1st Materials Research Society Indonesia Conference and Congress | |
The performance of the AAA and Acurox XB algorithms in the case of lung cancer | |
Zulfani, R.^1 ; Fadli, M.^1,2 ; Pawiro, S.A.^1 | |
Department of Physics, Faculty of Mathematics and Natural Sciences, University of Indonesia, Depok | |
16424, Indonesia^1 | |
Department of Radiotherapy MRCCC Siloam Hospitals Semanggi, Jakarta, Indonesia^2 | |
关键词: Anisotropic analytical algorithms; Dose prescription; Dose simulations; Intensity-modulated radiotherapy; Largest deviation; Measurements of; Planning target volumes; Therapy planning; | |
Others : https://iopscience.iop.org/article/10.1088/1757-899X/432/1/012022/pdf DOI : 10.1088/1757-899X/432/1/012022 |
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来源: IOP | |
【 摘 要 】
The Anisotropic Analytical Algorithm (AAA) and Acuros XB algorithms in advanced technique therapy planning has been implemented for Intensity Modulated Radiotherapy (IMRT) and Volumetric Arc Modulated Radiotherapy (VMAT) techniques. This study aimed to verify the dose simulation of IMRT and VMAT in planning target volume (PTV) of lung cancer cases. All planning were created using TPS Eclipse version 13.0.47. The IMRT planning were created using 7 fields whereas the VMAT technique employed the double arc with target dose prescription of 200 cGy each fraction. The results showed that the small decrepancy between planning and measurements of PTV in left and right lung cancer has occurred in VMAT technique, whereas Acuros XB algorithm had better planning quality than Anisotropic Analytical Algorithm (AAA) with differences about of 0,56%. In the organ at risk of left and right lung cancer, there was no significant difference between Acuros XB and Anisotropic Analytical Algorithm (AAA) with the largest deviation range obtained in simulated heart organ with around of ± 9%. We concluded that the Acuros XB algorithm has better performance than Anisotropic Analytical Algorithm (AAA) by a factor of approximately ± 1%.
【 预 览 】
Files | Size | Format | View |
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The performance of the AAA and Acurox XB algorithms in the case of lung cancer | 611KB | download |