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Individualized automated planning for dose bath reduction in robotic radiosurgery for benign tumors.

ABSTRACT: OBJECT:To explore the use of automated planning in robotic radiosurgery of benign vestibular schwannoma (VS) tumors for dose reduction outside the planning target volume (PTV) to potentially reduce risk of secondary tumor induction. METHODS:A system for automated planning (AUTOplans) for VS patients was set up. The goal of AUTO- planning was to reduce the dose bath, including the occurrence of high dose spikes leaking from the PTV into normal tissues, without worsening PTV coverage, OAR doses, or treatment time. For 20 VS patients treated with 1x12 Gy, the AUTOplan was compared with the plan generated with conventional, manual trial-and-error planning (MANplan). RESULTS:With equal PTV coverage, AUTOplans showed clinically negligible differences with MANplans in OAR sparing (largest mean difference for all OARs: ?D2% = 0.2 Gy). AUTOplan dose distributions were more compact: mean/maximum reductions of 23.6/53.8% and 9.6/28.5% in patient volumes receiving more than 1 or 6 Gy, respectively (p<0.001). AUTOplans also showed smaller dose spikes with mean/maximum reductions of 22.8/37.2% and 14.2/40.4% in D2% for shells at 1 and 7 cm distance from the PTV, respectively (p<0.001). CONCLUSION:Automated planning for benign VS tumors highly outperformed manual planning with respect to the dose bath outside the PTV, without deteriorating PTV coverage or OAR sparing, or significantly increasing treatment time.

SUBMITTER: Rossi L

PROVIDER: S-EPMC6364873 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Individualized automated planning for dose bath reduction in robotic radiosurgery for benign tumors.

Rossi Linda L Méndez Romero Alejandra A Milder Maaike M de Klerck Erik E Breedveld Sebastiaan S Heijmen Ben B

PloS one 20190206 2

<h4>Object</h4>To explore the use of automated planning in robotic radiosurgery of benign vestibular schwannoma (VS) tumors for dose reduction outside the planning target volume (PTV) to potentially reduce risk of secondary tumor induction.<h4>Methods</h4>A system for automated planning (AUTOplans) for VS patients was set up. The goal of AUTO- planning was to reduce the dose bath, including the occurrence of high dose spikes leaking from the PTV into normal tissues, without worsening PTV coverag ...[more]

PMID: 30726214

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Project description:Stereotactic radiosurgery (SRS) is the accurate, conformal delivery of high-dose radiation to well-defined targets while minimizing normal structure doses via steep dose gradients. While inverse treatment planning (ITP) with computerized optimization algorithms are routine, many aspects of the planning process remain user-dependent. We performed an international, multi-institutional benchmark trial to study planning variability and to analyze preferable ITP practice for spinal robotic radiosurgery. 10 SRS treatment plans were generated for a complex-shaped spinal metastasis with 21 Gy in 3 fractions and tight constraints for spinal cord (V14Gy < 2 cc, V18Gy < 0.1 cc) and target (coverage > 95%). The resulting plans were rated on a scale from 1 to 4 (excellent-poor) in five categories (constraint compliance, optimization goals, low-dose regions, ITP complexity, and clinical acceptability) by a blinded review panel. Additionally, the plans were mathemati-cally rated based on plan indices (critical structure and target doses, conformity, monitor units, normal tissue complication probability, and treatment time) and compared to the human rankings. The treatment plans and the reviewers' rankings varied substantially among the participating centers. The average mean overall rank was 2.4 (1.2-4.0) and 8/10 plans were rated excellent in at least one category by at least one reviewer. The mathematical rankings agreed with the mean overall human rankings in 9/10 cases pointing toward the possibility for sole mathematical plan quality comparison. The final rankings revealed that a plan with a well-balanced trade-off among all planning objectives was preferred for treatment by most par-ticipants, reviewers, and the mathematical ranking system. Furthermore, this plan was generated with simple planning techniques. Our multi-institutional planning study found wide variability in ITP approaches for spinal robotic radiosurgery. The participants', reviewers', and mathematical match on preferable treatment plans and ITP techniques indicate that agreement on treatment planning and plan quality can be reached for spinal robotic radiosurgery.

Project description:PurposeTo propose and validate a fully automated multicriterial treatment planning solution for a CyberKnife® equipped with an InCiseTM 2 multileaf collimator.MethodsThe AUTO BAO plans are generated using fully automated prioritized multicriterial optimization (AUTO MCO) of pencil-beam fluence maps with integrated noncoplanar beam angle optimization (BAO), followed by MLC segment generation. Both the AUTO MCO and segmentation algorithms have been developed in-house. AUTO MCO generates for each patient a single, high-quality Pareto-optimal IMRT plan. The segmentation algorithm then accurately mimics the AUTO MCO 3D dose distribution, while considering all candidate beams simultaneously, rather than replicating the fluence maps. Pencil-beams, segment dose depositions, and final dose calculations are performed with a stand-alone version of the clinical dose calculation engine. For validation, AUTO BAO plans were generated for 33 prostate SBRT patients and compared to reference plans (REF) that were manually generated with the commercial treatment planning system (TPS), in absence of time pressure. REF plans were also compared to AUTO RB plans, for which fluence map optimization was performed for the beam angle configuration used in the REF plan, and the segmentation could use all these beams or only a subset, depending on the dosimetry.ResultsAUTO BAO plans were clinically acceptable and dosimetrically similar to REF plans, but had on average reduced numbers of beams ((beams in AUTO BAO)/(beams in REF) (relative improvement): 24.7/48.3 (-49%)), segments (59.5/98.9 (-40%)), and delivery times (17.1/22.3 min. (-23%)). Dosimetry of AUTO RB and REF were also similar, but AUTO RB used on average fewer beams (38.0/48.3 (-21%)) and had on average shorter delivery times (18.6/22.3 min. (-17%)). Delivered Monitor Units (MU) were similar for all three planning approaches.ConclusionsA new, vendor-independent optimization workflow for fully automated generation of deliverable high-quality CyberKnife® plans was proposed, including BAO. Compared to manual planning with the commercial TPS, fraction delivery times were reduced by 5.3 min. (-23%) due to large reductions in beam and segment numbers.

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Project description:As irradiated brain volume at 12 Gy (V12) is a predictor for radionecrosis, the purpose of the study was to develop a model for Cyberknife (CK) plans that is able to predict the lowest achievable V12 at a given tumor size and prescription dose (PD), and to suggest a new quality index regarding V12 for optimizing the treatment planning of brain metastases.In our model V12 was approximated as a spherical shell around the tumor volume. The radial distance between tumor surface and the 12 Gy isodose line was calculated using an approximation of the mean dose gradient in that area. Assuming a radially symmetrical irradiation from the upper half space, the dose distribution is given by the superposition of single fields. The dose profiles of a single field were derived by the measured off-center ratios (OCR) of the CK system. Using the calculated gradients of the sum dose profiles, minimal-V12 was estimated for different tumor sizes. The model calculation was tested using a phantom dataset and retrospectively applied on clinical cases.Our model allows the prediction of a best-case scenario for V12 at a given tumor size and PD which was confirmed by the results of the isocentric phantom plans. The results of the non-isocentric phantom plans showed that an optimization of coverage caused an increase in V12. This was in accordance with the results of the retrospective analysis. V12 s of the clinical cases were on average twice that of the predicted model calculation. A good agreement was achieved for plans with an optimal conformity index (nCI). Re-planning of cases with high V12 showed that lower values could be reached by selecting smaller collimators and by allowing a larger number of total MU and more MU per beam.V12 is a main parameter for assessing plan quality in terms of radiotoxicity. The index f12 defined as the ratio of V12 from the actual plan with the evaluated V12 from our model describes the conformity of an optimally possible V12 and thus can be used as a new quality index for optimizing treatment plans.

Dataset Information

Individualized automated planning for dose bath reduction in robotic radiosurgery for benign tumors.

Publications

Individualized automated planning for dose bath reduction in robotic radiosurgery for benign tumors.

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