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Abstract #5225

Multi-fraction image reconstruction for radiotherapy on an MR-Linac

Bastien Lecoeur1,2, Prashant Nair1, Björn Eiben1, Jessica Gough3, Joan Chick1, Katharine Aitken3, Uwe Oelfke1, Wayne Luk2, and Andreas Wetscherek1
1Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom, 2Department of Computing, Imperial College London, London, United Kingdom, 3The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom

Synopsis

Keywords: Image Reconstruction, Pancreas

Motivation: Patients undergoing online-adaptive radiotherapy on an MR-Linac are imaged throughout treatment, but insufficient image quality can lead to long contouring times for pancreatic tumours.

Goal(s): We aim to improve image quality by exploiting the accumulated MRI raw data across treatment fractions, to decrease contouring times and provide high-quality reference images for real-time algorithms.

Approach: Deformation vector fields estimated from non-rigid image registration of daily images were used to reconstruct a midposition reference image combining the data across multiple treatment fractions.

Results: Reference images presented fewer streaking artefacts, but new artefacts appeared in areas with large daily changes (stomach, bowels).

Impact: Image quality on an MR-Linac can lead to slow contouring of abdominal tumours, limiting the potential of adaptive MR-guided radiotherapy. Combining raw data across fractions can improve image quality, potentially reducing clinical workloads and enabling novel real-time adaptive treatment workflows.

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Keywords