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Poster — Thur Eve — 52: Head and Neck IMRT Complexity Characterization and Prediction of Deliverability Using the Modulation Complexity Score
Author(s) -
McNiven AL,
Davidson MTM,
Sharpe MB,
Purdie TG
Publication year - 2010
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3476157
Subject(s) - context (archaeology) , intensity modulation , computer science , dosimetry , metric (unit) , head and neck , beam (structure) , radiation treatment planning , nuclear medicine , radiation therapy , mathematics , algorithm , medical physics , medicine , physics , optics , radiology , surgery , paleontology , operations management , phase modulation , phase noise , economics , biology
Intensity modulated radiation therapy (IMRT) is often referred to as being highly complex, but the definition of complexity can be varied. A single metric, the modulation complexity score (MCS), has previously been developed to quantify IMRT complexity. The purpose of this study is to evaluate the use of MCS in the characterization of segmentation complexity and beam deliverability in the context of head and neck IMRT. Fifty treatment plans were evaluated by calculating the MCS per beam. Patient‐specific measurements were obtained as part of the standard IMRT QA process using a diode array and retrospective analysis was completed using various gamma analysis criteria. The MCS, as well as single beam parameters (e.g. number of MU or control points), were compared to dosimetric results. 375 individual treatment beams were analyzed, with an average MCS of 0.245 (range: −0.338 – 0.754) and 125 MU on average (range: 32 to 295). All beams had >90% of diodes passing the standard gamma analysis (3%/3mm) with an average of 98%. There was a linear relationship between the number of MU and the MCS score (r 2 =0.75). The relationship between pass rate and complexity (characterized by MCS or MU) is not simple, however it may be possible to predict good dosimetric results based on the plan complexity. In conjunction with the ability to compile complexity statistics for specific treatment sites or protocols, MCS could impact the radiation therapy process at many points, including during planning, plan evaluation and QA.