Scattered slice SHARD reconstruction for motion correction in multi-shell diffusion MRI

• Published in: NeuroImage (Orlando, Fla.) Vol. 225; p. 117437
• Main Authors: Christiaens, Daan, Cordero-Grande, Lucilio, Pietsch, Maximilian, Hutter, Jana, Price, Anthony N., Hughes, Emer J., Vecchiato, Katy, Deprez, Maria, Edwards, A. David, Hajnal, Joseph V., Tournier, J-Donald
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15-01-2021; Elsevier Limited; Academic Press; Elsevier
• Subjects: Brain - diagnostic imaging; Connectome; Diffusion Magnetic Resonance Imaging - methods; Diffusion MRI; Humans; Image Processing, Computer-Assisted - methods; Infant, Newborn; Magnetic resonance imaging; Motion correction; Movement; Multi-shell; Neonatal imaging; Slice-to-volume reconstruction; SVD; Multi-shell; GMM; RMSE; Slice-to-volume reconstruction; SHARD; dMRI; Motion correction; ODF; SSP; Neonatal imaging; SH; SNR; FWHM; Diffusion MRI; dHCP; EPI
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2020.117437

•Subject motion in dMRI leads to a set of scattered slices with unique contrast.•We introduce a slice-to-volume reconstruction framework for multi-shell HARDI data•Based on a data-driven representation as spherical harmonics and radial decomposition (SHARD).•The method is evaluated in test-retest scans and in the neonatal dHCP cohort.•Results show robust reconstruction in severely motion-corrupted scans.
Diffusion MRI offers a unique probe into neural microstructure and connectivity in the developing brain. However, analysis of neonatal brain imaging data is complicated by inevitable subject motion, leading to a series of scattered slices that need to be aligned within and across diffusion-weighted contrasts. Here, we develop a reconstruction method for scattered slice multi-shell high angular resolution diffusion imaging (HARDI) data, jointly estimating an uncorrupted data representation and motion parameters at the slice or multiband excitation level. The reconstruction relies on data-driven representation of multi-shell HARDI data using a bespoke spherical harmonics and radial decomposition (SHARD), which avoids imposing model assumptions, thus facilitating to compare various microstructure imaging methods in the reconstructed output. Furthermore, the proposed framework integrates slice-level outlier rejection, distortion correction, and slice profile correction. We evaluate the method in the neonatal cohort of the developing Human Connectome Project (650 scans). Validation experiments demonstrate accurate slice-level motion correction across the age range and across the range of motion in the population. Results in the neonatal data show successful reconstruction even in severely motion-corrupted subjects. In addition, we illustrate how local tissue modelling can extract advanced microstructure features such as orientation distribution functions from the motion-corrected reconstructions.