Dose distributions at extreme irradiation depths of gamma knife radiosurgery: EGS4 Monte Carlo calculations

2001 ◽  
Vol 54 (3) ◽  
pp. 461-465 ◽  
Author(s):  
J.Y.C. Cheung ◽  
K.N. Yu ◽  
C.P. Yu ◽  
R.T.K. Ho
2021 ◽  
Vol 20 ◽  
pp. 153303382110464
Author(s):  
Jiankui Yuan ◽  
Elisha Fredman ◽  
Jian-Yue Jin ◽  
Serah Choi ◽  
David Mansur ◽  
...  

The aim of this work is to study the dosimetric effect from generated synthetic computed tomography (sCT) from magnetic resonance (MR) images using a deep learning algorithm for Gamma Knife (GK) stereotactic radiosurgery (SRS). The Monte Carlo (MC) method is used for dose calculations. Thirty patients were retrospectively selected with our institution IRB’s approval. All patients were treated with GK SRS based on T1-weighted MR images and also underwent conventional external beam treatment with a CT scan. Image datasets were preprocessed with registration and were normalized to obtain similar intensity for the pairs of MR and CT images. A deep convolutional neural network arranged in an encoder–decoder fashion was used to learn the direct mapping from MR to the corresponding CT. A number of metrics including the voxel-wise mean error (ME) and mean absolute error (MAE) were used for evaluating the difference between generated sCT and the true CT. To study the dosimetric accuracy, MC simulations were performed based on the true CT and sCT using the same treatment parameters. The method produced an MAE of 86.6 ± 34.1 Hundsfield units (HU) and a mean squared error (MSE) of 160.9 ± 32.8. The mean Dice similarity coefficient was 0.82 ± 0.05 for HU > 200. The difference for dose-volume parameter D95 between the ground true dose and the dose calculated with sCT was 1.1% if a synthetic CT-to-density table was used, and 4.9% compared with the calculations based on the water-brain phantom.


2018 ◽  
Vol 129 (Suppl1) ◽  
pp. 140-146
Author(s):  
Joshua Chiu ◽  
Steve Braunstein ◽  
Jean Nakamura ◽  
Philip Theodosopoulos ◽  
Penny Sneed ◽  
...  

OBJECTIVEInterfractional residual patient shifts are often observed during the delivery of hypofractionated brain radiosurgery. In this study, the authors developed a robustness treatment planning check procedure to assess the dosimetric effects of residual target shifts on hypofractionated Gamma Knife radiosurgery (GKRS).METHODSThe residual patient shifts were determined during the simulation process immediately after patient immobilization. To mimic incorporation of residual target shifts during treatment delivery, a quality assurance procedure was developed to sample and shift individual shots according to the residual uncertainties in the prescribed treatment plan. This procedure was tested and demonstrated for 10 hypofractionated GKRS cases.RESULTSThe maximum residual target shifts were less than 1 mm for the studied cases. When incorporating such shifts, the target coverage varied by 1.9% ± 2.2% (range 0.0%–7.1%) and selectivity varied by 3.6% ± 2.5% (range 1.1%–9.3%). Furthermore, when incorporating extra random shifts on the order of 0.5 mm, the target coverage decreased by as much as 7%, and nonisocentric variation in the dose distributions was noted for the studied cases.CONCLUSIONSA pretreatment robustness check procedure was developed and demonstrated for hypofractionated GKRS. Further studies are underway to implement this procedure to assess maximum tolerance levels for individual patient cases.


2012 ◽  
Vol 39 (6Part17) ◽  
pp. 3820-3820 ◽  
Author(s):  
L Wang ◽  
L Xing ◽  
D Sawkey ◽  
M Constantin ◽  
M Svatos ◽  
...  

1999 ◽  
Vol 26 (8) ◽  
pp. 1484-1491 ◽  
Author(s):  
N. Reynaert ◽  
F. Verhaegen ◽  
Y. Taeymans ◽  
M. Van Eijkeren ◽  
H. Thierens

Radiosurgery ◽  
2006 ◽  
pp. 26-35
Author(s):  
Vasu Ganesan ◽  
Rami Mehrem ◽  
John Fenner ◽  
Lee Walton

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