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

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.

Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

“…Across diagnosis groups, children with more severe social deficits, more inattentive symptoms, more hyperactive/impulsive symptoms, or poorer motor control were more likely to have unusable rs-fMRI data and be excluded, while older children or children with higher intellectual ability were less likely to be excluded for both levels of motion QC. Similarly, Simhal et al (2021) found that children with ASD and children with ADHD who failed a mock MRI training protocol were younger, had lower verbal and non-verbal intelligence scores, and more severe ADOS scores than children with ASD and children with ADHD who passed the training protocol. These findings suggest that the mechanisms driving missingess in rs-fMRI studies may be related to scientifically relevant participant characteristics.…”

“…Scanning these underrepresented populations requires thoughtful experimental accommodations. Some approaches for improving the likelihood of collecting usable data from pediatric participants focus on scan preparation: having a caregiver model scan procedures, practicing in an MRI simulator ( Horien et al, 2020 ; Nordahl et al, 2016 ; Simhal et al, 2021 ), or playing a virtual reality-based MRI game ( Pua et al, 2020 ; Stunden et al, 2021 ). Others focus on modifications during the scan: passive movie-viewing to reduce boredom ( Vanderwal et al, 2019 ), providing real-time feedback to participants using framewise integrated real-time MRI monitoring (FIRMM) software ( Dosenbach et al, 2017 ; Greene et al, 2018 ), or using personalized incentive systems to reward compliance with MRI instructions ( Pua et al, 2020 ).…”

Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

“…Scanning these underrepresented populations requires thoughtful experimental accommodations. Some approaches for improving the likelihood of collecting usable data from pediatric participants focus on scan preparation: having a caregiver model scan procedures, practicing in an MRI simulator (Nordahl et al, 2016; Horien et al, 2020; Simhal et al, 2021), or playing a virtual reality-based MRI game (Stunden et al, 2021; Pua et al, 2020). Others focus on modifications during the scan: passive movie-viewing to reduce boredom (Vanderwal et al, 2019), providing real-time feedback to participants using framewise integrated real-time MRI monitoring (FIRMM) software (Dosenbach et al, 2017; Greene et al, 2018), or using personalized incentive systems to reward compliance with MRI instructions (Pua et al, 2020).…”

“…For instance, extensive MRI simulator practice has been used to scan small samples of autistic children with intellectual disabilities (Nordahl et al, 2016), but this places additional burdens on families by requiring multiple visits. In addition, some studies with autistic children have observed that head motion, while reduced after extensive training, is still associated with symptom severity (Simhal et al, 2021; Gabrielsen et al, 2018). Virtual reality-based games played at home may be as effective as MRI simulator training for typically developing children, (Stunden et al, 2021); however, it remains unclear if children with neurodevelopmental disorders would respond similarly.…”

“…Scanning these underrepresented populations requires thoughtful experimental accommodations. Some approaches for improving the likelihood of collecting usable data from pediatric participants focus on scan preparation: having a caregiver model scan procedures, practicing in an MRI simulator (Nordahl et al, 2016;Horien et al, 2020;Simhal et al, 2021), or playing a virtual reality-based MRI game (Stunden et al, 2021;Pua et al, 2020).…”