Joint radial trajectory correction for accelerated T2* mapping on an MR‐Linac

Author:

Bano Wajiha1,Holmes Will1,Goodburn Rosie1,Golbabaee Mohammad2,Gupta Amit3,Withey Sam3,Tree Alison3,Oelfke Uwe1,Wetscherek Andreas1

Affiliation:

1. Joint Department of Physics The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust London UK

2. Department of Engineering Mathematics University of Bristol Bristol UK

3. The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research London UK

Abstract

AbstractBackgroundT2* mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T2* maps during MR‐guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub‐volumes.PurposeThe purpose of this work is to demonstrate the feasibility of the accelerated T2* mapping technique using model‐based image reconstruction with integrated trajectory auto‐correction (TrACR) for MR‐guided radiotherapy on an MR‐Linear accelerator (MR‐Linac).Materials and methodsThe proposed method was validated in a numerical phantom, where two T2* mapping approaches (sequential and joint) were compared for different noise levels (0,0.1,0.5,1) and gradient delays ([1, ‐1] and [1, ‐2] in units of dwell time for x‐ and y‐axis, respectively). Fully sampled k‐space was retrospectively undersampled using two different undersampling patterns. Root mean square errors (RMSEs) were calculated between reconstructed T2* maps and ground truth. In vivo data was acquired twice weekly in one prostate and one head and neck cancer patient undergoing treatment on a 1.5 T MR‐Linac. Data were retrospectively undersampled and T2* maps reconstructed, with and without trajectory corrections were compared.ResultsNumerical simulations demonstrated that, for all noise levels, T2* maps reconstructed with a joint approach demonstrated less error compared to an uncorrected and sequential approach. For a noise level of 0.1, uniform undersampling and gradient delay [1, ‐1] (in units of dwell time for x‐ and y‐axis, respectively), RMSEs for sequential and joint approaches were 13.01 and 9.32 ms, respectively, which reduced to 10.92 and 5.89 ms for a gradient delay of [1, 2]. Similarly, for alternate undersampling and gradient delay [1, ‐1], RMSEs for sequential and joint approaches were 9.80 and 8.90 ms, respectively, which reduced to 9.10 and 5.40 ms for gradient delay [1, 2]. For in vivo data, T2* maps reconstructed with our proposed approach resulted in less artifacts and improved visual appearance compared to the uncorrected approach. For both prostate and head and neck cancer patients, T2* maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV).ConclusionUsing the proposed approach, a retrospective data‐driven gradient delay correction can be performed, which is particularly relevant for hybrid devices, where full information on the machine configuration is not available for image reconstruction. T2* maps were acquired in under 5 min and can be integrated into MR‐guided radiotherapy treatment workflows, which minimizes patient burden and leaves time for additional imaging for online adaptive radiotherapy on an MR‐Linac.

Funder

Cancer Research UK

Publisher

Wiley

Subject

General Medicine

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