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Optimization of radiosurgery treatment planning via mixed integer programming
Author(s) -
Lee Eva K.,
Fox Tim,
Crocker Ian
Publication year - 2000
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 - 10.1118/1.598964
Subject(s) - radiosurgery , integer programming , radiation treatment planning , linear particle accelerator , dosimetry , linear programming , radiation therapy , nuclear medicine , mathematical optimization , computer science , medical physics , beam (structure) , algorithm , mathematics , medicine , radiology , physics , optics
An automated optimization algorithm based on mixed integer programming techniques is presented for generating high‐quality treatment plans for LINAC radiosurgery treatment. The physical planning in radiosurgery treatment involves selecting among a large collection of beams with different physical parameters an optimal beam configuration (geometries and intensities) to deliver the clinically prescribed radiation dose to the tumor volume while sparing the nearby critical structure and normal tissue. The proposed mixed integer programming models incorporate strict dose restrictions on tumor volume, and constraints on the desired number of beams, isocenters, couch angles, and gantry angles. The model seeks to deliver full prescription dose coverage and uniform radiation dose to the tumor volume while minimizing the excess radiation to the periphery normal tissue. In particular, it ensures that proximal normal tissues receive minimal dose via rapid dose fall‐off. Preliminary numerical tests on a single patient case indicate that this approach can produce exceptionally high‐quality plans in a fraction of the time required using the procedure currently employed by clinicians. The resulting plans provide highly uniform prescription dose to the tumor volume while drastically reducing the irradiation received by the proximal critical normal tissue.