Super-resolution T2-weighted 4D MRI for image guided radiotherapy

Joshua N. Freedman, David J. Collins, Oliver J. Gurney-Champion, Jamie R. McClelland, Simeon Nill, Uwe Oelfke, Martin O. Leach, Andreas Wetscherek

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)486-493
JournalRadiotherapy and oncology
Volume129
Issue number3
DOIs
Publication statusPublished - 2018

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