"In vivo" imaging of atherosclerosis

Atherosclerosis is a systemic and multifocal disease, which starts early in life, and that usually takes decades before overt disease eventually appears as a consequence of progressive obstruction or abrupt thrombotic occlusion. This silent course makes necessary to develop predictors of disease long before symptomatic lesions develop. Besides several classical risk factors and new emerging humoral risk predictors, imaging may constitute a formidable diagnostic and prognostic tool in order to identify presence, extension, progression (or regression) of disease as well as vulnerability of atherosclerotic lesions. This review summarizes the rapidly growing clinical and research field in imaging atherosclerosis from different perspectives opening important opportunities for timely detection and treatment of atherosclerosis.

A multivariate approach for processing magnetization effects in triggered event-related functional magnetic resonance imaging time series

Triggered event-related functional magnetic resonance imaging requires sparse intervals of temporally resolved functional data acquisitions, whose initiation corresponds to the occurrence of an event, typically an epileptic spike in the electroencephalographic trace. However, conventional fMRI time series are greatly affected by non-steady-state magnetization effects, which obscure initial blood oxygen level-dependent (BOLD) signals. Here, conventional echo-planar imaging and a post-processing solution based on principal component analysis were employed to remove the dominant eigenimages of the time series, to filter out the global signal changes induced by magnetization decay and to recover BOLD signals starting with the first functional volume. This approach was compared with a physical solution using radiofrequency preparation, which nullifies magnetization effects. As an application of the method, the detectability of the initial transient BOLD response in the auditory cortex, which is elicited by the onset of acoustic scanner noise, was used to demonstrate that post-processing-based removal of magnetization effects allows to detect brain activity patterns identical with those obtained using the radiofrequency preparation. Using the auditory responses as an ideal experimental model of triggered brain activity, our results suggest that reducing the initial magnetization effects by removing a few principal components from fMRI data may be potentially useful in the analysis of triggered event-related echo-planar time series. The implications of this study are discussed with special caution to remaining technical limitations and the additional neurophysiological issues of the triggered acquisition.