Optimization of radiosurgery treatment planning via mixed integer programming

An automated optimization algorithm based on mixed integer programming tech niques is presented for generating high-quality treatment plans for LINAC r adiosurgery treatment. The physical planning in radiosurgery treatment invo lves selecting among a large collection of beams with different physical pa rameters an optimal beam configuration (geometries and intensities) to deli ver the clinically prescribed radiation dose to the tumor volume while spar ing the nearby critical structure and normal tissue. The proposed mixed int eger programming models incorporate strict dose restrictions on tumor volum e, and constraints on the desired number of beams, isocenters, couch angles , and gantry angles. The model seeks to deliver full prescription dose cove rage and uniform radiation dose to the tumor volume while minimizing the ex cess radiation to the periphery normal tissue. In particular, it ensures th at proximal normal tissues receive minimal dose via rapid dose fall-off. Pr eliminary numerical tests on a single patient case indicate that this appro ach can produce exceptionally high-quality plans in a fraction of the time required using the procedure currently employed by clinicians. The resultin g plans provide highly uniform prescription dose to the tumor volume while drastically reducing the irradiation received by the proximal critical norm al tissue. (C) 2000 American Association of Physicists in Medicine. [S0094- 2405(00)00505-8].