Fully automated treatment planning for MLC‐based robotic radiotherapy

Abstract

To propose and validate a fully automated multi-criterial treatment planning solution for a CyberKnife ® equipped with an InCise™ 2 multi-leaf collimator. Methods: The AUTO BAO plans are generated with fully-automated prioritized multi-criterial optimization (AUTO MCO) of pencil-beam fluence maps with integrated non-coplanar beam angle optimization (BAO), followed by MLC segment generation. Both the AUTO MCO and segmentation algorithms have been in-house developed. 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. Results: AUTO 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. Conclusions: A 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 i Accepted ArticleThis article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Inter- and intrafraction dose variations in robotic stereotactic body radiation therapy (SBRT) for perihilar cholangiocarcinoma in the prospective phase I STRONG trial

“…Before doses were calculated in the rCTs, the rCTs were registered to their respective pCTs in a two-step procedure similar to the daily tumor setup procedure (see above), in which a spine match (translations and rotations) was followed by a match of fiducials (translations only). To determine which dose had actually been delivered during treatment, we used a standalone version of the clinical dose engine to calculate the rCT dose distributions for the planned Cyberknife settings (such as MLC segment shapes, MUs, and beam angles) ( 20 , 21 ). The clinical and standalone dose engines had slight differences in beam models.…”

Automated multi-criterial planning with beam angle optimization to establish non-coplanar VMAT class solutions for nasopharyngeal carcinoma

“…The system has an option for integrated optimization of beam intensity profiles and (non-coplanar) beam angle directions [8,11,12,15,[26][27][28][29][30][31][32][33], which was used in this study. Erasmus-iCycle generates Pareto-optimal and clinically favorable plans by applying an appropriate treatment site specific configuration ('wish-list') [15,17,34], containing hard constraints that can never be violated, and objectives that are optimized in order of priority.…”

“…Automatically generated Erasmus-iCycle plans were converted into clinically deliverable segmented plans using the Monaco treatment planning system (TPS), version 5.11 (Elekta AB, Stockholm, Sweden). These conversions were fully automatically performed, using patient-specific Monaco templates, automatically derived from the patient-specific Erasmus-iCycle FMO dose distributions [8,12,15,21,[26][27][28][29][30][31][32][33][34][35][36].…”

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer

“…Fully automated treatment planning can generate high quality treatment plans with consistent trade-offs for different patients [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] . With minimal user interaction, these methods are very suitable for treatment planning benchmark studies.…”