title: Statistical analysis of structural brain connectivity.
abstract: We present a framework for statistical analysis in large cohorts of structural brain connectivity, derived from diffusion weighted MRI. A brain network is defined between subcortical gray matter structures and a cortical parcellation obtained with FreeSurfer. Connectivity is established through minimum cost paths with an anisotropic local cost function and is quantified per connection. The connectivity network potentially encodes important information about brain structure, and can be analyzed using multivariate regression methods. The proposed framework can be used to study the relation between connectivity and e.g. brain function or neurodegenerative disease. As a proof of principle, we perform principal component regression in order to predict age and gender, based on the connectivity networks of 979 middle-aged and elderly subjects, in a 10-fold cross-validation. The results are compared to predictions based on fractional anisotropy and mean diffusivity averaged over the white matter and over the corpus callosum. Additionally, the predictions are performed based on the best predicting connection in the network. Principal component regression outperformed all other prediction models, demonstrating the age and gender information encoded in the connectivity network.
authors.affiliation: Biomedical Imaging Group Rotterdam, Department of Radiology, Erasmus MC, Rotterdam, The Netherlands.
authors.forename: Renske
authors.initials: R
authors.lastname: de Boer
authors.forename: Michiel
authors.initials: M
authors.lastname: Schaap
authors.forename: Fedde
authors.initials: F
authors.lastname: van der Lijn
authors.forename: Henri A
authors.initials: HA
authors.lastname: Vrooman
authors.forename: Marius
authors.initials: M
authors.lastname: de Groot
authors.forename: Meike W
authors.initials: MW
authors.lastname: Vernooij
authors.forename: M Arfan
authors.initials: MA
authors.lastname: Ikram
authors.forename: Evert F S
authors.initials: EF
authors.lastname: van Velsen
authors.forename: Aad
authors.initials: A
authors.lastname: van der Lugt
authors.forename: Monique M B
authors.initials: MM
authors.lastname: Breteler
authors.forename: Wiro J
authors.initials: WJ
authors.lastname: Niessen
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003627:Data Interpretation, Statistical; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009434:Neural Pathways / Q000033:anatomy & histology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity