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Lung IMRT planning with automatic determination of beam angle configurations.

ABSTRACT: Beam angle configuration is a major planning decision in intensity modulated radiation treatment (IMRT) that has a significant impact on dose distributions and thus quality of treatment, especially in complex planning cases such as those for lung cancer treatment. We propose a novel method to automatically determine beam configurations that incorporates noncoplanar beams. We then present a completely automated IMRT planning algorithm that combines the proposed method with a previously reported OAR DVH prediction model. Finally, we validate this completely automatic planning algorithm using a set of challenging lung IMRT cases. A beam efficiency index map is constructed to guide the selection of beam angles. This index takes into account both the dose contributions from individual beams and the combined effect of multiple beams by introducing a beam-spread term. The effect of the beam-spread term on plan quality was studied systematically and the weight of the term to balance PTV dose conformity against OAR avoidance was determined. For validation, complex lung cases with clinical IMRT plans that required the use of one or more noncoplanar beams were re-planned with the proposed automatic planning algorithm. Important dose metrics for the PTV and OARs in the automatic plans were compared with those of the clinical plans. The results are very encouraging. The PTV dose conformity and homogeneity in the automatic plans improved significantly. And all the dose metrics of the automatic plans, except the lung V5 Gy, were statistically better than or comparable with those of the clinical plans. In conclusion, the automatic planning algorithm can incorporate non-coplanar beam configurations in challenging lung cases and can generate plans efficiently with quality closely approximating that of clinical plans.

SUBMITTER: Yuan L

PROVIDER: S-EPMC6691500 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Lung IMRT planning with automatic determination of beam angle configurations.

Yuan Lulin L Zhu Wei W Ge Yaorong Y Jiang Yuliang Y Sheng Yang Y Yin Fang-Fang FF Wu Q Jackie QJ

Physics in medicine and biology 20180706 13

Beam angle configuration is a major planning decision in intensity modulated radiation treatment (IMRT) that has a significant impact on dose distributions and thus quality of treatment, especially in complex planning cases such as those for lung cancer treatment. We propose a novel method to automatically determine beam configurations that incorporates noncoplanar beams. We then present a completely automated IMRT planning algorithm that combines the proposed method with a previously reported O ...[more]

PMID: 29846178

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Project description:Purpose To develop and evaluate an integrated solution for automatic intensity-modulated radiation therapy (IMRT) planning in non-small-cell lung cancer (NSCLC) cases. Methods A novel algorithm named as multi-objectives adjustment policy network (MOAPN) was proposed and trained to learn how to adjust multiple optimization objectives in commercial Eclipse treatment planning system (TPS), based on the multi-agent deep reinforcement learning (DRL) scheme. Furthermore, a three-dimensional (3D) dose prediction module was developed to generate the patient-specific initial optimization objectives to reduce the overall exploration space during MOAPN training. 114 previously treated NSCLC cases suitable for stereotactic body radiotherapy (SBRT) were selected from the clinical database. 87 cases were used for the model training, and the remaining 27 cases for evaluating the feasibility and effectiveness of MOAPN in automatic treatment planning. Results For all tested cases, the average number of adjustment steps was 21 ± 5.9 (mean ± 1 standard deviation). Compared with the MOAPN initial plans, the actual dose of chest wall, spinal cord, heart, lung (affected side), esophagus and bronchus in the MOAPN final plans reduced by 14.5%, 11.6%, 4.7%, 16.7%, 1.6% and 7.7%, respectively. The dose result of OARs in the MOAPN final plans was similar to those in the clinical plans. The complete automatic treatment plan for a new case was generated based on the integrated solution, with about 5-6 min. Conclusion We successfully developed an integrated solution for automatic treatment planning. Using the 3D dose prediction module to obtain the patient-specific optimization objectives, MOAPN formed action-value policy can simultaneously adjust multiple objectives to obtain a high-quality plan in a shorter time. This integrated solution contributes to improving the efficiency of the overall planning workflow and reducing the variation of plan quality in different regions and treatment centers. Although improvement is warranted, this proof-of-concept study has demonstrated the feasibility of this integrated solution in automatic treatment planning based on the Eclipse TPS.

Project description:Volumetric-modulated arc therapy (VMAT) is emerging as a leading technology in treating early-stage, non-small cell lung cancer (NSCLC) with stereotactic ablative radiotherapy (SABR). However, two other modalities capable of deliver-ing intensity-modulated radiation therapy (IMRT) include fixed-beam and helical TomoTherapy (HT). This study aims to provide an extensive dosimetric compari-son among these various IMRT techniques for treating early-stage NSCLC with SABR. Ten early-stage NSCLC patients were retrospectively optimized using three fixed-beam techniques via nine to eleven beams (high and low modulation step-and-shoot (SS), and sliding window (SW)), two VMAT techniques via two partial arcs (SmartArc (SA) and RapidArc (RA)), and three HT techniques via three different fan beam widths (1 cm, 2.5 cm, and 5 cm) for 80 plans total. Fixed-beam and VMAT plans were generated using flattening filter-free beams. SS and SA, HT treatment plans, and SW and RA were optimized using Pinnacle v9.1, Tomoplan v.3.1.1, and Eclipse (Acuros XB v11.3 algorithm), respectively. Dose-volume histogram statistics, dose conformality, and treatment delivery efficiency were analyzed. VMAT treatment plans achieved significantly lower values for contralat-eral lung V5Gy (p ? 0.05) compared to the HT plans, and significantly lower mean lung dose (p < 0.006) compared to HT 5 cm treatment plans. In the comparison between the VMAT techniques, a significant reduction in the total monitor units (p = 0.05) was found in the SA plans, while a significant decrease was observed in the dose falloff parameter, D2cm, (p = 0.05), for the RA treatments. The maximum cord dose was significantly reduced (p = 0.017) in grouped RA&SA plans com-pared to SS. Estimated treatment time was significantly higher for HT and fixed-beam plans compared to RA&SA (p < 0.001). Although, a significant difference was not observed in the RA vs. SA (p = 0.393). RA&SA outperformed HT in all parameters measured. Despite an increase in dose to the heart and bronchus, this study demonstrates that VMAT is dosimetrically advantageous in treating early-stage NSCLC with SABR compared to fixed-beam, while providing significantly shorter treatment times.

Project description:Beam angle optimization (BAO) by far remains an important and challenging problem in external beam radiation therapy treatment planning. Conventional BAO algorithms discussed in previous studies all focused on photon-based therapies. Impact of BAO on proton therapy is important while proton therapy increasingly receives great interests. This study focuses on potential benefits of BAO on intensity-modulated proton therapy (IMPT) that recently began available to clinical cancer treatment.The authors have developed a novel uncertainty incorporated BAO algorithm for IMPT treatment planning in that IMPT plan quality is highly sensitive to uncertainties such as proton range and setup errors. A linear programming was used to optimize robust intensity maps to scenario-based uncertainties for an incident beam angle configuration. Unlike conventional intensity-modulated radiation therapy with photons (IMXT), the search space for IMPT treatment beam angles may be relatively small but optimizing an IMPT plan may require higher computational costs due to larger data size. Therefore, a deterministic local neighborhood search algorithm that only needs a very limited number of plan objective evaluations was used to optimize beam angles in IMPT treatment planning.Three prostate cancer cases and two skull base chordoma cases were studied to demonstrate the dosimetric advantages and robustness of optimized beam angles from the proposed BAO algorithm. Two- to four-beam plans were optimized for prostate cases, and two- and three-beam plans were optimized for skull base cases. By comparing plans with conventional two parallel-opposed angles, all plans with optimized angles consistently improved sparing at organs at risks, i.e., rectum and femoral heads for prostate, brainstem for skull base, in either nominal dose distribution or uncertainty-based dose distributions. The efficiency of the BAO algorithm was demonstrated by comparing it with alternative methods including simulated annealing and genetic algorithm. The numbers of IMPT plan objective evaluations required were reduced by up to a factor of 5 while the same optimal angle plans were converged in selected comparisons.Uncertainty incorporated BAO may introduce pronounced improvement of IMPT plan quality including dosimetric benefits and robustness over uncertainties, based on the five clinical studies in this paper. In addition, local search algorithms may be more efficient in finding optimal beam angles than global optimization approaches for IMPT BAO.

Project description:Background:Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. Methods:With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. Results:In this ten-patient sample, CTV V95 decreased significantly from 99-100% for PBopt to 77-94% for MCrecalc and recovered to 99-100% for MCopt (P<10-5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10-3). CTV D95 robustness to range and setup errors improved under MCopt (?D95 =-1%) compared to MCrecalc (?D95 =-6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10-3). Conclusions:MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.

Project description:PurposeThere are limited clinical data on scanning-beam proton therapy (SPT) in treating locally advanced lung cancer, as most published studies have used passive-scatter technology. There is increasing interest in whether the dosimetric advantages of SPT compared with photon therapy can translate into superior clinical outcomes. We present our experience of SPT and photon intensity modulated radiation therapy (IMRT) with clinical dosimetry and outcomes in patients with stage III lung cancer.Methods and materialsPatients with stage III lung cancer treated at our center between 2013 and May 2018 were identified in compliance with our institutional review board (64 patients = 34 SPT + 30 IMRT). Most proton patients were treated with pencil beam scanning (28 of 34), and 6 of 34 were treated with uniform scanning. Fisher exact test, χ2 test, and Mann-Whitney test were used to compare groups. All tests were 2-sided.ResultsPatient characteristics were similar between the IMRT and SPT patients, except for worse lung function in the IMRT group. Mean dose to lung, heart, and esophagus was lower in the SPT group, with most benefit in the low-dose region (lungs, 9.7 Gy vs 15.7 Gy for SPT vs IMRT, respectively [P = .004]; heart, 7 Gy vs 14 Gy [P = .001]; esophagus, 28.2 Gy vs 30.9 Gy [P = .023]). Esophagitis and dermatitis grades were not different between the 2 groups. Grade 2+ pneumonitis was 21% in the SPT group and 40% in the IMRT group (P = .107). Changes in blood counts were not different between the 2 groups. Overall survival and progression-free survival were not different between SPT and IMRT (median overall survival, 41.6 vs 30.7 months, respectively [P = .52]; median progression-free survival, 19.5 vs 14.6 months [P = .50]).ConclusionsWe report our experience with SPT and IMRT in stage III lung cancer. Our cohort of patients treated with SPT had lower doses to normal organs (lungs, heart, esophagus) than our IMRT cohort. There was no statistically significant difference in toxicity rates or survival, although there may have been a trend toward lower rates of pneumonitis.

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Lung IMRT planning with automatic determination of beam angle configurations.

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Lung IMRT planning with automatic determination of beam angle configurations.

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