Is it time to switch your T1W sequence? Assessing the impact of prospective motion correction on the reliability and quality of structural imaging

Abstract

New large neuroimaging studies, such as the Adolescent Brain Cognitive Development study (ABCD) and Human Connectome Project (HCP) Development studies are adopting a new T1-weighted imaging sequence with prospective motion correction (PMC) in favor of the more traditional 3-Dimensional Magnetization-Prepared Rapid Gradient-Echo Imaging (MPRAGE) sequence. Here, we used a developmental dataset (ages 5–21, N = 348) from the Healthy Brain Network (HBN) Initiative to directly compare two widely used MRI structural sequences: one based on the Human Connectome Project (MPRAGE) and another based on the ABCD study (MPRAGE+PMC). We aimed to determine if the morphometric measurements obtained from both protocols are equivalent or if one sequence has a clear advantage over the other. The sequences were also compared through quality control measurements. Inter- and intra-sequence reliability were assessed with another set of participants ( N = 71) from HBN that performed two MPRAGE and two MPRAGE+PMC sequences within the same imaging session, with one MPRAGE (MPRAGE1) and MPRAGE+PMC (MPRAGE+PMC1) pair at the beginning of the session and another pair (MPRAGE2 and MPRAGE+PMC2) at the end of the session. Intraclass correlation coefficients (ICC) scores for morphometric measurements such as volume and cortical thickness showed that intra-sequence reliability is the highest with the two MPRAGE+PMC sequences and lowest with the two MPRAGE sequences. Regarding inter-sequence reliability, ICC scores were higher for the MPRAGE1 - MPRAGE+PMC1 pair at the beginning of the session than the MPRAGE1 - MPRAGE2 pair, possibly due to the higher motion artifacts in the MPRAGE2 run. Results also indicated that the MPRAGE+PMC sequence is robust, but not impervious, to high head motion. For quality control metrics, the traditional MPRAGE yielded better results than MPRAGE+PMC in 5 of the 8 measurements. In conclusion, morphometric measurements evaluated here showed high inter-sequence reliability between the MPRAGE and MPRAGE+PMC sequences, especially in images with low head motion. We suggest that studies targeting hyperkinetic populations use the MPRAGE+PMC sequence, given its robustness to head motion and higher reliability scores. However, neuroimaging researchers studying non-hyperkinetic participants can choose either MPRAGE or MPRAGE+PMC sequences, but should carefully consider the apparent tradeoff between relatively increased reliability, but reduced quality control metrics when using the MPRAGE+PMC sequence.

A longitudinal resource for studying connectome development and its psychiatric associations during childhood

“…We also found high correlations in FD among the different functional scans (r: 0.496-0.767), as well as between the functional scans and the Euler number (r: 0.469-0.674). This high level of correlation between quality measures for different functional scans, as well as between functional and structural scans, has also been observed in other studies 89,92,93 . During the collection of fMRIs, physiological data (cardiac and respiratory) were obtained during scanning.…”

Predicting multimodal MRI outcomes in children with neurodevelopmental conditions following MRI simulator training

“…This was motivated by the explicit goal to identify factors that may guide decisions before scheduling a scan session. A range of approaches aimed to improve data collection during scans continue to emerge (Vanderwal et al 2015; Dosenbach et al 2017; Ai et al 2020; Power et al 2019). Each has strengths and weaknesses and no one is applicable to a range of different scans and populations to date, unlike MRI simulator training.…”

“…For example, FIRMM has been shown to be useful for functional MRI data collection (Dosenbach et al 2017) however, its efficacy with structural and diffusion MRI data is yet to be established. Scans including prospective motion correction have been shown promising for structural scans (e.g., T1-weighted) (Ai et al 2020). CaseForge has been shown to be effective at reducing head motion in small samples of children and two adults completing R-fMRI (Power et al 2019; Lynch et al 2021), but not in another sample of adults completing task-fMRI (Jolly, Sadhukha, and Chang 2020, 2021).…”

“…As a result, the prevailing wisdom remains -the best way to handle motion is to prevent it (Ai et al 2020) . In this regard, efforts to minimize motion during MRI scanning such as passive movie viewing (Vanderwal et al 2015) , real-time motion monitoring and/or feedback (Dosenbach et al 2017;Greene et al 2018; Krause et al 2019) , prospective motion correction (Ai et al 2020) , and head stabilizers (Power et al 2019) have been reported to be effective. However, they may not all apply across the broad range of MRI modalities and specialized sequences, the list of which continues to emerge (e.g., fMRI, diffusion MRI, MR spectroscopy, quantitative T1-weighted/T2 mapping, arterial spin labeling).…”

“…Multiple methods for addressing motion artifacts post-scan exist, but they inevitably limit both data and sample size, and thus degrees of freedom (Yan et al 2013; Bright, Tench, and Murphy 2017; Ciric et al 2017; Satterthwaite et al 2019; Eklund et al 2020). As a result, the prevailing wisdom remains - the best way to handle motion is to prevent it (Ai et al 2020). In this regard, efforts to minimize motion during MRI scanning such as passive movie viewing (Vanderwal et al 2015), real-time motion monitoring and/or feedback (Dosenbach et al 2017; Greene et al 2018; Krause et al 2019), prospective motion correction (Ai et al 2020), and head stabilizers (Power et al 2019) have been reported to be effective.…”