期刊
RADIOTHERAPY AND ONCOLOGY
卷 150, 期 -, 页码 211-218出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2020.06.049
关键词
Synthetic CT; Nasopharyngeal carcinoma; MRI-only radiotherapy; Generative adversarial networks; Conditional GAN; Cycle GAN
资金
- National Key R&D Program of China [2017YFC0113200]
- Science and Technology Program of Guangdong Province, China [2015B020214002]
- Science and Technology Program of Guangzhou, China [201607010199]
Background and purpose: To investigate the feasibility of synthesizing computed tomography (CT) images from magnetic resonance (MR) images using generative adversarial networks (GANs) for nasopharyngeal carcinoma (NPC) intensity-modulated radiotherapy (IMRT) planning. Materials and methods: Conventional T1-weighted MR images and CT images were acquired from 173 NPC patients. The MR and CT images of 28 patients were randomly chosen as the independent tested set. The remaining images were used to build a conditional GAN (cGAN) and a cycle-consistency GAN (cycleGAN). A U-net was used as the generator in cGAN, whereas a residual-Unet was used as the generator in cycleGAN. The cGAN was trained using the deformable registered MR-CT image pairs, whereas the cycleGAN was trained using the unregistered MR and CT images. The generated synthetic CT (SCT) images from cGAN and cycleGAN were compared with the true CT images with respect to their Hounsfield Unit (HU) discrepancy and dosimetric accuracy for NPC IMRT plans. Results: The mean absolute errors within the body were 69.67 +/- 9.27 HU and 100.62 +/- 7.39 HU for the cGAN and cycleGAN, respectively. The 2%/2-mm gamma passing rates were (98.68 +/- 0.94)% and (98.52 +/- 1.13)% for the cGAN and cycleGAN, respectively. Meanwhile, the absolute dose discrepancies within the regions of interest were (0.49 +/- 0.24)% and (0.62 +/- 0.36)%, respectively. Conclusion: Both cGAN and cycleGAN could swiftly generate accurate SCT volume images from MR images, with high dosimetric accuracy for NPC IMRT planning. cGAN was preferable if high-quality MR-CT image pairs were available. (C) 2020 The Author(s). Published by Elsevier B.V. Radiotherapy and Oncology 150 (2020) 217-224 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据