Literature DB >> 27370141

A comprehensive formulation for volumetric modulated arc therapy planning.

Dan Nguyen1, Qihui Lyu1, Dan Ruan1, Daniel O'Connor1, Daniel A Low1, Ke Sheng1.   

Abstract

PURPOSE: Volumetric modulated arc therapy (VMAT) is a widely employed radiation therapy technique, showing comparable dosimetry to static beam intensity modulated radiation therapy (IMRT) with reduced monitor units and treatment time. However, the current VMAT optimization has various greedy heuristics employed for an empirical solution, which jeopardizes plan consistency and quality. The authors introduce a novel direct aperture optimization method for VMAT to overcome these limitations.
METHODS: The comprehensive VMAT (comVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term to penalize the difference between the optimized dose and the prescribed dose, as well as an anisotropic total variation term to promote piecewise continuity in the fluence maps, preparing it for direct aperture optimization. A level set function was used to describe the aperture shapes and the difference between aperture shapes at adjacent angles was penalized to control MLC motion range. A proximal-class optimization solver was adopted to solve the large scale optimization problem, and an alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc comVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme case, a lung (LNG) case, and two head and neck cases-one with three PTVs (H&N3PTV) and one with foue PTVs (H&N4PTV)-to test the efficacy. The plans were optimized using an alternating optimization strategy. The plans were compared against the clinical VMAT (clnVMAT) plans utilizing two overlapping coplanar arcs for treatment.
RESULTS: The optimization of the comVMAT plans had converged within 600 iterations of the block minimization algorithm. comVMAT plans were able to consistently reduce the dose to all organs-at-risk (OARs) as compared to the clnVMAT plans. On average, comVMAT plans reduced the max and mean OAR dose by 6.59% and 7.45%, respectively, of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N3PTV case. PTV coverages measured by D95, D98, and D99 were within 0.25% of the prescription dose. By comprehensively optimizing all beams, the comVMAT optimizer gained the freedom to allow some selected beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization.
CONCLUSIONS: The novel nongreedy VMAT approach simultaneously optimizes all beams in an arc and then directly generates deliverable apertures. The single arc VMAT approach thus fully utilizes the digital Linac's capability in dose rate and gantry rotation speed modulation. In practice, the new single VMAT algorithm generates plans superior to existing VMAT algorithms utilizing two arcs.

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Mesh:

Year:  2016        PMID: 27370141      PMCID: PMC4912562          DOI: 10.1118/1.4953832

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  27 in total

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Authors:  Wilko F A R Verbakel; Johan P Cuijpers; Daan Hoffmans; Michael Bieker; Ben J Slotman; Suresh Senan
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  11 in total

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2.  Many-isocenter optimization for robotic radiotherapy.

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3.  Use of proximal operator graph solver for radiation therapy inverse treatment planning.

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4.  Deterministic direct aperture optimization using multiphase piecewise constant segmentation.

Authors:  Dan Nguyen; Daniel O'Connor; Dan Ruan; Ke Sheng
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5.  Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

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6.  A novel optimization framework for VMAT with dynamic gantry couch rotation.

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7.  Solving the volumetric modulated arc therapy (VMAT) problem using a sequential convex programming method.

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8.  A fast optimization approach for treatment planning of volumetric modulated arc therapy.

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9.  ROAD: ROtational direct Aperture optimization with a Decoupled ring-collimator for FLASH radiotherapy.

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10.  A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.

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