Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics
| Autor: | Felicitas J. Detmer, Martin Slawski, Fernando Mut, Farid Hamzei-Sichani, Christopher M. Putman, Juan R. Cebral, Carlos Jimenez, Bong Jae Chung |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Adult
Male medicine.medical_specialty Subarachnoid hemorrhage 0206 medical engineering Biomedical Engineering Hemodynamics Health Informatics 02 engineering and technology Aneurysm Ruptured Models Biological Article Aneurysm rupture 03 medical and health sciences Young Adult 0302 clinical medicine Aneurysm Risk Factors Medicine Humans Radiology Nuclear Medicine and imaging cardiovascular diseases Internal validation Aged Probability Retrospective Studies Receiver operating characteristic business.industry Area under the curve Intracranial Aneurysm General Medicine Middle Aged medicine.disease 020601 biomedical engineering Computer Graphics and Computer-Aided Design Regression Computer Science Applications Cross-Sectional Studies ROC Curve Area Under Curve Surgery Female Computer Vision and Pattern Recognition Radiology business 030217 neurology & neurosurgery |
| Popis: | PURPOSE: Unruptured cerebral aneurysms pose a dilemma for physicians who need to weigh the risk of a devastating subarachnoid hemorrhage against the risk of surgery or endovascular treatment and their complications when deciding on a treatment strategy. A prediction model could potentially support such treatment decisions. The aim of this study was to develop and internally validate a model for aneurysm rupture based on hemodynamic and geometric parameters, aneurysm location, and patient gender and age. METHODS: Cross-sectional data from 1,061 patients were used for image-based computational fluid dynamics and shape characterization of 1,631 aneurysms for training an aneurysm rupture probability model using logistic group Lasso regression. The model’s discrimination and calibration were internally validated based on the area under the curve (AUC) of the receiver operating characteristic (ROC) and calibration plots. RESULTS: The final model retained 11 hemodynamic and 12 morphological variables, aneurysm location, as well as patient age and gender. An adverse hemodynamic environment characterized by a higher maximum oscillatory shear index, higher kinetic energy and smaller low shear area as well as a more complex aneurysm shape, male gender and younger age were associated with an increased rupture risk. The corresponding AUC of the model was 0.86 (95% CI [0.85, 0.86], after correction for optimism 0.84). CONCLUSION: The model combining variables from various domains was able to discriminate between ruptured and unruptured aneurysms with an AUC of 86%. Internal validation indicated potential for the application of this model in clinical practice after evaluation with longitudinal data. |
| Databáze: | OpenAIRE |
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