title: A systematic benchmark method for analysis and comparison of IMRT treatment planning algorithms.
abstract: Tools and procedures for evaluating and comparing different intensity-modulated radiation therapy (IMRT) systems are presented. IMRT is increasingly in demand and there are numerous systems available commercially. These programs introduce significantly different software to dosimetrists and physicists than conventional planning systems, and the options often seem initially overwhelmingly complex to the user. By creating geometric target volumes and critical normal tissues, the characteristics of the algorithms may be investigated, and the influence of the different parameters explored. Overall optimization strategies of the algorithm may be characterized by treating a square target volume (TV) with 2 perpendicular beams, with and without heterogeneities. A half-donut (hemi-annulus) TV with a "donut hole" (central cylinder) critical normal tissue (CNT) on a CT of a simulated quality assurance phantom is suggested as a good geometry to explore the IMRT algorithm parameters. Using this geometry, the order of varying parameters is suggested. First is to determine the effects of the number of stratifications of optimized intensity fluence on the resulting dose distribution, and selecting a fixed number of stratifications for further studies. To characterize the dose distributions, a dose-homogeneity index (DHI) is defined as the ratio of the dose received by 90% of the volume to the minimum dose received by the "hottest" 10% of the volume. The next step is to explore the effects of priority and penalty on both the TV and the CNT. Then, choosing and fixing these parameters, the effects of varying the number of beams can be looked at. As well as evaluating the dose distributions (and DHI), the number of subfields and the number of monitor units required for different numbers of stratifications and beams can be evaluated.
authors.affiliation: Radiation Oncology, UMass-Memorial Health Care, Worcester, MA 01655, USA. Mayoc@ummhc.org
authors.forename: Charles S
authors.initials: CS
authors.lastname: Mayo
authors.forename: Marcia M
authors.initials: MM
authors.lastname: Urie
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D019047:Phantoms, Imaging; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D014057:Tomography, X-Ray Computed