title: A technique to sharpen the beam penumbra for Gamma Knife radiosurgery.
abstract: In stereotactic radiosurgery, a narrow beam penumbra is often desired for producing steep dose fall-off between the target volume and adjacent critical structures. Due to limited source sizes and the scattering effects, the physical penumbra of the Gamma Knife (GK) is often restricted to a width of 1-2 mm. In this work, we developed a technique to further reduce the beam penumbra and improve the dose profile for the Gamma Knife delivery. Under this technique, a conic filter is inserted into an individual plug collimator of a GK helmet to flatten the beam profile. Monte Carlo calculations were carried out to simulate the GK geometry of the individual plug collimator and to optimize the physical shapes of the filters. The calculations were performed for a series of filter shapes with different collimator sizes. Our results show that a proper filter significantly reduces the single GK beam penumbra width (defined as the distance from the 90% to 50% isodose lines) by 30-60%. The beam intensity is reduced by about 20-50% when the filter is used. A treatment plan was developed for a trigeminal neuralgia case by commissioning the filtered beam profile for Leksell Gamma Plan (version 5.31). Compared with the conventional treatment plan, a significant improvement was found on the critical structure sparing and on the target dose uniformity. In conclusion, the proposed technique is feasible and effective in sharpening the beam penumbra for Gamma Knife beam profiles.
authors.affiliation: Department of Radiation Oncology, University of Maryland, School of Medicine, Baltimore, MD 21201, USA.
authors.forename: M
authors.initials: M
authors.lastname: Guerrero
authors.forename: X Allen
authors.initials: XA
authors.lastname: Li
authors.forename: Lijun
authors.initials: L
authors.lastname: Ma
mesh_terms: D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D001932:Brain Neoplasms / Q000601:surgery; D006801:Humans; D009010:Monte Carlo Method; D016634:Radiosurgery / Q000379:methods* / Q000706:statistics & numerical data; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data