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Whole‐procedure clinical accuracy of Gamma Knife treatments of large lesions a)
Author(s) -
Ma Lijun,
Chuang Cynthia,
Descovich Martina,
Petti Paula,
Smith Ver,
Verhey Lynn
Publication year - 2008
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 - 10.1118/1.2987669
Subject(s) - isocenter , imaging phantom , radiosurgery , nuclear medicine , quality assurance , radiation treatment planning , quadrature (astronomy) , medical physics , image guided radiation therapy , dosimetry , medical imaging , medicine , physics , mathematics , optics , radiology , radiation therapy , external quality assessment , pathology
The mechanical accuracy of Gamma Knife radiosurgery based on single‐isocenter measurement has been established to within 0.3 mm . However, the full delivery accuracy for Gamma Knife treatments of large lesions has only been estimated via the quadrature‐sum analysis. In this study, the authors directly measured the whole‐procedure accuracy for Gamma Knife treatments of large lesions to examine the validity of such estimation. The measurements were conducted on a head‐phantom simulating the whole treatment procedure that included frame placement, computed tomography imaging, treatment planning, and treatment delivery. The results of the measurements were compared with the dose calculations from the treatment planning system. Average agreements of 0.1 – 1.6 mm for the isodose lines ranging from 25% to 90% of the maximum dose were found despite potentially large contributing uncertainties such as 3 ‐ mm imaging resolution, 2 ‐ mm dose grid size, 1 ‐ mm frame registration, multi‐isocenter deliveries, etc. The results of our measurements were found to be significantly smaller ( > 50 % ) than the calculated value based on the quadrature‐sum analysis. In conclusion, Gamma Knife treatments of large lesions can be delivered much more accurately than predicted from the quadrature‐sum analysis of major sources of uncertainties from each step of the delivery chain.