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      Multicriteria VMAT optimization

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          Abstract

          Purpose: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency. Methods: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE. Results: VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than five minutes on average. VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems.

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          Most cited references12

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          CERR: a computational environment for radiotherapy research.

          A software environment is described, called the computational environment for radiotherapy research (CERR, pronounced "sir"). CERR partially addresses four broad needs in treatment planning research: (a) it provides a convenient and powerful software environment to develop and prototype treatment planning concepts, (b) it serves as a software integration environment to combine treatment planning software written in multiple languages (MATLAB, FORTRAN, C/C++, JAVA, etc.), together with treatment plan information (computed tomography scans, outlined structures, dose distributions, digital films, etc.), (c) it provides the ability to extract treatment plans from disparate planning systems using the widely available AAPM/RTOG archiving mechanism, and (d) it provides a convenient and powerful tool for sharing and reproducing treatment planning research results. The functional components currently being distributed, including source code, include: (1) an import program which converts the widely available AAPM/RTOG treatment planning format into a MATLAB cell-array data object, facilitating manipulation; (2) viewers which display axial, coronal, and sagittal computed tomography images, structure contours, digital films, and isodose lines or dose colorwash, (3) a suite of contouring tools to edit and/or create anatomical structures, (4) dose-volume and dose-surface histogram calculation and display tools, and (5) various predefined commands. CERR allows the user to retrieve any AAPM/RTOG key word information about the treatment plan archive. The code is relatively self-describing, because it relies on MATLAB structure field name definitions based on the AAPM/RTOG standard. New structure field names can be added dynamically or permanently. New components of arbitrary data type can be stored and accessed without disturbing system operation. CERR has been applied to aid research in dose-volume-outcome modeling, Monte Carlo dose calculation, and treatment planning optimization. In summary, CERR provides a powerful, convenient, and common framework which allows researchers to use common patient data sets, and compare and share research results.
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            Intensity-modulated arc therapy with dynamic multileaf collimation: an alternative to tomotherapy.

            C. X. Yu (1995)
            The desire to improve local tumour control and cure more cancer patients, coupled with advances in computer technology and linear accelerator design, has spurred the developments of three-dimensional conformal radiotherapy techniques. Optimized treatment plans, aiming to deliver high dose to the target while minimizing dose to the surrounding tissues, can be delivered with multiple fields each with spatially modulated beam intensities or with multiple-slice treatments. This paper introduces a new method, intensity-modulated arc therapy (IMAT), for delivering optimized treatment plans to improve the therapeutic ratio. It utilizes continuous gantry motion as in conventional arc therapy. Unlike conventional arc therapy, the field shape, which is conformed with the multileaf collimator, changes during gantry rotation. Arbitrary two-dimensional beam intensify distributions at different beam angles are delivered with multiple superimposing arcs. A system capable of delivering the IMAT has been implemented. An example is given that illustrates the feasibility of this new method. Advantages of this new technique over tomotherapy and other slice-based delivery schemes are also discussed.
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              Approximating convex pareto surfaces in multiobjective radiotherapy planning.

              Radiotherapy planning involves inherent tradeoffs: the primary mission, to treat the tumor with a high, uniform dose, is in conflict with normal tissue sparing. We seek to understand these tradeoffs on a case-to-case basis, by computing for each patient a database of Pareto optimal plans. A treatment plan is Pareto optimal if there does not exist another plan which is better in every measurable dimension. The set of all such plans is called the Pareto optimal surface. This article presents an algorithm for computing well distributed points on the (convex) Pareto optimal surface of a multiobjective programming problem. The algorithm is applied to intensity-modulated radiation therapy inverse planning problems, and results of a prostate case and a skull base case are presented, in three and four dimensions, investigating tradeoffs between tumor coverage and critical organ sparing.
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                Author and article information

                Journal
                20 May 2011
                2011-12-06
                Article
                10.1118/1.3675601
                1105.4109
                67baafae-d4fe-4b3a-9b5e-0df0312081bd

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                physics.med-ph

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