Estimating the apparent transverse relaxation time (R2*) from images with different contrasts (ESTATICS) reduces motion artifacts

Relaxation rates provide important information about tissue microstructure. Multi-parameter mapping (MPM) estimates multiple relaxation parameters from multi-echo FLASH acquisitions with different basic contrasts, i.e., proton density (PD), T1 or magnetization transfer (MT) weighting. Motion can particularly affect maps of the apparent transverse relaxation rate R2*, which are derived from the signal of PD-weighted images acquired at different echo times. To address the motion artifacts, we introduce ESTATICS, which robustly estimates R2* from images even when acquired with different basic contrasts. ESTATICS extends the fitted signal model to account for inherent contrast differences in the PDw, T1w and MTw images. The fit was implemented as a conventional ordinary least squares optimization and as a robust fit with a small or large confidence interval. These three different implementations of ESTATICS were tested on data affected by severe motion artifacts and data with no prominent motion artifacts as determined by visual assessment or fast optical motion tracking. ESTATICS improved the quality of the R2* maps and reduced the coefficient of variation for both types of data—with average reductions of 30% when severe motion artifacts were present. ESTATICS can be applied to any protocol comprised of multiple 2D/3D multi-echo FLASH acquisitions as used in the general research and clinical setting

Pathobiology of human intracranial saccular aneurysms

Intracranial saccular aneurysms develop in the course of life in a few percent of the total population. Usually they grow slowly, remain unnoticed, but their rupture induces subarachnoid bleeding with fatal or devastating consequences. Several theories have been constructed to explain the pathomechanism of aneurysm development and rupture. Here these theories will be reviewed. The very complicated blood flow pattern in arteries at the human cerebral base, instability of collateral circulation as well as blood pressure changes can disturb normal, laminar blood flow at bifurcations. With endothelial damage, integrity of basal lamina and internal elastic lamina will also be affected. Evagination of the thin wall occurs with increasing stresses on medial elements. Any pathological factor affecting molecular structures joining connective tissue components with each other, or with the cellular structures, will promote the evagination process. With further enlargement of the sack, increasing mechanical forces make the presence of smooth muscle cells impossible in the wall. When this happens, the ability to rearrange, reorientate connective tissue fibers with the aid of active forces will be lost. Passive rearrangement of fiber structure governed by distending forces, thinning of the wall will be the result, unavoidably leading to the fatal outcome. We can conclude that current hypotheses of human intracranial saccular aneurysm development are not necessarily contradictory. Probably, they describe different factors promoting separate phases in the aneurysm development.Biomedical Reviews 2000; 11: 53-61

Follow the heart or the head? The interactive influence model of emotion and cognition

The experience of emotion has a powerful influence on daily-life decision making. Following Plato’s description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in the head) reins in our impulses (from the heart) and overrides our snap judgments. However, from Darwin’s evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. In this review, we provide a new model, called The interactive influence model of emotion & cognition, to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making