Chuter, R, Prestwich, R, Bird, D et al. (4 more authors) (2017) The use of deformable image registration to integrate diagnostic MRI into the radiotherapy planning pathway for head and neck cancer. Radiotherapy and Oncology, 122 (2). pp. 229-235. ISSN 0167-8140
Abstract
To assess the accuracy of gross tumour volume (GTV) delineation for head and neck squamous cell carcinoma (HNSCC) using a diagnostic position MRI (MRI-D) deformably registered to the planning CT (pCT), by comparison with a dedicated planning position MRI (MRI-RT).Fourteen patients with HNSCC underwent a T1-weighted MRI-D and MRI-RT. A reference GTV was defined as that delineated on MRI-RT rigidly registered to pCT. GTVs were delineated on: MRI-D and then registered to pCT by deformable image registration over the whole image (DIR-whole); MRI-D and then registered to pCT with rigid registration over a region of interest defined as GTV+3cm (Rigid-ROI); and on the pCT alone. These were compared using positional metrics to the reference.GTVs delineated on MRI-D followed by DIR-whole were significantly more accurate than those delineated on CT alone. The mean Dice Similarity Coefficient was 0.6 and 0.72 for pCT and DIR-whole respectively. Use of MRI-D with Rigid-ROI provided no advantage over CT-only delineation.Contouring on MRI-RT rigidly registered to pCT should be considered as the gold standard for HNSCC. In radiotherapy centres lacking a dedicated MRI-RT, the use of an MRI-D with DIR-whole offers a significant advantage for the accuracy of GTV delineation over contouring on pCT alone.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Image registration; Diagnostic MRI; Head and neck |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Aug 2016 10:17 |
Last Modified: | 20 Apr 2017 12:14 |
Published Version: | https://doi.org/10.1016/j.radonc.2016.07.016 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.radonc.2016.07.016 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:103643 |