We propose a Bayesian approach to incorporate anatomical information in the clustering of fiber trajectories. An expectation-maximization (EM) algorithm is used to cluster the trajectories, in which an atlas serves as the prior on the labels. The atlas guides the clustering algorithm and makes the resulting bundles anatomically meaningful. In addition, it provides the seed points for the tractography and initial settings of the EM algorithm. The proposed approach provides a robust and automated tool for tract-oriented analysis both in a single subject and over a population.
Regional investigations of newborn MRI are important to understand the appearance and consequences of early brain injury. Previously, regionalization in neonates has been achieved with a Talairach parcellation, using internal landmarks of the brain. Non-synostotic dolichocephaly defines a bi-temporal narrowing of the preterm infant's head caused by pressure on the immature skull. The impact of dolichocephaly on brain shape and regional brain shift, which may compromise the validity of the parcellation scheme, has not yet been investigated.
In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age.
Magnetic resonance imaging (MRI) contrast agents are utilized adjunctively to enhance the contrast between normal and abnormal structures on MRI scans. Along with the rapid evolution of the field has come a new appreciation for the medicinal chemistry of this unique class of metallopharmaceuticals. The efficacy of MRI agents is a complex function of chemical, biophysical, and pharmacological properties, which must be married in a package of exquisite safety.
BACKGROUND AND PURPOSE: Meta-analyses of extant genome-wide data illustrate the need to focus on subtypes of ischemic stroke for gene discovery. The National Institute of Neurological Disorders and Stroke SiGN (Stroke Genetics Network) contributes substantially to meta-analyses that focus on specific subtypes of stroke.
A 78-year-old woman suffered a stroke inside a magnetic resonance scanner while being imaged because of a brief transient ischemic attack 2 hours earlier. Diffusion-weighted images obtained 11 minutes after stroke showed tissue injury not found on initial images. The data show early, abrupt diffusion changes in hypoperfused tissue, adding to our understanding of the progression of microstructural abnormalities in the hyperacute phase of stroke.
BACKGROUND AND PURPOSE: Perfusion-weighted imaging can predict infarct growth in acute stroke and potentially be used to select patients with tissue at risk for reperfusion therapies. However, the lack of consensus and evidence on how to best create PWI maps that reflect tissue at risk challenges comparisons of results and acute decision-making in trials.
INTRODUCTION: The increased risk of cerebro- and cardiovascular disease in migraineurs may be the consequence of a systemic condition affecting whole body vasculature. At cerebrovascular level, this may be reflected by interictal global or regional cerebral perfusion abnormalities. Whether focal perfusion changes occur during interictal migraine has not been convincingly demonstrated.
