Age Related Impacts on Structural Magnetic Resonance Image Quality in Individuals with Avoidant Restrictive Food Intake Disorder (ARFID)

We are currently investigating structural brain alterations in Avoidant/Restrictive Food Intake Disorder (ARFID) using magnetic resonance imaging (MRI). When conducting MRI and other neuroimaging studies, it is critical to assess image quality using quality control (QC) measures to assess suitability of images for use in downstream analyses. Motion artifacts have been shown to occur most frequently in the MRI scans of youth, which is a target demographic in ARFID. Better understanding the impact of age and ARFID diagnosis in relation to MRI image quality can inform study design, recruitment efforts and study visit protocols. In this study, we utilized data collected from a set of multidisciplinary studies on the neurobiology of ARFID that began in 2016 to conduct QC on scan data and to investigate potential impacts of age and ARFID diagnosis on MRI structural image quality, comparing those with ARFID and healthy controls. The study participants included children, adolescents, and adult males and females. The final sample included 155 individuals, ages 9-45 years old, with both ARFID (n =117) and healthy controls (n =38). High resolution MRI scan sequences, including a T1-weighted sequence were acquired on a Siemens 3 Tesla Tim Trio scanner. Visual QC was conducted in 3D Slicer. After QC was completed, age and ARFID diagnosis were evaluated as potential factors in relation to passing or failing scores across both groups. A main effect of age on image quality was observed, while a main effect of ARFID on image quality was not observed. Identifying the age ranges in which motion is most likely to occur during scans helps aid in study protocol development and helps investigators collect reliable data to investigate brain alterations in ARFID and additional psychiatric disorders. Determining whether ARFID diagnosis has an impact on scan quality informs researchers how to best collect data within this clinical population.