A Comparison of the Dose Distributions for Various Movements of the Multileaf Collimators by Using a Two-dimensional Ionization Chamber in a Medical Linear Accelerator

2015 ◽  
Vol 65 (4) ◽  
pp. 389-393
Author(s):  
Joon-Ho CHOI ◽  
Soon-Kwon NAM*
Keyword(s):  
Linear Accelerator ◽  
Ionization Chamber ◽  
Two Dimensional ◽  
Dose Distributions ◽  
Multileaf Collimators ◽  
Medical Linear Accelerator

scholarly journals Dose distributions verification for High dose rate brachytherapy plans by using ionization chambers 2D array

2016 ◽  
Vol 15 (3) ◽  
pp. 6618-6625
Author(s):  
Rasha Moustafa Abdelfattah ◽  
N. Ahmed Deiab ◽  
M. Hassan Elnaggar ◽  
M. Hany Khedr ◽  
R. Abdelmoneim Rizk
Keyword(s):  
Treatment Planning ◽  
Ionization Chamber ◽  
Measured Data ◽  
Planning System ◽  
Global Maximum ◽  
Test Case ◽  
Hdr Brachytherapy ◽  
Two Dimensional ◽  
Dose Distributions ◽  
2D Array

The purpose of this paper is to perform dosimetric verification (in-phantom) of dose distributions calculated with treatment planning system (TPS) by using  2D chamber array device in HDR brachytherapy. HDR brachytherapy treatment plans’dose distribution verification is performed using the two-dimensional (2D) ionization chamber array MatriXX Evolution developed by IBA Dosimetry (IBA Dosimetry, Germany) whose detector area is covered with the Nucletron Freiburg Flap Applicator Set (Nucletron BV,Veenendaal, the Netherlands) with catheters such that the detector plane was set to 0.86 cm from the catheter plane. Fixed slabs of RW3 (Perspex) were added below the 2D-ARRAY to provide full scattering conditions. The phantom was scanned on computed tomography (CT) for treatment planning with 2.5-mm slice thickness. Based on the CT data of the phantom, three different plans were calculated by the planning system (Oncentrabrachy version 4.3, Nucletron BV) and then are exported to the VERISOFT software for comparison with measured data. For comparison of dose distributions, both dose planes – measured & calculated – were normalized  to the global maximum dose of the reference matrix (measured data set) and compared using the Gamma index method. Gamma indexes were evaluated using a dose-difference criterion of 3% and a distance criterion of 3 mm (γ≤1).The total number of evaluated dose points for the vault test case  is 9755, 98.6 % of them (9623 point) passed the criteria of acceptability (3% delta dose and 3-mm distance criteria) and 1.4% of them (132 point) failed it. The total number of evaluated dose points for the full test case is 19964, 93.6 % of them (18683 point) passed  the criteria of acceptability and 6.4% of them (1281 point) failed it. And the total number of evaluated dose points for the cylinder test case is 19871, 96.9 % of them (19258 point) passed the criteria of acceptability and 3.1% of them (613 point) failed it. By thisThe use of the two-dimensional (2D) ionization chamber array MatriXX Evolution for brachytherapy applications has been successfully demonstrated. The array measurements in these planes have shown acceptable agreement with the TPS, generally within 3% delta dose and 3-mm distance agreement criteria within each plane. The comparisons made led to make a relation between the passing percentage values to the number of the evaluated dose points for each test case and it was found that as the number of these pixels increases the possibility of having more failing points increases.

Comparing of two dimensional and three dimensional fully convolutional networks for radiotherapy dose prediction in left-sided breast cancer

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110381
Author(s):  
Xue Bai ◽  
Ze Liu ◽  
Jie Zhang ◽  
Shengye Wang ◽  
Qing Hou ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Region Of Interest ◽  
Dice Similarity Coefficient ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Dose Distributions ◽  
Convolutional Networks ◽  
Dose Prediction ◽  
Fully Convolutional Networks ◽  
Percentage Difference

Fully convolutional networks were developed for predicting optimal dose distributions for patients with left-sided breast cancer and compared the prediction accuracy between two-dimensional and three-dimensional networks. Sixty cases treated with volumetric modulated arc radiotherapy were analyzed. Among them, 50 cases were randomly chosen to conform the training set, and the remaining 10 were to construct the test set. Two U-Net fully convolutional networks predicted the dose distributions, with two-dimensional and three-dimensional convolution kernels, respectively. Computed tomography images, delineated regions of interest, or their combination were considered as input data. The accuracy of predicted results was evaluated against the clinical dose. Most types of input data retrieved a similar dose to the ground truth for organs at risk ( p > 0.05). Overall, the two-dimensional model had higher performance than the three-dimensional model ( p < 0.05). Moreover, the two-dimensional region of interest input provided the best prediction results regarding the planning target volume mean percentage difference (2.40 ± 0.18%), heart mean percentage difference (4.28 ± 2.02%), and the gamma index at 80% of the prescription dose are with tolerances of 3 mm and 3% (0.85 ± 0.03), whereas the two-dimensional combined input provided the best prediction regarding ipsilateral lung mean percentage difference (4.16 ± 1.48%), lung mean percentage difference (2.41 ± 0.95%), spinal cord mean percentage difference (0.67 ± 0.40%), and 80% Dice similarity coefficient (0.94 ± 0.01). Statistically, the two-dimensional combined inputs achieved higher prediction accuracy regarding 80% Dice similarity coefficient than the two-dimensional region of interest input (0.94 ± 0.01 vs 0.92 ± 0.01, p < 0.05). The two-dimensional data model retrieves higher performance than its three-dimensional counterpart for dose prediction, especially when using region of interest and combined inputs.

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