PURPOSE: Premature infants are at increased risk of impaired visual performance related to both cortical and subcortical pathways for oculomotor control. The hypothesis for the current study was that preterm infants with impaired saccades, smooth pursuit, and binocular eye alignment at age 2 years would have smaller occipital brain volumes at term equivalent, as measured by volumetric magnetic resonance (MR) techniques, than would preterm infants without such abnormalities. METHODS: Study participants consisted of 68 infants from a representative regional cohort of 100 preterm infants born between 23 and 33 weeks’ gestation. At term equivalent, all infants underwent MR imaging, and the images were coregistered, tissue segmented into five cerebral tissue subtypes, and further subdivided into eight regions for each hemisphere. At 2 years corrected, all infants completed a comprehensive orthoptic evaluation performed by a single examiner.

A mathematical model was applied to new lesion formation in multiple sclerosis, as apparent on frequent T2-weighted MRI. The pathophysiologically motivated two-process model comprises two opposing nonlinear self-limiting processes, intended to represent degenerative and reparatory processes, respectively, investigating T2 activity from a dynamic/temporal rather than a spatial/static perspective. Parametric maps were obtained from the model to characterize the MRI dynamics of lesion development, answering the questions of how long new T2 lesion activity persists, how much residual damage/hyperintensity remains and how the T2 dynamics compare to those of contrast-enhancing MRI indicating active inflammation. 997 MRI examinations were analyzed, acquired weekly to monthly from 45 patients over a 1-year period. The model was applied to all pixels within 332 new lesions, capturing the time profiles with excellent fidelity (r = 0.89 +/- 0.03 average correlation between model and image data). From this modeling perspective, the observed dynamics in new T2 lesions are in agreement with two opposing processes of longitudinal intensity change, such as inflammation and degeneration versus resorbtion and repair. On average, about one third of a new lesion consisted of transient signal change with little or no residual hyperintensity and activity of 10 weeks or less. Global lesion burden as MRI surrogate of disease activity may therefore be confounded by large amounts of transient hyperintensity. T2 activity also persisted significantly beyond the period of contrast enhancement, thereby defining MRI sensitivity toward a subacute phase of lesion development beyond blood-brain barrier patency. Concentric patterns of dynamic properties within a lesion were observed, consistent with concentric histological appearance of resulting MS plaques.

BACKGROUND/PURPOSE: Despite its potential for visualizing white matter fiber tracts in vivo, diffusion tensor tractography has found only limited applications in clinical research in which specific anatomic connections between distant regions need to be evaluated. We introduce a robust method for fiber clustering that guides the separation of anatomically distinct fiber tracts and enables further estimation of anatomic connectivity between distant brain regions. METHODS: Line scanning diffusion tensor images (LSDTI) were acquired on a 1.5T magnet. Regions of interest for several anatomically distinct fiber tracts were manually drawn; then, white matter tractography was performed by using the Runge-Kutta method to interpolate paths (fiber traces) following the major directions of diffusion, in which traces were seeded only within the defined regions of interest. Next, a fully automatic procedure was applied to fiber traces, grouping them according to a pairwise similarity function that takes into account the shapes of the fibers and their spatial locations. RESULTS: We demonstrated the ability of the clustering algorithm to separate several fiber tracts which are otherwise difficult to define (left and right fornix, uncinate fasciculus and inferior occipitofrontal fasciculus, and corpus callosum fibers). CONCLUSION: This method successfully delineates fiber tracts that can be further analyzed for clinical research purposes. Hypotheses regarding specific fiber connections and their abnormalities in various neuropsychiatric disorders can now be tested.

White matter fiber bundles in the human brain can be located by tracing the local water diffusion in diffusion weighted magnetic resonance imaging (MRI) images. In this paper, a novel Bayesian modeling approach for white matter tractography is presented. The uncertainty associated with estimated white matter fiber paths is investigated, and a method for calculating the probability of a connection between two areas in the brain is introduced. The main merits of the presented methodology are its simple implementation and its ability to handle noise in a theoretically justified way. Theory for estimating global connectivity is also presented, as well as a theorem that facilitates the estimation of the parameters in a constrained tensor model of the local water diffusion profile.

We propose a simple method for reconstructing vascular trees from 3D images. Our algorithm extracts persistent maxima of the intensity on all axis-aligned 2D slices of the input image. The maxima concentrate along 1D intensity ridges, in particular along blood vessels. We build a forest connecting the persistent maxima with short edges. The forest tends to approximate the blood vessels present in the image, but also contains numerous spurious features and often fails to connect segments belonging to one vessel in low contrast areas. We improve the forest by applying simple geometric filters that trim short branches, fill gaps in blood vessels and remove spurious branches from the vascular tree to be extracted. Experiments show that our technique can be applied to extract coronary trees from heart CT scans.