Date of Degree
2012
Document Type
thesis
Degree Name
MS (Master of Science)
Department
Biomedical Engineering
First Advisor
Madhavan L. Raghavan
Abstract
Cerebral aneurysm rupture is a major cause of death and permanent disability. Rupture rate, however, is low; therefore, a physician must weigh the risk of rupture against treatment risk. In order to help physicians determine the rupture risk of any particular case, studies have previously explored morphology as an indicator for mechanical and hemodynamic characteristics of rupture-prone aneurysms. Morphological characteristics of the aneurysms in these studies are often quantified with morphometric indices, or normalized measures of specific geometric traits. This study introduces several novel morphometric indices. These include tissue stretch ratio, which characterizes the amount of deformation which aneurysm tissue may have undergone; neck-to-vessel ratio, which may have hemodynamic implications and is derived from the ratio of the diameter of the ostium to the diameter of the parent vessel; ellipticity index, which may indicate increased wall tension due to an elliptical shape; and non-sphericity index, which may indicate the presence of stress concentrations due to a non-spherical shape. In order to extrapolate these morphological measures, the aneurysm must first be separated from the parent vasculature. A novel method for aneurysm sac isolation is presented, which uses an approximation of the healthy parent vessel to remove all non-aneurysmal portions of a vascular model. This approach results in a more complete extraction of the aneurysm geometry than is possible using previous standard techniques. The repeatability of the isolation process is analyzed, as well as mesh-independence and the agreement of the resulting aneurysm sac model to a known geometry.
Pages
x, 85
Bibliography
80-83
Copyright
Copyright 2012 Benjamin Berkowitz
Recommended Citation
Berkowitz, Benjamin Micah. "Development and demonstration of an automated method for deriving novel morphometric indices of cerebral aneurysms." thesis, University of Iowa, 2012.
http://ir.uiowa.edu/etd/3565.