Diffusion Tensor Imaging Biomarkers to Predict Motor Outcomes in Stroke: A Narrative Review.

Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2-7 days (acute), and >7-90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables.

Brain Connectomics of Visual-Motor Deficits in Children with Developmental Coordination Disorder.

OBJECTIVE: To extend preliminary findings on associated white matter deficits and structural connectivity in children with developmental coordination disorder (DCD). STUDY DESIGN: Diffusion magnetic resonance imaging-based tractography was used to identify abnormal microstructural properties of specific sensorimotor white matter tracts in 21 children with DCD between 8 and 10 years of age and 20 age- and sex-matched typically developing controls. Graph theoretical analyses were applied to evaluate whole brain connectomics. Associations were also calculated between the tractography/connectome results and visual-motor performance, as measured with the Beery-Buktenica Developmental Test of Visual Motor Integration. RESULTS: Significant positive correlations were obtained between visual-motor trace scores and fractional anisotropy (FA) in the retrolenticular limb of the internal capsule within the group with DCD. Moreover, lower FA in sensorimotor tracts and altered structural connectivity were observed for children with DCD. Compared with controls, subjects with DCD showed decreases in clustering coefficient, and global and local efficiency, suggesting weaker structural network segregation and integration. The degree of decreased global efficiency was significantly associated with poor visual-motor tracing outcomes, above and beyond FA reductions. Specifically, nodal efficiency at the cerebellar lobule VI and right parietal superior gyrus were found significant predictors to discriminate between children with DCD and those with typical development. CONCLUSIONS: Specific white matter alterations and network topology features associate with visual-motor deficits and DCD diagnosis indicating the clinical potential of diffusion magnetic resonance imaging-based metrics for diagnosing DCD.