Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Space-Varying Coefficient Models for Brain Imaging

The methodological development and the application in this paper originate from diffusion tensor imaging (DTI), a powerful nuclear magnetic resonance technique enabling diagnosis and monitoring of several diseases as well as reconstruction of neural pathways. We reformulate the current analysis framework of separate voxelwise regressions as a 3d space-varying coefficient model (VCM) for the entire set of DTI images recorded on a 3d grid of voxels. Hence by allowing to borrow strength from spatially adjacent voxels, to smooth noisy observations, and to estimate diffusion tensors at any location within the brain, the three-step cascade of standard data processing is overcome simultaneously. We conceptualize two VCM variants based on B-spline basis functions: a full tensor product approach and a sequential approximation, rendering the VCM numerically and computationally feasible even for the huge dimension of the joint model in a realistic setup. A simulation study shows that both approaches outperform the standard method of voxelwise regressions with subsequent regularization. Due to major efficacy, we apply the sequential method to a clinical DTI data set and demonstrate the inherent ability of increasing the rigid grid resolution by evaluating the incorporated basis functions at intermediate points. In conclusion, the suggested fitting methods clearly improve the current state-of-the-art, but ameloriation of local adaptivity remains desirable

Epistemological Foundations for Neuroeconomics

Neuroeconomics is an emerging field crossing neuroscientific data, the use of brain-imaging tools, experimental and behavioral economics, and an attempt at a better understanding of the cognitive assumptions that underlie theoretical predictive economic models. In this paper the authors try two things: 1) To assess the epistemological biases that affect Neuroeconomics as it is currently done. A number of significant experiments are discussed in that perspective. 2) To imagine an original way - apart from what is already being done - to run experiments in brain-imaging that are relevant to the discussion of rationality assumptions at the core of economic theory.Neuroeconomics, Rationality Assumptions, Abduction

Egas Moniz: 90 years (1927-2017) from cerebral angiography

In June 2017 we celebrate the 90th anniversary of the pioneer discovery of cerebral angiography, the seminal imaging technique used for visualizing cerebral blood vessels and vascular alterations as well as other intracranial disorders. Egas Moniz (1874-1955) was the first to describe the use of this revolutionary technique which, until 1975 (when computed tomography, CT, scan was introduced in the clinical practice), was the sole diagnostic tool to provide an imaging of cerebral vessels and therefore alterations due to intracranial pathology. Moniz introduced in the clinical practice this fundamental and important diagnostic tool. The present contribution wishes to pay a tribute to the Portuguese neurosurgeon, who was also a distinguished neurologist and statesman. Despite his tremendous contribution in modern brain imaging, Egas Moniz was awarded the Nobel Prize in Physiology or Medicine in 1949 for prefrontal leucotomy, the neurosurgical intervention nowadays unacceptable, but should rather be remembered for his key contribution to modern brain imaging. KEYWORDS

A comparison of Voxel compression mapping & longitudinal Voxel-Based morphometry

Clinical motivation: Serial brain imaging can reveal patterns of change over time with important clinical implications for neurodegenerative disease [1]. We investigate the performance of four analysis methods, in terms of a comparison of 20 patients with probable AD to 20 age- and sex-matched controls, characterising differences in change from baseline to later scans

Use of Remote Surface Based Tools for Visualizing Integrated Brain Imaging Data

We describe a surface-based approach to 3D visualization of integrated neuroimaging data. Our web-enabled software allows researchers to use these visualization tools over the Internet. We present examples of brain imaging studies where such remote surface-based visualization techniques have proven to be quite effective

Through Skull Fluorescence Imaging of the Brain in a New Near-Infrared Window

To date, brain imaging has largely relied on X-ray computed tomography and magnetic resonance angiography with limited spatial resolution and long scanning times. Fluorescence-based brain imaging in the visible and traditional near-infrared regions (400-900 nm) is an alternative but currently requires craniotomy, cranial windows and skull thinning techniques, and the penetration depth is limited to 1-2 mm due to light scattering. Here, we report through-scalp and through-skull fluorescence imaging of mouse cerebral vasculature without craniotomy utilizing the intrinsic photoluminescence of single-walled carbon nanotubes in the 1.3-1.4 micrometre near-infrared window. Reduced photon scattering in this spectral region allows fluorescence imaging reaching a depth of >2 mm in mouse brain with sub-10 micrometre resolution. An imaging rate of ~5.3 frames/s allows for dynamic recording of blood perfusion in the cerebral vessels with sufficient temporal resolution, providing real-time assessment of blood flow anomaly in a mouse middle cerebral artery occlusion stroke model.Comment: 38 pages, 4 main figures and 11 Supplementary figures. published in Nature Photonics, 201