Surface Metrology of Cerebral Arteries Luminal Surface
Atherosclerotic lesions within carotid and cerebral vessels are likely to influence hemodynamics and manifest into vascular pathologies, including Alzheimers Disease and ischemic stroke. Hemodynamics are influenced by changes in luminal diameter of vessels and wall shear stress derived from turbulence, which directly relates to the surface topography of the lumen. In this study, we performed a quantitative assessment of surface metrology of carotid and cerebral arteries in relation to vessel size and location among individuals. We speculate intracranial vessels will follow suit of extracranial vessels, with increased surface roughness in larger-diameter vessels. Samples of the internal carotid, common carotid, and multiple branches of the Circle of Willis were collected at 18 different sites from 10 human whole body donors. The arterial surface metrology was analyzed using a Sensofar S Neox 3D optical profiler, from which ISO 25718-2 areal roughness parameters, texture direction, motifs analysis, and scale-sensitive fractal analyses were analyzed using SensoMap software. The most significant differences between individuals, though surface roughness appears also greater in the larger vessels. In comparison, the side (left vs. right) is almost immaterial. With further research in this field, the pathophysiology of intracranial atherosclerosis a the role of atherosclerosis in neurodegenerative disorders.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Classification of Carotid Plaque with Jellyfish Sign Through Convolutional and Recurrent Neural Networks Utilizing Plaque Surface Edges
In carotid arteries, plaque can develop as localized elevated lesions. The Jellyfish sign, marked by fluctuating plaque surfaces with blood flow pulsation, is a dynamic characteristic of these plaques that has recently a…
A Two-step Surface-based 3D Deep Learning Pipeline for Segmentation of Intracranial Aneurysms
The exact shape of intracranial aneurysms is critical in medical diagnosis and surgical planning. While voxel-based deep learning frameworks have been proposed for this segmentation task, their performance remains limite…
Deep LearningMedical DiagnosisSegmentationRobots That Generate Planarity Through Geometry
Constraining motion to a flat surface is a fundamental requirement for equipment across science and engineering. Modern precision robotic motion systems, such as gantries, rely on the flatness of components, including gu…
Contrasting results of surface metrology techniques for three-dimensional human fingerprints
Fingerprints, otherwise known as dermatoglyphs, are most commonly thought of in the context of identification, but have myriad other roles in human biology. They are formed by the restricted ability of ridges and furrows…
Multi-Task Deep Learning for Surface Metrology
A reproducible deep learning framework is presented for surface metrology to predict surface texture parameters together with their reported standard uncertainties. Using a multi-instrument dataset spanning tactile and o…