Associations between Maternal Risk Factors and Intrinsic Placental and Fetal Brain Functional Properties in Congenital Heart Disease

The relationship between maternal risk factors (MRFs) (particularly pre-gravid obesity, diabetes, and hypertension) and congenital heart disease (CHD) to placental and fetal brain outcomes is poorly understood. Here, we tested the hypothesis that MRF and CHD would be associated with reduced intrinsic placental and fetal brain function using a novel non-invasive technique. Pregnant participants with and without MRF and fetal CHD were prospectively recruited and underwent feto-placental MRI. Using intrinsic properties of blood oxygen level dependent imaging (BOLD) we quantified spatiotemporal variance of placenta and fetal brain. MRFs and CHD were correlated with functional characteristics of the placenta and fetal brain. Co-morbid MRF (hypertension, diabetes, and obesity) reduced spatiotemporal functional variance of placenta and fetal brain (p < 0.05). CHD predicted reduced fetal brain temporal variance compared to non-CHD (p < 0.05). The presence of both MRF and CHD was associated with reduced intrinsic pBOLD temporal variance (p = 0.047). There were no significant interactions of MRFs and CHD status on either temporal or spatial variance of intrinsic brain BOLD. MRF and CHD reduced functional characteristic of placenta and brain in fetuses. MRF modification and management during pregnancy may have the potential to not only provide additional risk stratification but may also improve neurodevelopmental outcomes.     

Bridging the cognitive-cellular neuroscience gap empirically: a study combining physiology,modelling and fMRI

In this article, we present a mixed qualitative and quantitative approach for evaluation of information technology (IT) security investments. For this purpose, we model security scenarios by using defense trees, an extension of attack trees with countermeasures and we use economic quantitative indexes for computing the defender's return on security investment and the attacker's return on attack. We show how our approach can be used to evaluate economic profitability of countermeasures and their deterrent effect on attackers, thus providing decision makers with a useful tool for performing better evaluation of IT security investments during the risk management process.     

Simultaneous correction of ghost and geometric distortion artifactsin EPI using a multiecho reference scan

A computationally efficient technique is described for the simultaneous removal of ghosting and geometrical distortion artifacts in echo-planar imaging (EPI) utilizing a multiecho, gradient-echo reference scan. Nyquist ghosts occur in EPI reconstructions because odd and even lines of k-space are acquired with opposite polarity, and experimental imperfections such as gradient eddy currents, imperfect pulse sequence timing, B0 field inhomogeneity, susceptibility, and chemical shift result in the even and odd lines of k-space being offset by different amounts relative to the true center of the acquisition window. Geometrical distortion occurs due to the limited bandwidth of the EPI images in the phase-encode direction. This distortion can be problematic when attempting to overlay an activation map from a functional magnetic resonance imaging experiment generated from EPI data on a high-resolution anatomical image. The method described here corrects for geometrical distortion related to B0 inhomogeneity, gradient eddy currents, radio-frequency pulse frequency offset, and chemical shift effect. The algorithm for removing ghost artifacts utilizes phase information in two dimensions and is, thus, more robust than conventional one-dimensional methods. An additional reference scan is required which takes approximately 2 min for a matrix size of 64 X 64 and a repetition time of 2 s. Results from a water phantom and a human brain at 3 T demonstrate the effectiveness of the method for removing ghosts and geometric distortion artifacts.