Journal article
Assessment of image-derived risk factors for natural course of unruptured cerebral aneurysms
Journal of neurosurgery, Vol.124(2), pp.288-295
02/2016
DOI: 10.3171/2015.2.JNS142265
PMID: 26381246
Abstract
The goal of this prospective longitudinal study was to test whether image-derived metrics can differentiate unruptured aneurysms that will become unstable (grow and/or rupture) from those that will remain stable.
One hundred seventy-eight patients harboring 198 unruptured cerebral aneurysms for whom clinical observation and follow-up with imaging surveillance was recommended at 4 clinical centers were prospectively recruited into this study. Imaging data (predominantly CT angiography) at initial presentation was recorded. Computational geometry was used to estimate numerous metrics of aneurysm morphology that described the size and shape of the aneurysm. The nonlinear, finite element method was used to estimate uniform pressure-induced peak wall tension. Computational fluid dynamics was used to estimate blood flow metrics. The median follow-up period was 645 days. Longitudinal outcome data on these aneurysm patients-whether their aneurysms grew or ruptured (the unstable group) or remained unchanged (the stable group)-was documented based on follow-up at 4 years after the beginning of recruitment.
Twenty aneurysms (10.1%) grew, but none ruptured. One hundred forty-nine aneurysms (75.3%) remained stable and 29 (14.6%) were lost to follow-up. None of the metrics-including aneurysm size, nonsphericity index, peak wall tension, and low shear stress area-differentiated the stable from unstable groups with statistical significance.
The findings in this highly selected group do not support the hypothesis that image-derived metrics can predict aneurysm growth in patients who have been selected for observation and imaging surveillance. If aneurysm shape is a significant determinant of invasive versus expectant management, selection bias is a key limitation of this study.
Details
- Title: Subtitle
- Assessment of image-derived risk factors for natural course of unruptured cerebral aneurysms
- Creators
- Manasi Ramachandran - Department of Biomedical Engineering, University of IowaRohini Retarekar - Department of Biomedical Engineering, University of IowaMadhavan L Raghavan - Department of Biomedical Engineering, University of IowaBenjamin Berkowitz - Department of Biomedical Engineering, University of IowaBenjamin Dickerhoff - Department of Biomedical Engineering, University of IowaTatiana Correa - Department of Biomedical Engineering, University of IowaSteve Lin - Department of Biomedical Engineering, University of IowaKevin Johnson - University of IowaDavid Hasan - Department of Neurosurgery, University of Iowa Hospitals and Clinics; andChristopher Ogilvy - Department of Surgery, Division of Neurosurgery, Beth Israel Deaconess Medical Center; andRobert Rosenwasser - Department of Neurosurgery, Jefferson University Hospital, PhiladelphiaJames Torner - Department of Epidemiology, University of Iowa, Iowa City, IowaEinar Bogason - Department of Neurosurgery, Penn State University, Hershey; andChristopher J Stapleton - Department of Neurosurgery, Massachusetts General Hospital, Boston, MassachusettsRobert E Harbaugh - Department of Engineering Science and Mechanics, Pennsylvania State University, State College, Pennsylvania
- Resource Type
- Journal article
- Publication Details
- Journal of neurosurgery, Vol.124(2), pp.288-295
- DOI
- 10.3171/2015.2.JNS142265
- PMID
- 26381246
- NLM abbreviation
- J Neurosurg
- ISSN
- 1933-0693
- eISSN
- 1933-0693
- Publisher
- United States
- Grant note
- R01 HL083475 / NHLBI NIH HHS R01HL083475 / NHLBI NIH HHS
- Language
- English
- Date published
- 02/2016
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Epidemiology; Surgery; Injury Prevention Research Center; Neurosurgery; Otolaryngology
- Record Identifier
- 9983995162002771
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