Performance studies of four-dimensional cone beam computed tomography

被引:28
|
作者
Qi, Zhihua [1 ]
Chen, Guang-Hong [1 ,2 ,3 ]
机构
[1] Univ Wisconsin Madison, Dept Med Phys, Madison, WI 53705 USA
[2] Univ Wisconsin Madison, Dept Radiol, Madison, WI 53705 USA
[3] Univ Wisconsin Madison, Dept Human Oncol, Madison, WI 53705 USA
来源
PHYSICS IN MEDICINE AND BIOLOGY | 2011年 / 56卷 / 20期
基金
美国国家卫生研究院;
关键词
DEFORMABLE REGISTRATION; IMAGE REGISTRATION; RESPIRATORY MOTION; CT; MODEL; RECONSTRUCTION; ARTIFACTS;
D O I
10.1088/0031-9155/56/20/013
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Four-dimensional cone beam computed tomography (4DCBCT) has been proposed to characterize the breathing motion of tumors before radiotherapy treatment. However, when the acquired cone beam projection data are retrospectively gated into several respiratory phases, the available data to reconstruct each phase is under-sampled and thus causes streaking artifacts in the reconstructed images. To solve the under-sampling problem and improve image quality in 4DCBCT, various methods have been developed. This paper presents performance studies of three different 4DCBCT methods based on different reconstruction algorithms. The aims of this paper are to study (1) the relationship between the accuracy of the extracted motion trajectories and the data acquisition time of a 4DCBCT scan and (2) the relationship between the accuracy of the extracted motion trajectories and the number of phase bins used to sort projection data. These aims will be applied to three different 4DCBCT methods: conventional filtered backprojection reconstruction (FBP), FBP with McKinnon-Bates correction (MB) and prior image constrained compressed sensing (PICCS) reconstruction. A hybrid phantom consisting of realistic chest anatomy and a moving elliptical object with known 3D motion trajectories was constructed by superimposing the analytical projection data of the moving object to the simulated projection data from a chest CT volume dataset. CBCT scans with gantry rotation times from 1 to 4 min were simulated, and the generated projection data were sorted into 5, 10 and 20 phase bins before different methods were used to reconstruct 4D images. The motion trajectories of the moving object were extracted using a fast free-form deformable registration algorithm. The root mean square errors (RMSE) of the extracted motion trajectories were evaluated for all simulated cases to quantitatively study the performance. The results demonstrate (1) longer acquisition times result in more accurate motion delineation for each method; (2) ten or more phase bins are necessary in 4DCBCT to ensure sufficient temporal resolution in tumor motion and (3) to achieve the same performance as FBP-4DCBCT with a 4 min data acquisition time, MB-4DCBCT and PICCS-4DCBCT need about 2- and 1 min data acquisition times, respectively.
引用
收藏
页码:6709 / 6721
页数:13
相关论文
共 50 条
  • [1] Registration-Based Reconstruction of Four-Dimensional Cone Beam Computed Tomography
    Christoffersen, Christian P. V.
    Hansen, David
    Poulsen, Per
    Sorensen, Thomas Sangild
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2013, 32 (11) : 2064 - 2077
  • [2] Target-Specific Optimization of Four-Dimensional Cone Beam Computed Tomography
    Ahmad, M.
    Pan, T.
    [J]. MEDICAL PHYSICS, 2012, 39 (06) : 3682 - 3682
  • [3] Target-specific optimization of four-dimensional cone beam computed tomography
    Ahmad, Moiz
    Pan, Tinsu
    [J]. MEDICAL PHYSICS, 2012, 39 (09) : 5683 - 5696
  • [4] Streaking Artifacts Reduction in Four-Dimensional Cone-Beam Computed Tomography
    Leng, S.
    Zambelli, J.
    Tolakanahalli, R.
    Nett, B.
    Munro, P.
    Star-Lack, J.
    Paliwal, B.
    Chen, G.
    [J]. MEDICAL PHYSICS, 2008, 35 (06)
  • [5] Streaking artifacts reduction in four-dimensional cone-beam computed tomography
    Leng, Shuai
    Zambelli, Joseph
    Tolakanahalli, Ranjini
    Nett, Brian
    Munro, Peter
    Star-Lack, Joshua
    Paliwal, Bhudatt
    Chena, Guang-Hong
    [J]. MEDICAL PHYSICS, 2008, 35 (10) : 4649 - 4659
  • [6] Both four-dimensional computed tomography and four-dimensional cone beam computed tomography under-predict lung target motion during radiotherapy
    Steiner, Elisabeth
    Shieh, Chun-Chien
    Caillet, Vincent
    Booth, Jeremy
    O'Brien, Ricky
    Briggs, Adam
    Hardcastle, Nicholas
    Jayamanne, Dasantha
    Szymura, Kathryn
    Eade, Thomas
    Keall, Paul
    [J]. RADIOTHERAPY AND ONCOLOGY, 2019, 135 : 65 - 73
  • [7] Target displacement evaluation for fluoroscopic and four-dimensional cone-beam computed tomography
    Iramina, H.
    Nakamura, M.
    Iizuka, Y.
    Matsuo, Y.
    Mizowaki, T.
    Hiraoka, M.
    Kanno, I.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2016, 119 : S148 - S148
  • [8] Four-dimensional cone-beam computed tomography using an on-board imager
    Li, Tianfang
    Xing, Lei
    Munro, Peter
    McGuinness, Christopher
    Chao, Ming
    Yang, Yong
    Loo, Bill
    Koong, Albert
    [J]. MEDICAL PHYSICS, 2006, 33 (10) : 3825 - 3833
  • [9] Correction: Application of four-dimensional cone beam computed tomography in lung cancer radiotherapy
    Muyasha Abulimiti
    Xu Yang
    Minghui Li
    Fukui Huan
    Yanxin Zhang
    Liang Jun
    [J]. Radiation Oncology, 18
  • [10] Evaluating the four-dimensional cone beam computed tomography with varying gantry rotation speed
    Yoganathan, S. A.
    Maria, K. J.
    Ali, Shajahan Mohamed
    Agarwal, Arpita
    Mishra, Surendra P.
    Kumar, Shaleen
    [J]. BRITISH JOURNAL OF RADIOLOGY, 2016, 89 (1060):