Minimizing noise in pediatric task-based functional MRI; Adolescents with developmental disabilities and typical development

Abstract

Functional Magnetic Resonance Imaging (fMRI) represents a powerful tool with which to examine brain functioning and development in typically developing pediatric groups as well as children and adolescents with clinical disorders. However, fMRI data can be highly susceptible to misinterpretation due to the effects of excessive levels of noise, often related to head motion. Imaging children, especially with developmental disorders, requires extra considerations related to hyperactivity, anxiety and the ability to perform and maintain attention to the fMRI paradigm. We discuss a number of methods that can be employed to minimize noise, in particular movement-related noise. To this end we focus on strategies prior to, during and following the data acquisition phase employed primarily within our own laboratory. We discuss the impact of factors such as experimental design, screening of potential participants and pre-scan training on head motion in our adolescents with developmental disorders and typical development. We make some suggestions that may minimize noise during data acquisition itself and finally we briefly discuss some current processing techniques that may help to identify and remove noise in the data. Many advances have been made in the field of pediatric imaging, particularly with regard to research involving children with developmental disorders. Mindfulness of issues such as those discussed here will ensure continued progress and greater consistency across studies.

Brain lateralization of phonological awareness varies by maternal education

“…In the case of consecutive outlier volumes, the outlier volumes are replaced with a linear interpolation from the nearest good images, with the relative weighting of the two good volumes adjusted to account for distance between the non‐outlier volume and the repaired volume. To meet acceptable fMRI data quality and be included in this study, participants had no more than 10% of the volumes from each run and no more than eight consecutive volumes were interpolated in this way (Fassbender, Mukherjee, & Schweitzer, ). Interpolated volumes were then partially deweighted when first‐level models were calculated on the repaired images (Mazaika, Hoeft, Glover, & Reiss, ).…”

Neurocognitive Development of the Resolution of Selective Visuo-Spatial Attention: Functional MRI Evidence From Object Tracking

“…To reduce residual errors after realignment, ArtRepair toolbox for high motion samples (Stanford Psychiatric Neuroimaging Laboratory 2 ) was applied to the EPI data sets that had been prepared by a first step of spatial smoothing (4 mm FWHM). This algorithm removes interpolation errors from the image time series on a voxel-by-voxel basis ( Grootoonk et al, 2000 ) and has been recommended in preference to adding motion regressors to the design matrix in high motion samples ( Mazaika, 2009 ; Wilke, 2012 ; Fassbender et al, 2017 ). In a second step, ArtRepair was used to identify noisy volumes on the basis of frame-to-frame movement (threshold: 1.5 mm, calculated using Pythagoras’ theorem based on the 6 translation and rotation parameters derived from SPM’s image realignment process; Mazaika, 2009 ; Wilke, 2012 , 2014 ; Power et al, 2015 ) and signal fluctuations, which were then corrected via interpolation between the nearest non-repaired scans (“scrubbing”; Power et al, 2012 , 2015 ; Siegel et al, 2014 ).…”

Clinical application of advanced MR methods in children: points to consider

“…In addition to balancing unwanted parts of the task and to distract the child from the main condition (thus maximizing the difference of activation in the targeted brain regions), it should also keep the child busy and engaged . This is important as active participation of the child will allow for longer scanning sessions . To this effect, a nominal control condition can be used as an additional stimulation condition, which may result in several contrasts being extractable from the acquired data in the sense of a dual‐, or even triple‐use task .…”

“…Making sure the child is lying comfortably is important as discomfort will lead to an increase in motion and, ultimately, to shorter scanning times. During the session, using stabilizing foam paddings is the preferred means to minimize motion as children tend to have a low tolerance towards more “radical” restraint systems like bite bars . It should also be remembered that, for younger children in particular, extra padding may be required to ensure optimal head placement in the center of the coil .…”