The purpose of this work was to highlight the neurological differences between the MR resting state networks of a group of children with ADHD (pre-treatment) and an age-matched healthy group. Results were obtained using different image analysis techniques. A sample of n = 46 children with ages between 6 and 12 years were included in this study (23 per cohort). Resting state image analysis was performed using ReHo, ALFF and ICA techniques. ReHo and ICA represent connectivity analyses calculated with different mathematical approaches. ALFF represents an indirect measurement of brain activity. The ReHo and ICA analyses suggested differences between the two groups, while the ALFF analysis did not. The ReHo and ALFF analyses presented differences with respect to the results previously reported in the literature. ICA analysis showed that the same resting state networks that appear in healthy volunteers of adult age were obtained for both groups. In contrast, these networks were not identical when comparing the healthy and ADHD groups. These differences affected areas for all the networks except the Right Memory Function network. All techniques employed in this study were used to monitor different cerebral regions which participate in the phenomenological characterization of ADHD patients when compared to healthy controls. Results from our three analyses indicated that the cerebellum and mid-frontal lobe bilaterally for ReHo, the executive function regions in ICA, and the precuneus, cuneus and the clacarine fissure for ALFF, were the “hubs” in which the main inter-group differences were found. These results do not just help to explain the physiology underlying the disorder but open the door to future uses of these methodologies to monitor and evaluate patients with ADHD.

ObjectiveAn obsessive-compulsive disorder (OCD) subtype has been associated with streptococcal infections and is called pediatric autoimmune neuropsychiatric disorders associated with streptococci (PANDAS). The neuroanatomical characterization of subjects with this disorder is crucial for the better understanding of its pathophysiology; also, evaluation of these features as classifiers between patients and controls is relevant to determine potential biomarkers and useful in clinical diagnosis. This was the first multivariate pattern analysis (MVPA) study on an early-onset OCD subtype.MethodsFourteen pediatric patients with PANDAS were paired with 14 healthy subjects and were scanned to obtain structural magnetic resonance images (MRI). We identified neuroanatomical differences between subjects with PANDAS and healthy controls using voxel-based morphometry, diffusion tensor imaging (DTI), and surface analysis. We investigated the usefulness of these neuroanatomical differences to classify patients with PANDAS using MVPA.ResultsThe pattern for the gray and white matter was significantly different between subjects with PANDAS and controls. Alterations emerged in the cortex, subcortex, and cerebellum. There were no significant group differences in DTI measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity) or cortical features (thickness, sulci, volume, curvature, and gyrification). The overall accuracy of 75% was achieved using the gray matter features to classify patients with PANDAS and healthy controls.ConclusionThe results of this integrative study allow a better understanding of the neural substrates in this OCD subtype, suggesting that the anatomical gray matter characteristics could have an immune origin that might be helpful in patient classification.

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Poorly characterized by non-invasive diagnostic imaging techniques, pulmonary hypertension (PHT) is commonly associated with changes in vascular hemodynamics and remodeling of pulmonary artery architecture. These disease phenotypes represent potential biomarkers of interest in clinical environment. In this retrospective clinical study, 33 patients with pulmonary hypertension and seventeen controls were recruited. Architectural remodeling was characterized using 3D-contrast enhanced angiogram via the measurement of pulmonary artery diameters, bifurcation distances, and angles. Hemodynamics were characterized using 4D-flow magnetic resonance imaging (MRI) via wall shear stress, kinetic energy, vorticity, and directional flow dynamics. Parameters were compared using independent samples student’s t-tests. Correlational analysis was performed using Pearson’s correlation. PHT patients demonstrated dilation in the main and right branch of the pulmonary artery (p < 0.05). Furthermore, these patients also exhibited increases in bifurcation distances in the left and right pulmonary arteries (p < 0.05). Wall shear stress, maximum kinetic energy, and energy loss were decreased in the pulmonary artery (p < 0.001). Correlations were observed between peak velocities and right ventricle ejection fraction (r = 0.527, p < 0.05). These findings suggest that pulmonary artery remodeling and hemodynamic changes may possess clinical utility as MRI biomarkers for PHT.