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Airway Morphology of a Rare Pediatric Diffuse Lung Disease - Statistical Shape Analysis of airway trees from patients diagnosed with Neuroendocrine Cell Hyperplasia of Infancy

English, German · Paperback / Softback

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Neuroendocrine Cell Hyperplasia of Infancy (NEHI) is a rare diffuse lung disease, providing diagnostic and prognostic difficulties due to heterogeneous presentations and unknown etiology. Confirmed cases of NEHI show an increased count of neuroendocrine cells in airway walls upon completion of a lung biopsy. These cells are associated with branch morphogenesis during fetal growth, which leads our hypothesis that NEHI symptoms are correlated with changes in infant airway tree structure. Using volumetric computed tomography scans, patient airway trees are edited to establish a skeletonized form. Image registration techniques align both a control and diseased group into a standard coordinate frame. Principle Component Analysis provides information about the greatest axes of variation, leading to a set of parameters that classify NEHI from the control group. We found that the extent of airway tree deformation in these given axes was correlated with airway functionality. These results suggest that statistical shape models of the NEHI lung show promise for alternative disease diagnostics and stratification.

About the author










Marlijne Cook is a graduate of the Department of Bioengineering Master's program at the University of Colorado Denver | Anschutz Medical Campus. Her academic pursuits were in quantitative image analysis techniques, aiming to improve diagnosis and prognosis. Marlijne graduated from the University of New Hampshire in 2009 with a BS in Mathematics.

Product details

Authors Marlijne Cook
Publisher LAP Lambert Academic Publishing
 
Languages English, German
Product format Paperback / Softback
Released 01.01.2015
 
EAN 9783659665219
ISBN 978-3-659-66521-9
No. of pages 100
Dimensions 150 mm x 220 mm x 5 mm
Weight 150 g
Subject Natural sciences, medicine, IT, technology > Mathematics > Analysis

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