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Automated planning through robust templates and multicriterial optimization for lung VMAT SBRT of lung lesions.

ABSTRACT: PURPOSE:To develop and validate a robust template for VMAT SBRT of lung lesions, using the multicriterial optimization (MCO) of a commercial treatment planning system. METHODS:The template was established and refined on 10 lung SBRT patients planned for 55 Gy/5 fr. To improve gradient and conformity a ring structure around the planning target volume (PTV) was set in the list of objectives. Ideal fluence optimization was conducted giving priority to organs at risk (OARs) and using the MCO, which further pushes OARs doses. Segmentation was conducted giving priority to PTV coverage. Two different templates were produced with different degrees of modulation, by setting the Fluence Smoothing parameter to Medium (MFS) and High (HFS). Each template was applied on 20 further patients. Automatic and manual plans were compared in terms of dosimetric parameters, delivery time, and complexity. Statistical significance of differences was evaluated using paired two-sided Wilcoxon signed-rank test. RESULTS:No statistically significant differences in PTV coverage and maximum dose were observed, while an improvement was observed in gradient and conformity. A general improvement in dose to OARs was seen, which resulted to be significant for chest wall V30 Gy , total lung V20 Gy , and spinal cord D0.1 cc . MFS plans are characterized by a higher modulation and longer delivery time than manual plans. HFS plans have a modulation and a delivery time comparable to manual plans, but still present an advantage in terms of gradient. CONCLUSION:The automation of the planning process for lung SBRT using robust templates and MCO was demonstrated to be feasible and more efficient.

SUBMITTER: Marrazzo L

PROVIDER: S-EPMC7324702 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Automated planning through robust templates and multicriterial optimization for lung VMAT SBRT of lung lesions.

Marrazzo Livia L Arilli Chiara C Pellegrini Roberto R Bonomo Pierluigi P Calusi Silvia S Talamonti Cinzia C Casati Marta M Compagnucci Antonella A Livi Lorenzo L Pallotta Stefania S

Journal of applied clinical medical physics 20200410 6

<h4>Purpose</h4>To develop and validate a robust template for VMAT SBRT of lung lesions, using the multicriterial optimization (MCO) of a commercial treatment planning system.<h4>Methods</h4>The template was established and refined on 10 lung SBRT patients planned for 55 Gy/5 fr. To improve gradient and conformity a ring structure around the planning target volume (PTV) was set in the list of objectives. Ideal fluence optimization was conducted giving priority to organs at risk (OARs) and using ...[more]

PMID: 32275353

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Project description:Postoperative/adjuvant radiotherapy of advanced gastric cancer involves a large planning target volume (PTV) with multi-concave shapes which presents a challenge for volumetric modulated arc therapy (VMAT) planning. This study investigates the advantages of automated VMAT planning for this site compared to manual VMAT planning by expert planners.For 20 gastric cancer patients in the postoperative/adjuvant setting, dual-arc VMAT plans were generated using fully automated multi-criterial treatment planning (autoVMAT), and compared to manually generated VMAT plans (manVMAT). Both automated and manual plans were created to deliver a median dose of 45 Gy to the PTV using identical planning and segmentation parameters. Plans were evaluated by two expert radiation oncologists for clinical acceptability. AutoVMAT and manVMAT plans were also compared based on dose-volume histogram (DVH) and predicted normal tissue complication probability (NTCP) analysis.Both manVMAT and autoVMAT plans were considered clinically acceptable. Target coverage was similar (manVMAT: 96.6?±?1.6%, autoVMAT: 97.4?±?1.0%, p?=?0.085). With autoVMAT, median kidney dose was reduced on average by >?25%; (for left kidney from 11.3?±?2.1 Gy to 8.9?±?3.5 Gy (p?=?0.002); for right kidney from 9.2?±?2.2 Gy to 6.1?±?1.3 Gy (p?<? 0.001)). Median dose to the liver was lower as well (18.8?±?2.3 Gy vs. 17.1?±?3.6 Gy, p?=?0.048). In addition, Dmax of the spinal cord was significantly reduced (38.3?±?3.7 Gy vs. 31.6?±?2.6 Gy, p?<? 0.001). Substantial improvements in dose conformity and integral dose were achieved with autoVMAT plans (4.2% and 9.1%, respectively; p?<? 0.001). Due to the better OAR sparing in the autoVMAT plans compared to manVMAT plans, the predicted NTCPs for the left and right kidney and the liver-PTV were significantly reduced by 11.3%, 12.8%, 7%, respectively (p???0.001). Delivery time and total number of monitor units were increased in autoVMAT plans (from 168?±?19 s to 207?±?26 s, p?=?0.006) and (from 781?±?168 MU to 1001?±?134 MU, p?=?0.003), respectively.For postoperative/adjuvant radiotherapy of advanced gastric cancer, involving a complex target shape, automated VMAT planning is feasible and can substantially reduce the dose to the kidneys and the liver, without compromising the target dose delivery.

Project description: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.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.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)}.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.

Project description:AimsIn patients undergoing locoregional radiotherapy (RT) for breast cancer including the internal mammary chain (IMC), VMAT has been shown to be superior to tangential-field radiotherapy in terms of target coverage and minimising dose to heart and lungs. In this study we describe and validate organ motion-based robust optimisation for generating breast and locoregional lymph node VMAT plans that are robust to inter-fractional changes.Materials and methodsIn this retrospective study of five patients with left-sided breast cancer requiring locoregional breast radiotherapy including the IMC, non-robust plans were generated in the nominal scenario (planning-CT) and corresponding robust plans were created by optimising over a range of simulated CTs representing worst-case scenario shape changes to the breast. Both plans were re-calculated on CBCT images (n = 67) acquired prior to RT to generate estimates of delivered fractional dose. Plan robustness to inter-fractional changes was assessed in terms of the estimated target coverage and OAR dose.ResultsOrgan motion-based robust optimisation was able to generate clinically acceptable treatment plans in the nominal scenario on the planning CT with no significant differences to OAR dose between the robust and non-robust planning techniques. All plans (robust and non-robust) achieved the mandatory target coverage requirements. Estimates of delivered dose demonstrated a significant improvement in breast target coverage for the robust plans compared to non-robust plans. For the breast CTV, 92% of the robust plans achieved the optimal D98% > 95% clinical goal as compared to 71% of the non-robust plans (p < 0.01). 94% of robust plans achieved acceptable superficial breast coverage, as compared to 55% for the non-robust technique.ConclusionsOrgan motion-based robust optimisation VMAT is able to produce clinically acceptable organ-at-risk sparing plans for locoregional breast radiotherapy (including the IMC) that are robust to inter-fractional changes, therefore reducing the likelihood of reactive adaptive re-planning.

Project description:PURPOSE:To develop and implement a fully automated approach to intensity modulated radiation therapy (IMRT) treatment planning. METHOD:The optimization algorithm is developed based on a hierarchical constrained optimization technique and is referred internally at our institution as expedited constrained hierarchical optimization (ECHO). Beamlet contributions to regions-of-interest are precomputed and captured in the influence matrix. Planning goals are of two classes: hard constraints that are strictly enforced from the first step (e.g., maximum dose to spinal cord), and desirable goals that are sequentially introduced in three constrained optimization problems (better planning target volume (PTV) coverage, lower organ at risk (OAR) doses, and smoother fluence map). After solving the optimization problems using external commercial optimization engines, the optimal fluence map is imported into an FDA-approved treatment planning system (TPS) for leaf sequencing and accurate full dose calculation. The dose-discrepancy between the optimization and TPS dose calculation is then calculated and incorporated into optimization by a novel dose correction loop technique using Lagrange multipliers. The correction loop incorporates the leaf sequencing and scattering effects into optimization to improve the plan quality and reduce the calculation time. The resultant optimal fluence map is again imported into TPS for leaf sequencing and final dose calculation for plan evaluation and delivery. The workflow is automated using application program interface (API) scripting, requiring user interaction solely to prepare the contours and beam arrangement prior to launching the ECHO plug-in from the TPS. For each site, parameters and objective functions are chosen to represent clinical priorities. The first site chosen for clinical implementation was metastatic paraspinal lesions treated with stereotactic body radiotherapy (SBRT). As a first step, 75 ECHO paraspinal plans were generated retrospectively and compared with clinically treated plans generated by planners using VMAT (volumetric modulated arc therapy) with 4 to 6 partial arcs. Subsequently, clinical deployment began in April, 2017. RESULTS:In retrospective study, ECHO plans were found to be dosimetrically superior with respect to tumor coverage, plan conformity, and OAR sparing. For example, the average PTV D95%, cord and esophagus max doses, and Paddick Conformity Index were improved, respectively, by 1%, 6%, 14%, and 15%, at a negligible 3% cost of the average skin D10cc dose. CONCLUSION:Hierarchical constrained optimization is a powerful and flexible tool for automated IMRT treatment planning. The dosimetric correction step accurately accounts for detailed dosimetric multileaf collimator and scattering effects. The system produces high-quality, Pareto optimal plans and avoids the time-consuming trial-and-error planning process.

Dataset Information

Automated planning through robust templates and multicriterial optimization for lung VMAT SBRT of lung lesions.

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Automated planning through robust templates and multicriterial optimization for lung VMAT SBRT of lung lesions.

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