An MRI-based mid-ventilation approach for radiotherapy of the liver

被引:17
|
作者
van de Lindt, Tessa N. [1 ]
Schubert, Gerald [2 ]
van der Heide, Uulke A. [1 ]
Sonke, Jan-Jakob [1 ]
机构
[1] Netherlands Canc Inst, Dept Radiat Oncol, Amsterdam, Netherlands
[2] Philips, MR Therapy, Vantaa, Finland
关键词
Respiratory motion; Mid-ventilation; MRI; Liver; MR-linac; ORGAN MOTION; CT SCANS; REGISTRATION;
D O I
10.1016/j.radonc.2016.10.020
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
MRI is increasingly being used in radiotherapy of the liver. The purpose of this study was to develop and validate a strategy to acquire MR images for treatment planning and image guidance in the presence of respiratory motion. By interleaving two navigator triggered MRI sequences, a fast but low-resolution image in mid ventilation (midV) and a high-resolution image in exhale were acquired efficiently. Deformable registration was applied to map the exhale image to the midV anatomy. Cine-MRI scans were acquired for motion quantification. The method was validated with a motion phantom, 10 volunteers and 1 patient with a liver tumor. The time-weighted mean position of a local structure in a cine-scan was defined as the midV-position ground truth and used to determine the accuracy of the midV-triggering method. Deformable registration accuracy was validated using the SIFT algorithm. Acquisition time of the midV/exhale-scan was 3-5 min. The accuracy of the midV-position was <= 0.5 +/- 0.5 mm for phantom motion and <= 0.9 +/- 1.2 mm for the volunteers. Mean residuals after deform able registration were <= 0.2 +/- 1.8 mm. The accuracy and reproducibility of the method are within inter and intra-fraction liver position variability (Case et al., 2009) and could in the future be incorporated in a conventional liver radiotherapy or MR-linac workflow. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:276 / 280
页数:5
相关论文
共 50 条
  • [1] Mid-ventilation based PTV margins in Stereotactic Body Radiotherapy (SBRT): A clinical evaluation
    Peulen, Heike
    Belderbos, Jose
    Rossi, Maddalena
    Sonke, Jan-Jakob
    RADIOTHERAPY AND ONCOLOGY, 2014, 110 (03) : 511 - 516
  • [2] Mid-ventilation position planning: Optimal model for dose distribution in lung tumour
    Benchalal, M.
    Cazoulat, G.
    Bellec, J.
    Leseur, J.
    Chajon, E.
    Haigron, P.
    Lena, H.
    de Crevoisier, R.
    Simon, A.
    CANCER RADIOTHERAPIE, 2012, 16 (02): : 91 - 99
  • [3] An evaluation of the mid-ventilation method for the planning of stereotactic lung plans
    Thomas, Simon J.
    Evans, Barry J.
    Harihar, Lakshmi
    Chantler, Hannah J.
    Martin, Alexander G. R.
    Harden, Susan V.
    RADIOTHERAPY AND ONCOLOGY, 2019, 137 : 110 - 116
  • [4] Mid-ventilation CT scan construction from four-dimensional respiration-correlated CT scans for radiotherapy planning of lung cancer patients
    Wolthaus, Jochem W. H.
    Schneider, Christoph
    Sonke, Jan-Jakob
    van Herk, Marcel
    Belderbos, Jose S. A.
    Rossi, Maddalena M. G.
    Lebesque, Joos V.
    Damen, Eugene M. F.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2006, 65 (05): : 1560 - 1571
  • [5] A novel anthropomorphic multimodality phantom for MRI-based radiotherapy quality assurance testing
    Singhrao, Kamal
    Fu, Jie
    Wu, Holden H.
    Hu, Peng
    Kishan, Amar U.
    Chin, Robert K.
    Lewis, John H.
    MEDICAL PHYSICS, 2020, 47 (04) : 1443 - 1451
  • [6] Quantitative Analysis of Liver Disease Using MRI-Based Radiomic Features of the Liver and Spleen
    Sack, Jordan
    Nitsch, Jennifer
    Meine, Hans
    Kikinis, Ron
    Halle, Michael
    Rutherford, Anna
    JOURNAL OF IMAGING, 2022, 8 (10)
  • [7] Quantifying the reduction of respiratory motion by mechanical ventilation with MRI for radiotherapy
    Z. van Kesteren
    J. K. Veldman
    M. J. Parkes
    M. F. Stevens
    P. Balasupramaniam
    J. G. van den Aardweg
    G. van Tienhoven
    A. Bel
    I. W. E. M. van Dijk
    Radiation Oncology, 17
  • [8] MRI-based diagnostics of dementia
    Kloeppel, S.
    Mader, I.
    NERVENHEILKUNDE, 2013, 32 (10) : 720 - 724
  • [9] Comparison of CT images with average intensity projection, free breathing, and mid-ventilation for dose calculation in lung cancer
    Khamfongkhruea, Chirasak
    Thongsawad, Sangutid
    Tannanonta, Chirapha
    Chamchod, Sasikarn
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2017, 18 (02): : 26 - 36
  • [10] Accessibility of the Cervicothoracic Junction Through an Anterior Approach An MRI-based Algorithm
    Mai, Harry T.
    Mitchell, Sean M.
    Jenkins, Tyler J.
    Savage, Jason W.
    Patel, Alpesh A.
    Hsu, Wellington K.
    SPINE, 2016, 41 (01) : 69 - 73