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CBCT‐based synthetic CT generation using deep‐attention cycleGAN for pancreatic adaptive radiotherapy
Author(s) -
Liu Yingzi,
Lei Yang,
Wang Tonghe,
Fu Yabo,
Tang Xiangyang,
Curran Walter J.,
Liu Tian,
Patel Pretesh,
Yang Xiaofeng
Publication year - 2020
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.14121
Subject(s) - hounsfield scale , medicine , cone beam computed tomography , nuclear medicine , radiation treatment planning , image guided radiation therapy , cone beam ct , dose volume histogram , radiation therapy , radiology , computed tomography
Purpose Current clinical application of cone‐beam CT (CBCT) is limited to patient setup. Imaging artifacts and Hounsfield unit (HU) inaccuracy make the process of CBCT‐based adaptive planning presently impractical. In this study, we developed a deep‐learning‐based approach to improve CBCT image quality and HU accuracy for potential extended clinical use in CBCT‐guided pancreatic adaptive radiotherapy. Methods Thirty patients previously treated with pancreas SBRT were included. The CBCT acquired prior to the first fraction of treatment was registered to the planning CT for training and generation of synthetic CT (sCT). A self‐attention cycle generative adversarial network (cycleGAN) was used to generate CBCT‐based sCT. For the cohort of 30 patients, the CT‐based contours and treatment plans were transferred to the first fraction CBCTs and sCTs for dosimetric comparison. Results At the site of abdomen, mean absolute error (MAE) between CT and sCT was 56.89 ± 13.84 HU, comparing to 81.06 ± 15.86 HU between CT and the raw CBCT. No significant differences ( P > 0.05) were observed in the PTV and OAR dose‐volume‐histogram (DVH) metrics between the CT‐ and sCT‐based plans, while significant differences ( P < 0.05) were found between the CT‐ and the CBCT‐based plans. Conclusions The image similarity and dosimetric agreement between the CT and sCT‐based plans validated the dose calculation accuracy carried by sCT. The CBCT‐based sCT approach can potentially increase treatment precision and thus minimize gastrointestinal toxicity.