2D Dose Reconstruction by Artificial Neural Network for Pretreatment Verification of IMRT Fields
- Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran (Iran, Islamic Republic of)
- Department of Radiology Technology, School of Allied Medicine, Shahid Beheshti University of Medical Sciences, Tehran (Iran, Islamic Republic of)
- Shohada-e-Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran (Iran, Islamic Republic of)
The use of intensity-modulated radiation therapy (IMRT) is developing rapidly in clinical routines. Because of the high complexity and uniqueness of IMRT treatment plans, patient-specific pretreatment quality assurance is generally considered a necessary prerequisite for patient treatment. In this work, we proposed a modified methodology of electronic portal imaging device (EPID)–based dose validation for pretreatment verification of IMRT fields by applying artificial neural networks (ANNs). The ANN must be trained and validated before use for pretreatment dose verification. For this purpose, 20 EPID fluence maps of IMRT prostate anterior-posterior fields were used as an input for ANN (feed forward type) and a dose map of those fluence maps that were predicted by treatment planning system as an output for ANN. After the training and validation of the neural network, the analysis of 10 IMRT prostate anterior-posterior fields showed excellent agreement between ANN output and dose map predicted by the treatment planning system. The average overall fields pass rate was 96.0% ± 0.1% with 3 mm/3% criteria. The results indicated that the ANN can be used as a low-cost, fast, and powerful tool for pretreatment dose verification, based on an EPID fluence map.
- OSTI ID:
- 23075600
- Journal Information:
- Journal of Medical Imaging and Radiation Sciences, Vol. 49, Issue 3; Other Information: Copyright (c) 2018 Published by Elsevier Inc. on behalf of Canadian Association of Medical Radiation Technologists.; Country of input: International Atomic Energy Agency (IAEA); ISSN 1939-8654
- Country of Publication:
- United States
- Language:
- English
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