Dynamic field mapping and motion correction using interleaved double spin-echo diffusion MRI

Hutter, Jana, Christiaens, Daan, Deprez, Maria, Cordero-Grande, Lucilio, Slator, Paddy ORCID: https://orcid.org/0000-0001-6967-989X, Price, Anthony, Rutherford, Mary and Hajnal, Joseph V. 2017. Dynamic field mapping and motion correction using interleaved double spin-echo diffusion MRI. Presented at: International Conference on Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2017, Quebec City, 11 - 13 September 2017. Medical Image Computing and Computer Assisted Intervention − MICCAI 2017. , vol.10433 Springer International Publishing AG, pp. 523-531. 10.1007/978-3-319-66182-7_60

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Abstract

Diffusion MRI (dMRI) analysis requires combining data from many images and this generally requires corrections for image distortion and for subject motion during what may be a prolonged acquisition. Particularly in non-brain applications, changes in pose such as respiration can cause image distortion to be time varying, impeding static field map-based correction. In addition, motion and distortion correction is challenging at high b-values due to the low signal-to-noise ratio (SNR). In this work we develop a new approach that breaks the traditional “one-volume, one-weighting” paradigm by interleaving low-b and high-b slices, and combine this with a reverse phase-encoded double-spin echo sequence. Interspersing low and high b-value slices ensures that the low-b, high-SNR data is in close spatial and temporal proximity to support dynamic field map estimation from the double spin-echo acquisition and image-based motion correction. This information is propagated to high-b slices with interpolation across space and time. The method is tested in the challenging environment of fetal dMRI and it is demonstrated using data from 8 pregnant volunteers that combining dynamic distortion correction with slice-by-slice motion correction increases data consistency to facilitate advanced analyses where conventional methods fail.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Springer International Publishing AG
ISBN:	978-3-319-66182-7
Last Modified:	06 Jul 2023 14:30
URI:	https://orca.cardiff.ac.uk/id/eprint/160740

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