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Automated intensity modulated treatment planning: The expedited constrained hierarchical optimization (ECHO) system.

ABSTRACT: 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.

SUBMITTER: Zarepisheh M

PROVIDER: S-EPMC6625843 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Automated intensity modulated treatment planning: The expedited constrained hierarchical optimization (ECHO) system.

Zarepisheh Masoud M Hong Linda L Zhou Ying Y Oh Jung Hun JH Mechalakos James G JG Hunt Margie A MA Mageras Gig S GS Deasy Joseph O JO

Medical physics 20190529 7

<h4>Purpose</h4>To develop and implement a fully automated approach to intensity modulated radiation therapy (IMRT) treatment planning.<h4>Method</h4>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 constra ...[more]

PMID: 31055858

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Project description:To introduce a hybrid volumetric modulated arc therapy/intensity modulated radiation therapy (VMAT/IMRT) optimization strategy called FusionArc that combines the delivery efficiency of single-arc VMAT with the potentially desirable intensity modulation possible with IMRT.A beamlet-based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive technique. In the hybrid strategy, baseline single-arc VMAT plans are optimized and then the current cost function gradients with respect to the beamlets are used to define a metric for predicting which beam angles would benefit from further intensity modulation. Beams with the highest metric values (called the gradient factor) are converted from VMAT apertures to IMRT fluence, and the optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. One phantom and two clinical cases were used to validate the gradient factor and characterize the FusionArc strategy. Comparisons were made between standard IMRT, single-arc VMAT, and FusionArc plans with one to five IMRT∕hybrid beams.The gradient factor was found to be highly predictive of the VMAT angles that would benefit plan quality the most from beam modulation. Over the three cases studied, a FusionArc plan with three converted beams achieved superior dosimetric quality with reductions in final cost ranging from 26.4% to 48.1% compared to single-arc VMAT. Additionally, the three beam FusionArc plans required 22.4%-43.7% fewer MU∕Gy than a seven beam IMRT plan. While the FusionArc plans with five converted beams offer larger reductions in final cost--32.9%-55.2% compared to single-arc VMAT--the decrease in MU∕Gy compared to IMRT was noticeably smaller at 12.2%-18.5%, when compared to IMRT.A hybrid VMAT∕IMRT strategy was implemented to find a high quality compromise between gantry-angle and intensity-based degrees of freedom. This optimization method will allow patients to be simultaneously planned for dosimetric quality and delivery efficiency without switching between delivery techniques. Example phantom and clinical cases suggest that the conversion of only three VMAT segments to modulated beams may result in a good combination of quality and efficiency.

Project description: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.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.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.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.

Project description:Intensity modulated proton therapy (IMPT) is highly sensitive to range uncertainties and uncertainties caused by setup variation. The conventional inverse treatment planning of IMPT optimized based on the planning target volume (PTV) is not often sufficient to ensure robustness of treatment plans. In this paper, a method that takes the uncertainties into account during plan optimization is used to mitigate the influence of uncertainties in IMPT.The authors use the so-called "worst-case robust optimization" to render IMPT plans robust in the face of uncertainties. For each iteration, nine different dose distributions are computed-one each for ± setup uncertainties along anteroposterior (A-P), lateral (R-L) and superior-inferior (S-I) directions, for ± range uncertainty, and the nominal dose distribution. The worst-case dose distribution is obtained by assigning the lowest dose among the nine doses to each voxel in the clinical target volume (CTV) and the highest dose to each voxel outside the CTV. Conceptually, the use of worst-case dose distribution is similar to the dose distribution achieved based on the use of PTV in traditional planning. The objective function value for a given iteration is computed using this worst-case dose distribution. The objective function used has been extended to further constrain the target dose inhomogeneity.The worst-case robust optimization method is applied to a lung case, a skull base case, and a prostate case. Compared with IMPT plans optimized using conventional methods based on the PTV, our method yields plans that are considerably less sensitive to range and setup uncertainties. An interesting finding of the work presented here is that, in addition to reducing sensitivity to uncertainties, robust optimization also leads to improved optimality of treatment plans compared to the PTV-based optimization. This is reflected in reduction in plan scores and in the lower normal tissue doses for the same coverage of the target volume when subjected to uncertainties.The authors find that the worst-case robust optimization provides robust target coverage without sacrificing, and possibly even improving, the sparing of normal tissues. Our results demonstrate the importance of robust optimization. The authors assert that all IMPT plans should be robustly optimized.

Project description:In this study, we present an intensity-modulated radiotherapy technique based on forward planning dose calculations to provide a concave dose distribution to the prostate and seminal vesicles by means of modified dynamic arc therapy (M-DAT). Dynamic arcs (350 degrees) conforming to the beam's eye view of the prostate and seminal vesicles while shielding the rectum, combined with two lateral oblique conformal fields (15 degrees with respect to laterals) fitting the prostate only,were applied to deliver doses of 78 Gy and 61.23 Gy in 39 fractions to the prostate and seminal vesicles respectively. Dynamic wedges (45 degrees of thick end, anteriorly oriented) were used with conformal beams to adjust the dose homogeneity to the prostate, although in some cases, hard wedges (30 degrees of thick part,inferiorly oriented) were used with arcs to adjust the dose coverage to the seminal vesicles. The M-DAT was applied to 10 patients in supine and 10 patients in prone positioning to determine the proper patient positioning for optimum protection of the rectum. The M-DAT was compared with the simplified intensity-modulated arc therapy (SIMAT) technique, composed of three phases of bilateral dynamic arcs. The mean rectal dose in M-DAT for prone patients was 22.5 +/- 5.1 Gy; in M-DAT and SIMAT for supine patients, it was 30.2 +/- 5.1 Gy and 39.4 +/- 6.0 Gy respectively. The doses to 15%, 25%, 35%, and 50% of the rectum volume in M-DAT for prone patients were 44.5 +/- 10.2 Gy, 33.0 +/- 8.2 Gy, 25.3 +/- 6.4 Gy, and 16.3 +/- 5.6 Gy respectively. These values were lower than those in M-DAT and in SIMAT for supine patients by 7.7%, 18.2%, 22.4%, and 28.5% and by 25.0%, 32.1%, 34.9%, and 41.9% of the prescribed dose (78 Gy) respectively. Ion chamber measurements showed good agreement of the calculated and measured isocentric dose (maximum deviation of 3.5%). Accuracy of the dose distribution calculation was evaluated by film dosimetry using a gamma index, allowing 3% dose variation and 4 mm distance to agreement as the individual acceptance criteria in prostate and seminal vesicle levels alike for all supine and prone patients. We found that fewer than 10% of the pixels in the dose distribution of the calculated area of10 x 10-cm failed the acceptance criteria. These pixels were observed mainly in the low-dose regions, particularly at the level of the seminal vesicles. In conclusion, the single-phase M-DAT technique with patients in the prone position was found to provide the intended coverage of the prescribed doses to the prostate and seminal vesicles with improved protection for the rectum. Accordingly, M-DAT has replaced non-modulated conformal radiotherapy or SIMAT as the standard treatment for prostate cancer in our department.

Project description:The purpose of this study was to investigate the feasibility of incorporating linear energy transfer (LET) into the optimization of intensity modulated proton therapy (IMPT) plans. Because increased LET correlates with increased biological effectiveness of protons, high LETs in target volumes and low LETs in critical structures and normal tissues are preferred in an IMPT plan. However, if not explicitly incorporated into the optimization criteria, different IMPT plans may yield similar physical dose distributions but greatly different LET, specifically dose-averaged LET, distributions. Conventionally, the IMPT optimization criteria (or cost function) only includes dose-based objectives in which the relative biological effectiveness (RBE) is assumed to have a constant value of 1.1. In this study, we added LET-based objectives for maximizing LET in target volumes and minimizing LET in critical structures and normal tissues. Due to the fractional programming nature of the resulting model, we used a variable reformulation approach so that the optimization process is computationally equivalent to conventional IMPT optimization. In this study, five brain tumor patients who had been treated with proton therapy at our institution were selected. Two plans were created for each patient based on the proposed LET-incorporated optimization (LETOpt) and the conventional dose-based optimization (DoseOpt). The optimized plans were compared in terms of both dose (assuming a constant RBE of 1.1 as adopted in clinical practice) and LET. Both optimization approaches were able to generate comparable dose distributions. The LET-incorporated optimization achieved not only pronounced reduction of LET values in critical organs, such as brainstem and optic chiasm, but also increased LET in target volumes, compared to the conventional dose-based optimization. However, on occasion, there was a need to tradeoff the acceptability of dose and LET distributions. Our conclusion is that the inclusion of LET-dependent criteria in the IMPT optimization could lead to similar dose distributions as the conventional optimization but superior LET distributions in target volumes and normal tissues. This may have substantial advantages in improving tumor control and reducing normal tissue toxicities.

Project description:Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be satisfied when the TPS-QC tool generated re-optimized plans without sacrificing other dosimetric endpoints. In addition to its feasibility and accuracy, the proposed TPS-QC tool is also user-friendly and easy to operate, both of which are necessary characteristics for clinical use.

Project description:The purpose of this work is to evaluate the volumetric-modulated arc therapy (VMAT) multicriteria optimization (MCO) algorithm clinically available in the RayStation treatment planning system (TPS) and its ability to reduce treatment planning time while providing high dosimetric plan quality. Nine patients with localized prostate cancer who were previously treated with 78 Gy in 39 fractions using VMAT plans and rayArc system based on the direct machine parameter optimization (DMPO) algorithm were selected and replanned using the VMAT-MCO system. First, the dosimetric quality of the plans was evaluated using multiple conformity metrics that account for target coverage and sparing of healthy tissue, used in our departmental clinical protocols. The conformity and homogeneity index, number of monitor units, and treatment planning time for both modalities were assessed. Next, the effects of the technical plan parameters, such as constraint leaf motion CLM (cm/°) and maximum arc delivery time T (s), on the accuracy of delivered dose were evaluated using quality assurance passing rates (QAs) measured using the Delta4 phantom from ScandiDos. For the dosimetric plan's quality analysis, the results show that the VMAT-MCO system provides plans comparable to the rayArc system with no statistical difference for V95% (p < 0.01), D1% (p < 0.01), CI (p < 0.01), and HI (p < 0.01) of the PTV, bladder (p < 0.01), and rectum (p < 0.01) constraints, except for the femoral heads and healthy tissues, for which a dose reduction was observed using MCO compared with rayArc (p < 0.01). The technical parameter study showed that a combination of CLM equal to 0.5 cm/degree and a maximum delivery time of 72 s allowed the accurate delivery of the VMAT-MCO plan on the Elekta Versa HD linear accelerator. Planning evaluation and dosimetric measurements showed that VMAT-MCO can be used clinically with the advantage of enhanced planning process efficiency by reducing the treatment planning time without impairing dosimetric quality.

Dataset Information

Automated intensity modulated treatment planning: The expedited constrained hierarchical optimization (ECHO) system.

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Automated intensity modulated treatment planning: The expedited constrained hierarchical optimization (ECHO) system.

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