Current research on concussion is primarily focused on injury identification and treatment. Prevention initiatives are, however, important for reducing the incidence of brain injury. This report examines the development and implementation of an interactive electronic teaching program (an e-module) that is designed specifically for concussion education within an adolescent population. This learning tool and the accompanying consolidation rubric demonstrate that significant engagement occurs in addition to the knowledge gained among participants when it is used in a school curriculum setting.
Measurements of water molecule diffusion along fiber tracts in CNS by diffusion tensor imaging (DTI) provides a static map of neural connections between brain centers, but does not capture the electrical activity along axons for these fiber tracts. Here, a modification of the DTI method is presented to enable the mapping of active fibers. It is termed dynamic diffusion tensor imaging (dDTI) and is based on a hypothesized "anisotropy reduction due to axonal excitation" ("AREX"). The potential changes in water mobility accompanying the movement of ions during the propagation of action potentials along axonal tracts are taken into account. Specifically, the proposed model, termed "ionic DTI model", was formulated as follows. First, based on theoretical calculations, we calculated the molecular water flow accompanying the ionic flow perpendicular to the principal axis of fiber tracts produced by electrical conduction along excited myelinated and non-myelinated axons.Based on the changes in molecular water flow we estimated the signal changes as well as the changes in fractional anisotropy of axonal tracts while performing a functional task.The variation of fractional anisotropy in axonal tracts could allow mapping the active fiber tracts during a functional task. Although technological advances are necessary to enable the robust and routine measurement of this electrical activity-dependent movement of water molecules perpendicular to axons, the proposed model of dDTI defines the vectorial parameters that will need to be measured to bring this much needed technique to fruition.
The brain morphometry of 21 children, who were followed from birth and underwent structural brain magnetic resonance imaging at 8-10 years, was studied. This cohort included 11 children with prenatal cocaine exposure (CE) and 10 noncocaine-exposed children (NCE). We compared the CE versus NCE groups using FreeSurfer to automatically segment and quantify the volume of individual brain structures. In addition, we created a pediatric atlas specifically for this population and demonstrate the enhanced accuracy of this approach. We found an overall trend towards smaller brain volumes among CE children. The volume differences were significant for cortical gray matter, the thalamus and the putamen. Here, reductions in thalamic and putaminal volumes showed a robust inverse correlation with exposure levels, thus highlighting effects on dopamine-rich brain regions that form key components of brain circuitry known to play important roles in behavior and attention. Interestingly, head circumferences (HCs) at birth as well as at the time of imaging showed a tendency for smaller size among CE children. HCs at the time of imaging correlated well with the cortical volumes for all subjects. In contrast, HCs at birth were predictive of the cortical volume only for the CE group. A subgroup of these subjects (6 CE, 4 NCE) was also scanned at 13-15 years of age. In subjects who were scanned twice, we found that the trend for smaller structures continued into teenage years. We found that the differences in structural volumes between the CE and NCE groups are largely diminished when the HCs are controlled for or matched by study design. Participants in this study were drawn from a unique longitudinal cohort and, while the small sample size precludes strong conclusions regarding the longitudinal findings reported, the results point to reductions in HCs and in specific brain structures that persist through teenage years in children who were exposed to cocaine in utero.
BACKGROUND: Due to limited SNR the cerebral applications of the intravoxel incoherent motion (IVIM) concept have been sparse. MRI hardware developments have resulted in improved SNR and this may justify a reassessment of IVIM imaging for non-invasive quantification of the cerebral blood volume (CBV) as a first step toward determining the optimal field strength. PURPOSE: To investigate intravoxel incoherent motion imaging for its potential to assess cerebral blood volume (CBV) at three different MRI field strengths. MATERIALS AND METHODS: Four volunteers were scanned twice at 1.5 T, 3 T as well as 7 T. By correcting for field-strength-dependent effects of relaxation, estimates of corrected CBV (cCBV) were obtained in deep gray matter (DGM), frontal gray matter (FGM) and frontal white matter (FWM), using Bayesian analysis. In addition, simulations were performed to facilitate the interpretation of experimental data. RESULTS: In DGM, FGM and FWM we obtained cCBV estimates of 2.2 ml/100 ml, 2.7 ml/100 ml, 1.4 ml/100 ml at 1.5 T; 3.7 ml/100 ml, 5.0 ml/100 ml, 3.2 ml/100 ml at 3 T and 15.5 ml/100 ml, 20.3 ml/100 ml, 7.0 ml/100 ml at 7 T.
BACKGROUND: Blood transfusions are frequently given to patients with septic shock. However, the benefits and harms of different hemoglobin thresholds for transfusion have not been established. METHODS: In this multicenter, parallel-group trial, we randomly assigned patients in the intensive care unit (ICU) who had septic shock and a hemoglobin concentration of 9 g per deciliter or less to receive 1 unit of leukoreduced red cells when the hemoglobin level was 7 g per deciliter or less (lower threshold) or when the level was 9 g per deciliter or less (higher threshold) during the ICU stay. The primary outcome measure was death by 90 days after randomization.
This paper deals with fast and accurate visualization of pushbroom image data from airborne and spaceborne platforms. A pushbroom sensor acquires images in a line-scanning fashion, and this results in scattered input data that need to be resampled onto a uniform grid for geometrically correct visualization. To this end, we model the anisotropic spatial dependence structure caused by the acquisition process. Several methods for scattered data interpolation are then adapted to handle the induced anisotropic metric and compared for the pushbroom image rectification problem. A trick that exploits the semiordered line structure of pushbroom data to improve the computational complexity several orders of magnitude is also presented.
Marijuana is the most commonly used illicit drug in the United States, but little is known about its effects on the human brain, particularly on reward/aversion regions implicated in addiction, such as the nucleus accumbens and amygdala. Animal studies show structural changes in brain regions such as the nucleus accumbens after exposure to Δ9-tetrahydrocannabinol, but less is known about cannabis use and brain morphometry in these regions in humans. We collected high-resolution MRI scans on young adult recreational marijuana users and nonusing controls and conducted three independent analyses of morphometry in these structures: (1) gray matter density using voxel-based morphometry, (2) volume (total brain and regional volumes), and (3) shape (surface morphometry). Gray matter density analyses revealed greater gray matter density in marijuana users than in control participants in the left nucleus accumbens extending to subcallosal cortex, hypothalamus, sublenticular extended amygdala, and left amygdala, even after controlling for age, sex, alcohol use, and cigarette smoking. Trend-level effects were observed for a volume increase in the left nucleus accumbens only. Significant shape differences were detected in the left nucleus accumbens and right amygdala. The left nucleus accumbens showed salient exposure-dependent alterations across all three measures and an altered multimodal relationship across measures in the marijuana group. These data suggest that marijuana exposure, even in young recreational users, is associated with exposure-dependent alterations of the neural matrix of core reward structures and is consistent with animal studies of changes in dendritic arborization.
For accurate estimation of the ensemble average diffusion propagator (EAP), traditional multi-shell diffusion imaging (MSDI) approaches require acquisition of diffusion signals for a range of b-values. However, this makes the acquisition time too long for several types of patients, making it difficult to use in a clinical setting. In this work, we propose a new method for the reconstruction of diffusion signals in the entire q-space from highly undersampled sets of MSDI data, thus reducing the scan time significantly. In particular, to sparsely represent the diffusion signal over multiple q-shells, we propose a novel extension to the framework of spherical ridgelets by accurately modeling the monotonically decreasing radial component of the diffusion signal. Further, we enforce the reconstructed signal to have smooth spatial regularity in the brain, by minimizing the total variation (TV) norm. We combine these requirements into a novel cost function and derive an optimal solution using the Alternating Directions Method of Multipliers (ADMM) algorithm. We use a physical phantom data set with known fiber crossing angle of 45° to determine the optimal number of measurements (gradient directions and b-values) needed for accurate signal recovery. We compare our technique with a state-of-the-art sparse reconstruction method (i.e., the SHORE method of Cheng et al. (2010)) in terms of angular error in estimating the crossing angle, incorrect number of peaks detected, normalized mean squared error in signal recovery as well as error in estimating the return-to-origin probability (RTOP). Finally, we also demonstrate the behavior of the proposed technique on human in vivo data sets. Based on these experiments, we conclude that using the proposed algorithm, at least 60 measurements (spread over three b-value shells) are needed for proper recovery of MSDI data in the entire q-space.
Many studies have observed altered neurofunctional and structural organization in the aging brain. These observations from functional neuroimaging studies show a shift in brain activity from the posterior to the anterior regions with aging (PASA model), as well as a decrease in cortical thickness, which is more pronounced in the frontal lobe followed by the parietal, occipital, and temporal lobes (retrogenesis model). However, very little work has been done using diffusion MRI (dMRI) with respect to examining the structural tissue alterations underlying these neurofunctional changes in the gray matter. Thus, for the first time, we propose to examine gray matter changes using diffusion MRI in the context of aging. In this work, we propose a novel dMRI based measure of gray matter "heterogeneity" that elucidates these functional and structural models (PASA and retrogenesis) of aging from the viewpoint of diffusion MRI. In a cohort of 85 subjects (all males, ages 15-55 years), we show very high correlation between age and "heterogeneity" (a measure of structural layout of tissue in a region-of-interest) in specific brain regions. We examine gray matter alterations by grouping brain regions into anatomical lobes as well as functional zones. Our findings from dMRI data connects the functional and structural domains and confirms the "retrogenesis" hypothesis of gray matter alterations while lending support to the neurofunctional PASA model of aging in addition to showing the preservation of paralimbic areas during healthy aging.
BACKGROUND: The genetic risk factors for susceptibility to chronic obstructive pulmonary disease (COPD) are still largely unknown. Additional genetic variants are likely to be identified by genome-wide association studies in larger cohorts or specific subgroups. We sought to identify risk loci for moderate to severe and severe COPD with data from several cohort studies. METHODS: We combined genome-wide association analysis data from participants in the COPDGene study (non-Hispanic white and African-American ethnic origin) and the ECLIPSE, NETT/NAS, and Norway GenKOLS studies (self-described white ethnic origin). We did analyses comparing control individuals with individuals with moderate to severe COPD and with a subset of individuals with severe COPD. Single nucleotide polymorphisms yielding a p value of less than 5 × 10(-7) in the meta-analysis at loci not previously described were genotyped in individuals from the family-based ICGN study. We combined results in a joint meta-analysis (threshold for significance p
