Analytic characterization of linear accelerator radiosurgery dose distributions for fast optimization.
Linear accelerator (linac) radiosurgery utilizes non-coplanar arc therapy delivered through circular collimators. Generally, spherically symmetric arc sets are used, resulting in nominally spherical dose distributions. Various treatment planning parameters may be manipulated to provide dose conformation to irregular lesions. Iterative manipulation of these variables can be a difficult and time-consuming task, because (a) understanding the effect of these parameters is complicated and (b) three-dimensional (3D) dose calculations are computationally expensive. This manipulation can be simplified, however, because the prescription isodose surface for all single isocentre distributions can be approximated by conic sections. In this study, the effects of treatment planning parameter manipulation on the dimensions of the treatment isodose surface were determined empirically. These dimensions were then fitted to analytic functions, assuming that the dose distributions were characterized as conic sections. These analytic functions allowed real-time approximation of the 3D isodose surface. Iterative plan optimization, either manual or automated, is achieved more efficiently using this real time approximation of the dose matrix. Subsequent to iterative plan optimization, the analytic function is related back to the appropriate plan parameters, and the dose distribution is determined using conventional dosimetry calculations. This provides a pseudo-inverse approach to radiosurgery optimization, based solely on geometric considerations.
Meeks
S L
SL
Department of Neurosurgery, University of Florida College of Medicine, Gainesville 32610-0265, USA. meeks@neurosurgery.ufl.edu
Bova
F J
FJ
Buatti
J M
JM
Friedman
W A
WA
Eyster
B
B
Kendrick
L A
LA
D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010315:Particle Accelerators; D019047:Phantoms, Imaging; D016634:Radiosurgery; D013813:Therapy, Computer-Assisted; D014057:Tomography, X-Ray Computed