Purpose: To investigate the effect of resting-state (RS) functional magnetic resonance (MR) imaging blood oxygen level- dependent (BOLD) signal acquisition duration on stability of computed graph theory metrics of brain network connectivity. Materials and Methods: An institutional ethics committee approved this study, and informed consent was obtained. BOLD signal (7.5 minutes worth) was obtained from 30 subjects and truncated into 30-second time bins that ranged from 1.5 to 7.5 minutes. A binarized adjacency matrix for each subject and acquisition duration was generated at network costs between 0.1 and 0.5, where network cost is defi ned as the ratio of the number of edges (connections) in a network to the maximum possible number of edges. Measures of correlation coeffi cient stability associated with functional connectivity matrices (correlation coeffi cient standard deviation [SD] and correlation threshold) and associated graph theory metrics (small worldness, local effi ciency, and global effi ciency) were computed for each subject at each BOLD signal acquisition duration. Computations were implemented with a 15-node 30-core computer cluster to enable analysis of the approximately 2000 resulting brain networks. Analysis of variance and posthoc analyses were conducted to identify differences between time bins for each measure. Results: Small worldness, local efficiency, and global efficiency stabilized after 2 minutes of BOLD signal acquisition, whereas correlation coeffi cient data from functional connectivity matrices (correlation coeffi cient SD and costassociated threshold) stabilized after 5 minutes of BOLD signal acquisition. Conclusion: Graph theory metrics of brain network connectivity (small worldness, local effi ciency, and global effi ciency) may be accurately computed from as little as 1.5-2.0 minutes of RS functional MR imaging BOLD signal. As such, implementation of these methods in the context of timeconstrained clinical imaging protocols may be feasible and cost-effective.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging