Literature DB >> 27825795

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

Tessa N van de Lindt1, Gerald Schubert2, Uulke A van der Heide1, Jan-Jakob Sonke3.   

Abstract

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 3-5min. The accuracy of the midV-position was ⩽0.5±0.5mm for phantom motion and ⩽0.9±1.2mm for the volunteers. Mean residuals after deformable registration were ⩽0.2±1.8mm. 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. Copyright Â
© 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Liver; MR-linac; MRI; Mid-ventilation; Respiratory motion

Mesh:

Year:  2016        PMID: 27825795     DOI: 10.1016/j.radonc.2016.10.020

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  1 in total

1.  Retrospective four-dimensional magnetic resonance imaging of liver: Method development.

Authors:  Henna Kavaluus; Tiina Seppälä; Lauri Koivula; Eero Salli; Juhani Collan; Kauko Saarilahti; Mikko Tenhunen
Journal:  J Appl Clin Med Phys       Date:  2020-12-03       Impact factor: 2.102

  1 in total

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