Evaluation of DISORDER: retrospective image motion correction for volumetric brain MRI in a pediatric setting

Abstract

Background and Purpose: Head motion causes image degradation in brain MRI examinations, negatively impacting image quality, especially in pediatric populations. Here, we used a retrospective motion correction technique in children and assessed image quality improvement for 3D MRI acquisitions. Material and Methods: We prospectively acquired brain MRI at 3T using 3D sequences, T1-weighted MPRAGE, T2-weighted Turbo Spin Echo and FLAIR, in 32 unsedated children, including 7 with epilepsy (age range 2-18 years). We implemented a novel motion correction technique: Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy (DISORDER). For each subject and modality, we obtained 3 reconstructions: as acquired (Aq), after DISORDER motion correction (Di), and Di with additional outlier rejection (DiOut). We analyzed 288 images quantitatively, measuring 2 objective no-reference image quality metrics: Gradient Entropy (GE) and MPRAGE White Matter Homogeneity (WM-H). As a qualitative metric, we presented blinded and randomized images to 2 expert neuroradiologists who scored them for clinical readability. Results: Both image quality metrics improved after motion correction for all modalities and improvement correlated with the amount of intrascan motion. Neuroradiologists also considered the motion corrected images as of higher quality (Wilcoxon z=-3.164 MPRAGE, z=-2.066 TSE, z=-2.645 FLAIR, for all p<0.05). Conclusions: Retrospective image motion correction with DISORDER increased image quality both from an objective and qualitative perspective. In 75% of sessions, at least one sequence was improved by this approach, indicating the benefit of this technique in un-sedated children for both clinical and research environments.

Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age

“…While we cannot completely exclude motion as a confound in the current analyses, we used a conservative two-stage QC to ensure only data of good quality and successful preprocessing were included, and thus increase our confidence that we report biological effects. It is important that future analyses incorporate an estimate of in-scanner head motion or consider additional retrospective motion correction techniques ( Vecchiato et al., 2021 ). Lastly, to characterize cortical development during the neonatal period, we described the association between increasing age and metrics of cortical morphology and microstructure.…”

Widespread, depth-dependent cortical microstructure alterations in paediatric focal epilepsy

“…All scans were acquired using the DISORDER scheme, which has demonstrated improved tolerance against motion by guaranteeing that the acquisition of every shot contains a series of samples distributed incoherently throughout k-space (Cordero-Grande et al, 2020; Vecchiato et al, 2021). With this modified sampling order, motion estimation and image reconstruction can be effectively performed jointly using a parallel k-space model in the presence of rigid motion.…”