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Theoretical considerations of monitor unit calculations for intensity modulated beam treatment planning
Author(s) -
Boyer A.,
Xing L.,
Ma CM.,
Curran B.,
Hill R.,
Kania A.,
Bleier A.
Publication year - 1999
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 - 10.1118/1.598502
Subject(s) - multileaf collimator , radiation treatment planning , monitor unit , intensity modulation , collimator , computer science , convolution (computer science) , dosimetry , intensity (physics) , beam (structure) , algorithm , inverse , medical physics , nuclear medicine , mathematical optimization , mathematics , radiation therapy , physics , optics , artificial intelligence , radiology , medicine , geometry , phase modulation , artificial neural network , phase noise
A treatment planning system to compute intensity modulated radiotherapy (IMRT) treatments using inverse planning was investigated. The system was designed to optimize the intensity patterns required to treat a specified target volume with specified normal structure constraints. A beam model that uses the convolution of pencil beams was used to compute the dose distributions. A multileaf collimator leaf‐setting sequence intended to produce the intensity pattern was computed along with the monitor units required to deliver each of a number of fixed‐gantry modulated fields. Computer calculations are commonly verified using an independent manual procedure. It is difficult to calculate treatment delivery monitor units for this variant of IMRT using manual methods. Since manual calculations are not feasible, it is important both to understand and to verify the calculation of treatment monitor units by the planning system algorithm. A formal analysis was made of the dose calculation model and the monitor unit calculation embedded in the algorithm. Experimental verification of the dose delivered by plans computed with the methodology demonstrated an agreement of better than 4% between the dose model and measurements.