Validation of image registration and fusion of MV CBCT and planning CT for radiotherapy treatment planning

被引:0
|
作者
T. Hannah Mary Thomas
D. Devakumar
S. Balukrishna
Henry Finlay Godson
B. Paul Ravindran
机构
[1] Christian Medical College,Department of Bioengineering
[2] Christian Medical College,Department of Nuclear Medicine
[3] Christian Medical College,Department of Radiotherapy
关键词
Megavoltage cone beam CT; Registration; Planning CT; Fusion; Validation;
D O I
暂无
中图分类号
学科分类号
摘要
In areas like adaptive therapy, multi-phase radiotherapy, and single fraction palliative treatment or in the treatment of patients with metal implants where megavoltage(MV) CT could be considered as a treatment planning modality, the reduced contrast in the MV CT images could lead to limited accuracy in localization of the structures. This would affect the precision of the treatment. In this study, as an extension our previous work on bespoke MV cone beam CT (MV CBCT), we propose to register the MV CBCT with kilovoltage (kV) CT for treatment planning. The MV CBCT images registered with kV CT would be effective for treatment planning as it would account for the inadequate soft tissue information in the MV CBCT and would allow comparison of changes in patient dimensions and assist in localization of the structures. The intensity based registration algorithm of the BrainSCAN therapy planning software was used for image registration of the MV CBCT and kV CT images. The accuracy of the registration was validated using qualitative and quantitative measures. The effect of image quality on the level of agreement between the contouring done on both the MV CBCT and kV CT was assessed by comparing the volumes of six structures delineated. To assess the level of agreement between the plans after the registration, two independent plans were generated on the MV CBCT and the planning CT using the posterior fossa of the skull as the target. The dose volume histograms and conformity indices of the plans were compared. The results of this study show that treatment planning with MV CBCT images would be effective, using additional anatomical structure information derived from registering the MV CBCT image with a standard kVCT.
引用
收藏
页码:441 / 447
页数:6
相关论文
共 50 条
  • [1] Validation of image registration and fusion of MV CBCT and planning CT for radiotherapy treatment planning
    Thomas, T. Hannah Mary
    Devakumar, D.
    Balukrishna, S.
    Godson, Henry Finlay
    Ravindran, B. Paul
    AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE, 2011, 34 (04) : 441 - 447
  • [2] Validation of Planning CT to CBCT Deformable Image Registration-Based Dose Calculation for Prostate Cancer Adaptive Radiotherapy
    Zhang, X.
    MEDICAL PHYSICS, 2019, 46 (06) : E384 - E384
  • [3] Radiotherapy treatment planning: benefits of CT-MR image registration and fusion in tumor volume delineation
    Djan, Igor
    Petrovic, Borislava
    Erak, Marko
    Nikolic, Ivan
    Lucic, Silvija
    VOJNOSANITETSKI PREGLED, 2013, 70 (08) : 735 - 739
  • [4] CT and PET lung image registration and fusion in radiotherapy treatment planning using the chamfer-matching
    Cai, JL
    Chu, JCH
    Recine, D
    Sharma, M
    Nguyen, C
    Rodebaugh, R
    Saxena, VA
    Ali, A
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 1999, 43 (04): : 883 - 891
  • [5] Image registration and data fusion for treatment planning
    Kessler, M
    MEDICAL PHYSICS, 2004, 31 (06) : 1806 - 1806
  • [6] Automatic image registration of diagnostic and radiotherapy treatment planning CT head images
    Vaarkamp, J
    Barber, DC
    Conway, J
    Robinson, MH
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2000, 47 (01): : 225 - 230
  • [7] Evaluation of Synthetic CT Images Generated by Deformable Image Registration of Outdated Planning CT to CBCT of Treatment Day
    Yoon, J.
    Yeo, I.
    MEDICAL PHYSICS, 2021, 48 (06)
  • [8] Nonrigid image registration for head and neck cancer radiotherapy treatment planning with PET/CT
    Ireland, Rob H.
    Dyker, Karen E.
    Barber, David C.
    Wood, Steven M.
    Hanney, Michael B.
    Tindale, Wendy B.
    Woodhouse, Neil
    Hoggard, Nigel
    Conway, John
    Robinson, Martin H.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2007, 68 (03): : 952 - 957
  • [9] Multimodality Image Registration and Fusion Using Deep Learning for Radiotherapy Planning
    Ratke, A.
    Darsht, E.
    Baeumer, C.
    Spaan, B.
    Kroeninger, K.
    MEDICAL PHYSICS, 2022, 49 (06) : E737 - E737
  • [10] Deformable Image Registration of Diagnostical CT and Planning CT for Breast Conserving Radiotherapy
    Xie, X.
    Yan, H.
    Dai, J.
    MEDICAL PHYSICS, 2020, 47 (06) : E599 - E599