Super-resolution T2-weighted 4D MRI for image guided radiotherapy.
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Date
2018-12-01ICR Author
Author
Freedman, JN
Collins, DJ
Gurney-Champion, OJ
McClelland, JR
Nill, S
Oelfke, U
Leach, MO
Wetscherek, A
Type
Journal Article
Metadata
Show full item recordAbstract
BACKGROUND AND PURPOSE: The superior soft-tissue contrast of 4D-T2w MRI motivates its use for delineation in radiotherapy treatment planning. We address current limitations of slice-selective implementations, including thick slices and artefacts originating from data incompleteness and variable breathing. MATERIALS AND METHODS: A method was developed to calculate midposition and 4D-T2w images of the whole thorax from continuously acquired axial and sagittal 2D-T2w MRI (1.5 × 1.5 × 5.0 mm3). The method employed image-derived respiratory surrogates, deformable image registration and super-resolution reconstruction. Volunteer imaging and a respiratory motion phantom were used for validation. The minimum number of dynamic acquisitions needed to calculate a representative midposition image was investigated by retrospectively subsampling the data (10-30 dynamic acquisitions). RESULTS: Super-resolution 4D-T2w MRI (1.0 × 1.0 × 1.0 mm3, 8 respiratory phases) did not suffer from data incompleteness and exhibited reduced stitching artefacts compared to sorted multi-slice MRI. Experiments using a respiratory motion phantom and colour-intensity projection images demonstrated a minor underestimation of the motion range. Midposition diaphragm differences in retrospectively subsampled acquisitions were <1.1 mm compared to the full dataset. 10 dynamic acquisitions were found sufficient to generate midposition MRI. CONCLUSIONS: A motion-modelling and super-resolution method was developed to calculate high quality 4D/midposition T2w MRI from orthogonal 2D-T2w MRI.
Collections
Subject
Humans
Imaging, Three-Dimensional
Retrospective Studies
Phantoms, Imaging
Magnetic Resonance Imaging, Interventional
Radiotherapy, Image-Guided
Research team
Magnetic Resonance
Radiotherapy Physics Modelling
Language
eng
Date accepted
2018-05-14
License start date
2018-12
Citation
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2018, 129 (3), pp. 486 - 493
Publisher
ELSEVIER IRELAND LTD