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Neural Stem Cells and Oligodendrocyte Progenitors in the Central Nervous System
Published in Richard K. Burt, Alberto M. Marmont, Stem Cell Therapy for Autoimmune Disease, 2019
Jennifer A. Jackson, Diana L. Clarke
When glioblast formation ceases shortly after birth, the germinal VZ disappears throughout the neuroaxis and many of the remaining neuroepithelial cells become ependymal cells. The ependymal cells persist throughout adulthood lining the luminal surface of the ventricular system of the brain and the central canal of the spinal cord. These cells possess multiple cilia on their apical surface that effectively move the cerebral spinal fluid throughout these regions. Similarly, the SVZ, decreases in size and persists immediately adjacent to the ependymal cell layer throughout most of the ventricular regions of the brain. However, a SVZ region is not present in the developing or mature regions of the spinal cord.
Central nervous system
Published in A Stewart Whitley, Jan Dodgeon, Angela Meadows, Jane Cullingworth, Ken Holmes, Marcus Jackson, Graham Hoadley, Randeep Kumar Kulshrestha, Clark’s Procedures in Diagnostic Imaging: A System-Based Approach, 2020
A Stewart Whitley, Jan Dodgeon, Angela Meadows, Jane Cullingworth, Ken Holmes, Marcus Jackson, Graham Hoadley, Randeep Kumar Kulshrestha
The fourth ventricle is a midline structure situated behind the pons and in front of the cerebellum. It is diamond shaped from above and presents two lateral recesses on either side that pass inferiorly and anteriorly. It is continuous inferiorly with the central canal of the spinal cord. The fourth ventricle communicates with the subarachnoid space via three foramen, one central, one in the roof, known as foramen of Magendie, and one in the roof of each of the lateral recesses, known as foramen of Luschka. The ventricular system is lined with ciliated epithelium, termed ependyma.
Artificial Intelligence in Medical Imaging
Published in P. Kaliraj, T. Devi, Artificial Intelligence Theory, Models, and Applications, 2021
The performance of a DL approach called the SMORE algorithm was demonstrated to improve the visualization of brain white matter lesions, to improve the visualization of scarring in cardiac left ventricular remodeling after myocardial infarction, on multi-view images of the tongue, and to improve performance in parcellation of the brain ventricular system.
Leung-Malik Features and Adaboost Perform Classification of Alzheimer’s Disease Stages
Published in IETE Journal of Research, 2022
Shaik Basheera, M. Satya Sai Ram
Alzheimer’s disease is now the sixth largest cause of mortality in the United States, according to the most recent health survey. The most common kind of dementia that is associated with ageing is Alzheimer’s disease (AD). The first indication of Alzheimer’s disease is memory loss, which may disrupt a person’s routine. The hippocampus becomes smaller as Alzheimer’s disease progresses, the ventricular system enlarges and produces more cerebral spinal fluid (CSF), the volume of white matter (WM) in the brain decreases, and the volume of grey matter (GM) in the brain reduces. The Apolipoprotein e4 gene in the family and the individual’s own genetic make-up have a role in this (APOE4). AD is a progressive, fatal neurodegenerative disease characterized by the progressive death of brain cells and the loss of their connections to other neurons. The most important step is to get a diagnosis of Alzheimer’s disease at an early stage. The medical history of the patient, a neurological examination, a physical examination, and an assessment of the person’s memory and thinking using a unique questionnaire that was particularly devised by the physicians all contribute to the process of diagnosing Alzheimer’s disease in a patient. In addition to that, they use a rating for dementia and the Mini-Mental State Examination (MMSE). The National Institute on Aging and the Alzheimer’s Association were the first organizations to define clinical criteria for the diagnosis of Alzheimer’s disease. In addition to the clinical methods described above, a variety of imaging modalities are used to arrive at a diagnosis of Alzheimer’s disease stage.
A computational study of the EN 1078 impact test for bicycle helmets using a realistic subject-specific finite element head model
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2018
Michael Sandberg, Kwong Ming Tse, Long Bin Tan, Heow Pueh Lee
Geometrical information of the human skull and brain were obtained from high resolution axial computed tomography and magnetic resonance imaging images of a 51-year-old Caucasian male subject respectively. These medical images were imported into Mimics v13.0-v14.0 (Materialise, Leuven, Belgium) for the segmentation and reconstruction of the FE human head model, which comprises the skeletal skull, nasal septal cartilage, nasal lateral cartilage, with the overlying soft tissue, the cerebrospinal fluid (CSF), the white and grey matters of cerebrum, cerebellum, the ventricular system, the midbrain, the brainstem as well as the air-containing sinuses. Various components of the head model can be seen in Figure 1. All the skeletal tissues such as cartilages and cervical vertebrae were modelled as linear elastic, isotropic materials while the brain tissues were assumed to be linear viscoelastic. The material properties of the various components of the FE head model can be found in Table 1 and Tse et al. (2014). It should also be noted that the FE head model was validated against the ICP and relative displacement data of three cadaveric experiments (Nahum et al. 1977; Trosseille et al., 1992; Hardy, et al., 2001). More details on the development and validation of the FE head model can be found in Tse et al. (2014, 2015).
Influence of the corpus callosum anatomy on its mechanical behavior during a lateral impact. A finite element study
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2020
P.-M. François, B. Sandoz, P. Decq, S. Laporte
A parametric modelling of the head and its main components (cranial cavity, brain, brain stem, CC, FC, tentorium cerebelli, ventricular system, main sinus and bridging veins) has been developed, based on a previously method proposed at IBHGC (Laville et al. 2009). The global mesh is based on 162 geometrical primitives (383 parameters) and the coordinates of 12 anatomical landmarks. Scalp, skull, FC and tentorium cerebelli were modelled using quad shell elements (ca. 2,700), whole brain volume, blood in the main sinus and the cerebrospinal fluid in the ventricular system using tetra elements (ca. 61,000). Spring elements were used to model 11 pairs of bridging veins (Figure 1).