3D Quantitative-Amplified Magnetic Resonance Imaging (3D q-aMRI).

Amplified MRI (aMRI) is a promising new technique that can visualize pulsatile brain tissue motion by amplifying sub-voxel motion in cine MRI data, but it lacks the ability to quantify the sub-voxel motion field in physical units. Here, we introduce a novel post-processing algorithm called 3D quantitative amplified MRI (3D q-aMRI). This algorithm enables the visualization and quantification of pulsatile brain motion.

Intracranial aneurysm wall displacement depicted by amplified Flow predicts growth.

Background: Abnormal intracranial aneurysm (IA) wall motion has been associated with IA growth and rupture. Recently, a new image processing algorithm called amplified Flow (aFlow) has been used to successfully track IA wall motion by combining the amplification of cine and four-dimensional (4D) Flow MRI. We sought to apply aFlow to assess wall motion as a potential marker of IA growth in a paired-wise analysis of patients with growing versus stable aneurysms.

Myelination dictates axonal viscoelasticity.

During development, dramatic changes in myelination, growth of neural networks and changes in grey-to-white matter ratio build up the astonishingly plastic brain of a child. The progressive increase in myelination insulates the nervous system, which, in turn, modifies the mechanical microenvironment of the brain spatiotemporally. A growing body of evidence demonstrates the role of mechanical forces in growth, differentiation, maturation and electrical properties of neurons.

Predictive Helmet Optimization Framework Based on Reduced-Order Modeling of the Brain Dynamics.

Sports-related traumatic brain injuries (TBIs) are among the leading causes of head injuries in the world. Use of helmets is the main protective measure against this epidemic. The design criteria for the majority of the helmets often only consider the kinematics of the head.