Ricerc@Sapienza

Background: We investigated intracerebral fiber bundles using a tract-based spatial statistics (TBSS) analysis of diffusion tensor imaging (DTI) data to verify microstructural integrity in patients with episodic (MO) and chronic migraine (CM). Methods: We performed DTI in 19 patients with MO within interictal periods, 18 patients with CM without any history of drug abuse, and 18 healthy controls (HCs) using a 3 T magnetic resonance imaging scanner. We calculated diffusion metrics, including fractional anisotropy (FA), axial diffusion (AD), radial diffusion (RD), and mean diffusion (MD).

Diffusion-weighted magnetic resonance imaging (DW-MRI) tractography is a non-invasive tool to probe neural connections and the structure of the white matter. It has been applied successfully in studies of neurological disorders and normal connectivity. Recent work has revealed that tractography produces a high incidence of false-positive connections, often from “bottleneck” white matter configurations. The rich literature in histological connectivity analysis studies in the macaque monkey enables quantitative evaluation of the performance of tractography algorithms.

One of the greatest challenges in providing early effective treatment in mood disorders is the early differential diagnosis between major depression (MDD) and bipolar disorder (BD). A remarkable need exists to identify reliable biomarkers for these disorders. We integrate structural neuroimaging techniques (i.e. Tract-based Spatial Statistics, TBSS, and Voxel-based morphometry) in a multiple kernel learning procedure in order to define a predictive function of BD against MDD diagnosis in a sample of 148 patients.