Study of peripheral dose from low-dose CT to adaptive radiotherapy of postoperative prostate cancer

被引:1
作者
Gan, Guanghui [1 ]
Gong, Wei [1 ]
Jia, Lecheng [2 ,3 ]
Zhang, Wei [4 ]
Wang, Shimei [5 ]
Zhou, Juying [1 ]
Jiang, Hua [1 ]
机构
[1] Soochow Univ, Affiliated Hosp 1, Dept Radiat Oncol, Suzhou, Peoples R China
[2] Shenzhen United Imaging Res Inst Innovat Med Equip, Real Time Lab, Shenzhen, Peoples R China
[3] Zhejiang Engn Res Ctr Innovat & Applicat Intellige, Wenzhou, Peoples R China
[4] Shanghai United Imaging Healthcare Co Ltd, Radiotherapy Business Unit, Shanghai, Peoples R China
[5] United Imaging Healthcare Grp, Cent Res Inst, Shanghai, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2023年 / 13卷
关键词
peripheral dose; adaptive radiotherapy; low-dose CT; deep learning; prostate cancer; CONE-BEAM-CT; GUIDED RADIATION-THERAPY; COMPUTED-TOMOGRAPHY; MOTION; IMRT;
D O I
10.3389/fonc.2023.1227946
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
ObjectivesThe increasing use of computed tomography (CT) for adaptive radiotherapy (ART) has raised concerns about the peripheral radiation dose. This study investigates the feasibility of low-dose CT (LDCT) for postoperative prostate cancer ART to reduce the peripheral radiation dose, and evaluates the peripheral radiation dose of different imaging techniques and propose an image enhancement method based on deep learning for LDCT.Materials and methodsA linear accelerator integrated with a 16-slice fan-beam CT from UIH (United Imaging Healthcare, China) was utilized for prostate cancer ART. To reduce the tube current of CT for ART, LDCT was acquired. Peripheral doses of normal-dose CT (NDCT), LDCT, and mega-voltage computed tomography (MV-CT) were measured using a cylindrical Virtual Water (TM) phantom and an ion chamber. A deep learning model of LDCT for abdominal and pelvic-based cycle-consistent generative adversarial network was employed to enhance the image quality of LDCT. Six postoperative prostate cancer patients were selected to evaluate the feasibility of low-dose CT network restoration images (RCT) by the deep learning model for ART. The three aspects among NDCT, LDCT, and RCT were compared: the Hounsfield Unit (HU) of the tissue, the Dice Similarity Coefficient (DSC) criterion of target and organ, and dose calculation differences.ResultsIn terms of peripheral dose, the LDCT had a surface measurement point dose of approximately 1.85 mGy at the scanning field, while the doses of NDCT and MV-CT were higher at 22.85 mGy and 29.97 mGy, respectively. However, the image quality of LDCT was worse than NDCT. When compared to LDCT, the tissue HU value of RCT showed a significant improvement and was closer to that of NDCT. The DSC results for target CTV between RCT and NDCT were also impressive, reaching up to 94% for bladder and femoral heads, 98% for rectum, and 94% for the target organ. Additionally, the dose calculation differences for the ART plan based on LDCT and NDCT were all within 1%. Overall, these findings suggest that RCT can provide an effective alternative to NDCT and MV-CT with similar or better outcomes in HU values of tissue and organ damage. More testing is required before clinical application.
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页数:10
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共 24 条
  • [1] Imaging doses from the Elekta Synergy X-ray cone beam CT system
    Amer, A.
    Marchant, T.
    Sykes, J.
    Czajka, J.
    Moore, C.
    [J]. BRITISH JOURNAL OF RADIOLOGY, 2007, 80 (954) : 476 - 482
  • [2] MR-guidance in clinical reality: current treatment challenges and future perspectives
    Corradini, S.
    Alongi, F.
    Andratschke, N.
    Belka, C.
    Boldrini, L.
    Cellini, F.
    Debus, J.
    Guckenberger, M.
    Hoerner-Rieber, J.
    Lagerwaard, F. J.
    Mazzola, R.
    Palacios, M. A.
    Philippens, M. E. P.
    Raaijmakers, C. P. J.
    Terhaard, C. H. J.
    Valentini, V.
    Niyazi, M.
    [J]. RADIATION ONCOLOGY, 2019, 14 (1)
  • [3] Advances in image-guided radiation therapy
    Dawson, Laura A.
    Jaffray, David A.
    [J]. JOURNAL OF CLINICAL ONCOLOGY, 2007, 25 (08) : 938 - 946
  • [4] Online adaptive radiotherapy compared to plan selection for rectal cancer: quantifying the benefit
    de Jong, R.
    Crama, F.
    Visser, J.
    van Wieringen, N.
    Wiersma, J.
    Geijsen, E. D.
    Bel, A.
    [J]. RADIATION ONCOLOGY, 2020, 15 (01)
  • [5] Accurate patient dosimetry of kilovoltage cone-beam CT in radiation therapy
    Ding, George X.
    Duggan, Dennis M.
    Coffey, Charles W.
    [J]. MEDICAL PHYSICS, 2008, 35 (03) : 1135 - 1144
  • [6] Deep learning-based low-dose CT for adaptive radiotherapy of abdominal and pelvic tumors
    Gong, Wei
    Yao, Yiming
    Ni, Jie
    Jiang, Hua
    Jia, Lecheng
    Xiong, Weiqi
    Zhang, Wei
    He, Shumeng
    Wei, Ziquan
    Zhou, Juying
    [J]. FRONTIERS IN ONCOLOGY, 2022, 12
  • [7] CycleGAN denoising of extreme low-dose cardiac CT using wavelet-assisted noise disentanglement
    Gu, Jawook
    Yang, Tae Seong
    Ye, Jong Chul
    Yang, Dong Hyun
    [J]. MEDICAL IMAGE ANALYSIS, 2021, 74
  • [8] Patient dose from kilovoltage cone beam computed tomography imaging in radiation therapy
    Islam, Mohammad K.
    Purdie, Thomas G.
    Norrlinger, Bernhard D.
    Alasti, Hamideh
    Moseley, Douglas J.
    Sharpe, Michael B.
    Siewerdsen, Jeffrey H.
    Jaffray, David A.
    [J]. MEDICAL PHYSICS, 2006, 33 (06) : 1573 - 1582
  • [9] Image-to-Image Translation with Conditional Adversarial Networks
    Isola, Phillip
    Zhu, Jun-Yan
    Zhou, Tinghui
    Efros, Alexei A.
    [J]. 30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017), 2017, : 5967 - 5976
  • [10] Radiation dose from cone beam computed tomography for image-guided radiation therapy
    Kan, Monica W. K.
    Leung, Lucullus H. T.
    Wong, Wicger
    Lam, Nelson
    [J]. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2008, 70 (01): : 272 - 279