Alteration of White Matter Integrity in Dyslexic Children: Case-Control Study / 신경정신의학

OBJECTIVES: To compare the white matter microstructure of dyslexic children with normal children using diffusion tensor imaging. METHODS: Twenty one dyslexic children and 24 normal control children were recruited in the second and third grade of elementary school students. The fractional anisotropy (FA) values of 20 representative white matter tracts were estimated from the diffusion tensor imaging data of each subject using the Johns Hopkins University-white matter tractography atlas to determine the difference in white matter integrity between the dyslexic children and normal children. RESULTS: Compared to the normal control group, the FA values of the left inferior longitudinal fasciculus [F(1,39)=5.908, p<0.05] and temporal part of the right superior longitudinal fasciculus [F(1,39)=7.328, p=0.010] were significantly higher in the dyslexic group and there was no significant difference in the other tracts. CONCLUSION: In dyslexic children, compensatory pathways develop in the left inferior longitudinal fasciculus and in the temporal part of the right superior longitudinal fasciculus.

DTI measures identify mild and moderate TBI cases among patients with complex health problems: A receiver operating characteristic analysis of U.S. veterans.

Standard MRI methods are often inadequate for identifying mild traumatic brain injury (TBI). Advances in diffusion tensor imaging now provide potential biomarkers of TBI among white matter fascicles (tracts). However, it is still unclear which tracts are most pertinent to TBI diagnosis. This study ranked fiber tracts on their ability to discriminate patients with and without TBI. We acquired diffusion tensor imaging data from military veterans admitted to a polytrauma clinic (Overall n = 109; Age: M = 47.2, SD = 11.3; Male: 88%; TBI: 67%). TBI diagnosis was based on self-report and neurological examination. Fiber tractography analysis produced 20 fiber tracts per patient. Each tract yielded four clinically relevant measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity). We applied receiver operating characteristic (ROC) analyses to identify the most diagnostic tract for each measure. The analyses produced an optimal cutpoint for each tract. We then used kappa coefficients to rate the agreement of each cutpoint with the neurologist's diagnosis. The tract with the highest kappa was most diagnostic. As a check on the ROC results, we performed a stepwise logistic regression on each measure using all 20 tracts as predictors. We also bootstrapped the ROC analyses to compute the 95% confidence intervals for sensitivity, specificity, and the highest kappa coefficients. The ROC analyses identified two fiber tracts as most diagnostic of TBI: the left cingulum (LCG) and the left inferior fronto-occipital fasciculus (LIF). Like ROC, logistic regression identified LCG as most predictive for the FA measure but identified the right anterior thalamic tract (RAT) for the MD, RD, and AD measures. These findings are potentially relevant to the development of TBI biomarkers. Our methods also demonstrate how ROC analysis may be used to identify clinically relevant variables in the TBI population.