3D Visualization of Brainstem Anatomy in Relation to Lateral Medullary (Wallenberg) Syndrome Publique Deposited
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MLA citation style. 1192. https://mushare.marian.edu/concern/generic_works/087bbccd-e906-473d-b595-e93a55a6c69e?locale=fr 3d Visualization of Brainstem Anatomy In Relation to Lateral Medullary (wallenberg) Syndrome.
APA citation style(1192). 3D Visualization of Brainstem Anatomy in Relation to Lateral Medullary (Wallenberg) Syndrome. https://mushare.marian.edu/concern/generic_works/087bbccd-e906-473d-b595-e93a55a6c69e?locale=fr
Chicago citation style3d Visualization of Brainstem Anatomy In Relation to Lateral Medullary (wallenberg) Syndrome. 1192. https://mushare.marian.edu/concern/generic_works/087bbccd-e906-473d-b595-e93a55a6c69e?locale=fr
Note: These citations are programmatically generated and may be incomplete.
Context: The purpose of this project was to design a 3-dimensional method for visualizing structures within the brainstem with special attention to those involved in Lateral Medullary (Wallenberg) Syndrome. Wallenberg syndrome is a neurologic disorder involving an infarct in blood supply of the Posterior Inferior Cerebellar Artery. Around 60,000 new cases of Wallenberg syndrome occur each year in the U.S. resulting in a multitude of symptoms and often permanent impairment. Objective: The objective of this project was to observe the brainstem including the lateral medulla in its connection to Wallenberg syndrome. A secondary objective was to provide a resource to medical students as they learn the structure and function of the human brainstem. Design: This project was created using Amira software to extract a 3D model of the brainstem from a freely available CT data-set of a randomized patient. This model was used to create videos demonstrating key structural elements affected in Wallenberg Syndrome and made into a YouTube video available for public use. Setting: The scan data selected for this project was chosen based solely on image quality in order to provide the amount of resolution needed to extract the targeted structures. Methods: Amira is an analytical tool used to highlight anatomical structures in CT (and other imaging) scans within desired tissue parameters and interpolating the selections together to create a 3D structure. Results: The final structure extrapolated from Amira was a completed brainstem with cranial nerve nuclei, sensory and motor tracts, and other important structures impacted by Wallenberg syndrome. We believe these data will be helpful in visualizing other brainstem infarcts and injuries as well as a teaching tool for students in the medical field. Conclusions: Future expansions of this study will include extracting additional structures taken from the CT data as well as descriptions of other normal and abnormal anatomical conditions.