Confidence Bounds for Trees, which is a function of average objective function value and the number of times the node under testing has been visited, was employed to intelligently select the trajectory. For each candidate trajectory, we run an inverse fluence map optimization with an infinity norm regularization. The ranking of the plan as measured by the corresponding objective function value was then fed back to update the statistics of the nodes on the trajectory. The method was evaluated with a chest wall and a brain case, and the results were compared with the coplanar and noncoplanar 4pi beam configurations. For both clinical cases, the MCTS method found effective and easy-to-deliver trajectories within an hour. As compared with the coplanar plans, it offers much better sparing of the OARs while maintaining the PTV coverage. The quality of the MCTS-generated plan is found to be comparable to the 4pi plans. Artificial intelligence based on MCTS is valuable to facilitate the design of beam trajectory and paves the way for future clinical use of non-coplanar treatment delivery.

Can differences in linear energy transfer and thus relative biological effectiveness compromise the dosimetric advantage of intensity-modulated proton therapy as compared to passively scattered proton therapy?

PURPOSE: To investigate the effect of differences in linear energy transfer (LET) and thus the relative biological effectiveness (RBE) between passively scattered proton therapy (PS) and pencil-beam scanning intensity-modulated proton therapy (IMPT). METHODS: IMPT treatment plans were generated for six ependymoma patients, originally treated with PS, using the original plan's computed tomography image sets and beam directions, and its dose-volume values as optimization constraints. Two beam spot sizes and both single-field optimization (SFO) and multi-field optimization (MFO) techniques were used for each patient. Three-dimensional variable-RBE-weighted dose distributions were computed, using Monte Carlo calculated dose and LET distributions, and a linear dose and LET-based RBE model, and were compared between the two delivery methods. RESULTS: Increased target dose coverage and decreased mean and maximum dose to the OARs was achieved with IMPT compared to PS, for constant RBE value of 1.1. Nevertheless, the maximum variable-RBE-weighted dose to the brainstem, was increased up to 6% for the IMPT plans compared to the corresponding PS plans. CONCLUSIONS: IMPT can be dosimetrically superior to PS for ependymoma patients. However, caution should be exercised so that the increased dose conformity is not counteracted by an increase in radiobiological effect in adjacent critical structures.

Hippocampus-sparing radiotherapy using volumetric modulated arc therapy (VMAT) to the primary brain tumor: the result of dosimetric study and neurocognitive function assessment.

BACKGROUND: We hypothesized that hippocampal-sparing radiotherapy via volumetric modulated arc therapy (VMAT) could preserve the neurocognitive function (NCF) of patients with primary brain tumors treated with radiotherapy. METHODS: We reviewed data from patients with primary brain tumors who underwent hippocampal-sparing brain radiotherapy via VMAT between February 2014 and December 2015. The optimization criteria for the contralateral hippocampus was a maximum dose (Dmax) of less than 17 Gy. For NCF evaluations, the Seoul Verbal Learning Test for total recall, delayed recall, and recognition (SVLT-TR, DR, and Recognition) was performed at baseline and at seven months after radiotherapy. RESULTS: A total of 26 patients underwent NCF testing seven months after radiotherapy. Their median age was 49.5 years (range 26-77 years), and 14 (53.8%) had grade III/IV tumors. The median Dmax to the contralateral hippocampus was 16.4 Gy (range 3.5-63.4). The median mean dose to the contralateral hippocampus, expressed as equivalent to a 2-Gy dose (EQD2/2), was 7.4 Gy2 (0.7-13.1). The mean relative changes in SVLT-TR, SVLT-DR, and SVLT-Recognition at seven months compared to the baseline were - 7.7% (95% confidence interval [CI], - 19.6% to 4.2%), - 9.2% (95% CI, - 25.4% to 7.0%), and - 3.4% (- 12.7% to 5.8%), respectively. Two patients (7.7%) showed deteriorated NCF in the SVLT-TR and SVLT-DR, and three (11.5%) in the SVLT-Recognition. The mean dose of the left hippocampus and bilateral hippocampi were significantly higher in patients showing deterioration of the SVLT-TR and SVLT-Recognition than in those without deterioration. CONCLUSIONS: The contralateral hippocampus could be effectively spared in patients with primary brain tumor via VMAT to preserve the verbal memory function. Further investigation is needed to identify those patients who will most benefit from hippocampal-sparing radiotherapy of the primary brain tumor.

Optimizing the prescription isodose level in stereotactic volumetric-modulated arc radiotherapy of lung lesions as a potential for dose de-escalation.

BACKGROUND: To derive and exploit the optimal prescription isodose level (PIL) in inverse optimization of volumetric modulated arc radiotherapy (VMAT) as a potential approach to dose de-escalation in stereotactic body radiotherapy for non-small cell lung carcinomas (NSCLC). METHODS: For ten patients, inverse Monte Carlo dose optimization was performed to cover 95% PTV by varying prescription isodose lines (PIL) at 60 to 80% and reference 85%. Subsequently, these were re-normalized to the median gross tumor volume dose (GTV-based prescription) to assess the impacts of PTV and normal tissue dose reduction. RESULTS: With PTV-based prescription, GTV mean dose was much higher with the optimized PIL at 60% with significant reduction of normal lung receiving 30 to 10 Gy (V 30-10Gy ), and observable but insignificant dose reduction to spinal cord, esophagus, ribs, and others compared with 85% PIL. Mean doses to the normal lung between PTV and GTV was higher with 60-70% PIL than 85%. The dose gradient index was 5.0 ± 1.1 and 6.1 ± 1.4 for 60 and 85% PIL (p < 0.05), respectively. Compared with the reference 85% PIL plan using PTV-base prescription, significant decreases of all normal tissue doses were observed with 60% and 70% PIL by GTV-based prescription. Yet, the resulting biological effective (BED) mean doses of PTV remain sufficiently high, ranging 104.2 to 116.9 Gy α/ß = 10. CONCLUSIONS: Optimizing the PIL with VMAT has notable advantage of improving the dosimetric quality of lung SBRT and offers the potential of dose de-escalation for surrounding tissues while increasing the GTV dose simultaneously. The clinical implication of re-normalizing plans from PTV-prescription at 60-70% to the GTV median dose requires further investigations.

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PURPOSE: One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. METHODS AND MATERIALS: The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. RESULTS: Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. CONCLUSIONS: We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame.

Quantifying the effect of air gap, depth, and range shifter thickness on TPS dosimetric accuracy in superficial PBS proton therapy.

This study quantifies the dosimetric accuracy of a commercial treatment planning system as functions of treatment depth, air gap, and range shifter thickness for superficial pencil beam scanning proton therapy treatments. The RayStation 6 pencil beam and Monte Carlo dose engines were each used to calculate the dose distributions for a single treatment plan with varying range shifter air gaps. Central axis dose values extracted from each of the calculated plans were compared to dose values measured with a calibrated PTW Markus chamber at various depths in RW3 solid water. Dose was measured at 12 depths, ranging from the surface to 5 cm, for each of the 18 different air gaps, which ranged from 0.5 to 28 cm. TPS dosimetric accuracy, defined as the ratio of calculated dose relative to the measured dose, was plotted as functions of depth and air gap for the pencil beam and Monte Carlo dose algorithms. The accuracy of the TPS pencil beam dose algorithm was found to be clinically unacceptable at depths shallower than 3 cm with air gaps wider than 10 cm, and increased range shifter thickness only added to the dosimetric inaccuracy of the pencil beam algorithm. Each configuration calculated with Monte Carlo was determined to be clinically acceptable. Further comparisons of the Monte Carlo dose algorithm to the measured spread-out Bragg Peaks of multiple fields used during machine commissioning verified the dosimetric accuracy of Monte Carlo in a variety of beam energies and field sizes. Discrepancies between measured and TPS calculated dose values can mainly be attributed to the ability (or lack thereof) of the TPS pencil beam dose algorithm to properly model secondary proton scatter generated in the range shifter.

A clinical database to assess action levels and tolerances for the ongoing use of Mobius3D.

In radiation therapy, calculation of dose within the patient contains inherent uncertainties, inaccuracies, limitations, and the potential for random error. Thus, point dose-independent verification of such calculations is a well-established process, with published data to support the setting of both action levels and tolerances. Mobius3D takes this process one step further with a full independent calculation of patient dose and comparisons of clinical parameters such as mean target dose and voxel-by-voxel gamma analysis. There is currently no published data to directly inform tolerance levels for such parameters, and therefore this work presents a database of 1000 Mobius3D results to fill this gap. The data are tested for normality using a normal probability plot and found to fit this distribution for three sub groups of data; Eclipse, iPlan and the treatment site Lung. The mean (µ) and standard deviation (σ) of these sub groups is used to set action levels and tolerances at µ ± 2σ and µ ± 3σ, respectively. A global (3%, 3 mm) gamma tolerance is set at 88.5%. The mean target dose tolerance for Eclipse data is the narrowest at ± 3%, whilst iPlan and Lung have a range of -5.0 to 2.2% and -1.8 to 5.0%, respectively. With these limits in place, future results failing the action level or tolerance will fall within the worst 5% and 1% of historical results and an informed decision can be made regarding remedial action prior to treatment.

On the new metrics for IMRT QA verification.

PURPOSE: The aim of this work is to search for new metrics that could give more reliable acceptance/rejection criteria on the IMRT verification process and to offer solutions to the discrepancies found among different conventional metrics. Therefore, besides conventional metrics, new ones are proposed and evaluated with new tools to find correlations among them. These new metrics are based on the processing of the dose-volume histogram information, evaluating the absorbed dose differences, the dose constraint fulfillment, or modified biomathematical treatment outcome models such as tumor control probability (TCP) and normal tissue complication probability (NTCP). An additional purpose is to establish whether the new metrics yield the same acceptance/rejection plan distribution as the conventional ones. METHODS: Fifty eight treatment plans concerning several patient locations are analyzed. All of them were verified prior to the treatment, using conventional metrics, and retrospectively after the treatment with the new metrics. These new metrics include the definition of three continuous functions, based on dose-volume histograms resulting from measurements evaluated with a reconstructed dose system and also with a Monte Carlo redundant calculation. The 3D gamma function for every volume of interest is also calculated. The information is also processed to obtain ΔTCP or ΔNTCP for the considered volumes of interest. These biomathematical treatment outcome models have been modified to increase their sensitivity to dose changes. A robustness index from a radiobiological point of view is defined to classify plans in robustness against dose changes. RESULTS: Dose difference metrics can be condensed in a single parameter: the dose difference global function, with an optimal cutoff that can be determined from a receiver operating characteristics (ROC) analysis of the metric. It is not always possible to correlate differences in biomathematical treatment outcome models with dose difference metrics. This is due to the fact that the dose constraint is often far from the dose that has an actual impact on the radiobiological model, and therefore, biomathematical treatment outcome models are insensitive to big dose differences between the verification system and the treatment planning system. As an alternative, the use of modified radiobiological models which provides a better correlation is proposed. In any case, it is better to choose robust plans from a radiobiological point of view. The robustness index defined in this work is a good predictor of the plan rejection probability according to metrics derived from modified radiobiological models. The global 3D gamma-based metric calculated for each plan volume shows a good correlation with the dose difference metrics and presents a good performance in the acceptance/rejection process. Some discrepancies have been found in dose reconstruction depending on the algorithm employed. Significant and unavoidable discrepancies were found between the conventional metrics and the new ones. CONCLUSIONS: The dose difference global function and the 3D gamma for each plan volume are good classifiers regarding dose difference metrics. ROC analysis is useful to evaluate the predictive power of the new metrics. The correlation between biomathematical treatment outcome models and the dose difference-based metrics is enhanced by using modified TCP and NTCP functions that take into account the dose constraints for each plan. The robustness index is useful to evaluate if a plan is likely to be rejected. Conventional verification should be replaced by the new metrics, which are clinically more relevant.