KEYWORDS: Arteries, Magnetic resonance imaging, Scanning electron microscopy, Image segmentation, Independent component analysis, Image resolution, Hemodynamics, Aneurysms, Simulation of CCA and DLA aggregates, 3D image processing
Background: Hemodynamics is a driving factor behind remodeling of the cerebral vasculature, yet mechanisms of flowinduced remodeling remain incompletely understood. Studies employing serial imaging could help characterize hemodynamic-induced pathologic and physiologic remodeling of cerebral arteries. Methods: This preliminary study was performed us ing 4 mice. In 3, we induced flow-driven vascular remodeling in the Circle of Willis (CoW). This was done by ligation of the left common carotid artery (CCA), and the right external carot id and pterygopalatine arteries, which resulted in an increase of blood flow through the basilar artery and the right internal carotid artery. The remaining mouse was used as a wild-type control. In the 3 experimental mice, we performed 9.4 Tesla Magnetic Resonance Imaging (MRI) over a span of 3 months. 3D images were reconstructed for serial computational evaluation of gross morphological changes . These measurements were verified by the terminal vascular corrosion casting and scanning electron microscope imaging. Results: This study demonstrated the feasibility to distinguish and serially measure pathologic cerebral vascular changes in the mouse CoW, specifically in the anterior vasculature. We showed that these changes were characterized by compensatory arterial dilation and increased tortuosity on the anterior cerebral artery. From scanning electron microscope images, we also found that there was microscopic damage, akin to aneurysmal remodeling, at the right olfactory artery origin. Conclusions: MRI-based serial imaging has the potential to serially characterize gross morphological changes in the CoW in response to flow manipulation. In the future, combining this analysis with computational fluid dynamics simulations will help to define the hemodynamic environments corresponding to these and other pathologic remodeling changes in the mouse CoW.
Neurosurgeons currently base most of their treatment decisions for intracranial aneurysms (IAs) on morphological measurements made manually from 2D angiographic images. These measurements tend to be inaccurate because 2D measurements cannot capture the complex geometry of IAs and because manual measurements are variable depending on the clinician’s experience and opinion. Incorrect morphological measurements may lead to inappropriate treatment strategies. In order to improve the accuracy and consistency of morphological analysis of IAs, we have developed an image-based computational tool, AView. In this study, we quantified the accuracy of computer-assisted adjuncts of AView for aneurysmal morphologic assessment by performing measurement on spheres of known size and anatomical IA models. AView has an average morphological error of 0.56% in size and 2.1% in volume measurement. We also investigate the clinical utility of this tool on a retrospective clinical dataset and compare size and neck diameter measurement between 2D manual and 3D computer-assisted measurement. The average error was 22% and 30% in the manual measurement of size and aneurysm neck diameter, respectively. Inaccuracies due to manual measurements could therefore lead to wrong treatment decisions in 44% and inappropriate treatment strategies in 33% of the IAs. Furthermore, computer-assisted analysis of IAs improves the consistency in measurement among clinicians by 62% in size and 82% in neck diameter measurement. We conclude that AView dramatically improves accuracy for morphological analysis. These results illustrate the necessity of a computer-assisted approach for the morphological analysis of IAs.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.