title: Power calculations for multicenter imaging studies controlled by the false discovery rate.
abstract: Magnetic resonance imaging (MRI) is widely used in brain imaging research (neuroimaging) to explore structural and functional changes across dispersed neural networks visible only via multisubject experiments. Multicenter investigations are an effective way to increase recruitment rates. This article describes image-based power calculations for a two-group, cross-sectional design specified by the mean effect size and its standard error, sample size, false discovery rate (FDR), and size of the network (i.e., proportion of image locations) that truly demonstrates an effect. Minimum sample size (for fixed effect size) and the minimum effect size (for fixed sample size) are calculated by specifying the acceptable power threshold. Within-center variance was estimated in five participating centers by repeat MRI scanning of 12 healthy participants from whom distributions of gray matter were estimated. The effect on outcome measures when varying FDR and the proportion of true positives is presented. Their spatial patterns reflect within-center variance, which is consistent across centers. Sample sizes 3-6 times larger are needed when detecting effects in subcortical regions compared to the neocortex. Hypothesized multicenter studies of patients with first episode psychosis and control participants were simulated with varying proportions of the cohort recruited at each center. There is little penalty to sample size for recruitment at five centers compared to the center with the lowest variance alone. At 80% power 80 participants per group are required to observe differences in gray matter in high variance regions.
authors.affiliation: Department of Psychiatry and Behavioural and Clinical Neurosciences Institute, University of Cambridge, United Kingdom. js369@cam.ac.uk
authors.forename: John
authors.initials: J
authors.lastname: Suckling
authors.forename: Anna
authors.initials: A
authors.lastname: Barnes
authors.forename: Dominic
authors.initials: D
authors.lastname: Job
authors.forename: David
authors.initials: D
authors.lastname: Brenan
authors.forename: Katherine
authors.initials: K
authors.lastname: Lymer
authors.forename: Paola
authors.initials: P
authors.lastname: Dazzan
authors.forename: Tiago Reis
authors.initials: TR
authors.lastname: Marques
authors.forename: Clare
authors.initials: C
authors.lastname: MacKay
authors.forename: Shane
authors.initials: S
authors.lastname: McKie
authors.forename: Steve R
authors.initials: SR
authors.lastname: Williams
authors.forename: Steven C R
authors.initials: SC
authors.lastname: Williams
authors.forename: Stephen
authors.initials: S
authors.lastname: Lawrie
authors.forename: Bill
authors.initials: B
authors.lastname: Deakin
mesh_terms: D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D015233:Models, Statistical; D013223:Statistics as Topic