ArticleDevelopmental cognitive neuroscience2021
Predicting multiscan MRI outcomes in children with neurodevelopmental conditions following MRI simulator training.
Article in Developmental cognitive neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Practical considerations for dense longitudinal neuroimaging: Ten simple rules for frequent scanning over short time periods.Developmental cognitive neuroscience · 2026Article
- Factors linked to successful brain magnetic resonance imaging scans and data quality in autistic individuals across the functioning spectrum.BJPsych open · 2026Article
- Autism subtypes identified using cross-species functional connectivity analyses.Nature neuroscience · 2026Article
- Connectome-based symptom mapping and in silico related gene expression in children with autism and/or attention-deficit/hyperactivity disorder.Molecular psychiatry · 2026Article
- Differences in Head Motion During Functional Magnetic Resonance Imaging Across Pediatric Neuropsychiatric Disorders.Biological psychiatry global open science · 2025Article
- Biological subtyping of autism via cross-species fMRI.bioRxiv : the preprint server for biology · 2025Article
- Connectome-based symptom mapping andmedRxiv : the preprint server for health sciences · 2024Article
- Changes in MRI head motion across development: typical development and ADHD.Brain imaging and behavior · 2024Article
- Child life specialists predict successful MRI scanning in unsedated children 4 to 12 years old.Pediatric radiology · 2024Article
- Age, Motion, Medical, and Psychiatric Associations With Incidental Findings in Brain MRI.JAMA network open · 2024Article
- Efficacy of MRI data harmonization in the age of machine learning: a multicenter study across 36 datasets.Scientific data · 2024Article
- Factors associated with MRI success in children cooled for neonatal encephalopathy and controls.Pediatric research · 2023Article
- Longitudinal maturation of resting state networks: Relevance to sustained attention and attention deficit/hyperactivity disorder.Cognitive, affective & behavioral neuroscience · 2022Article
- Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?NeuroImage · 2022Article
- Key considerations for child and adolescent MRI data collection.Frontiers in neuroimaging · 2022Article
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Authors and funding
10 authors.
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Abstract
Pediatric brain imaging holds significant promise for understanding neurodevelopment. However, the requirement to remain still inside a noisy, enclosed scanner remains a challenge. Verbal or visual descriptions of the process, and/or practice in MRI simulators are the norm in preparing children. Yet, the factors predictive of successfully obtaining neuroimaging data remain unclear. We examined data from 250 children (6-12 years, 197 males) with autism and/or attention-deficit/hyperactivity disorder. Children completed systematic MRI simulator training aimed to habituate to the scanner environment and minimize head motion. An MRI session comprised multiple structural, resting-state, task and diffusion scans. Of the 201 children passing simulator training and attempting scanning, nearly all (94%) successfully completed the first structural scan in the sequence, and 88% also completed the following functional scan. The number of successful scans decreased as the sequence progressed. Multivariate analyses revealed that age was the strongest predictor of successful scans in the session, with younger children having lower success rates. After age, sensorimotor atypicalities contributed most to prediction. Results provide insights on factors to consider in designing pediatric brain imaging protocols.
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