Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics

  • Felicitas J. DetmerEmail author
  • Bong Jae Chung
  • Fernando Mut
  • Martin Slawski
  • Farid Hamzei-Sichani
  • Christopher Putman
  • Carlos Jiménez
  • Juan R. Cebral
Original Article



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.


Cross-sectional data from 1061 patients were used for image-based computational fluid dynamics and shape characterization of 1631 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 and calibration plots.


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).


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.


Cerebral aneurysm Risk factors Hemodynamics Shape Rupture Prediction 



This study was funded by the National Institutes of Health/National Institute of Neurological Disorders and Stroke (NIH-NINDS, Grant #R21NS094780).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. For this type of study, formal consent is not required.

Supplementary material

11548_2018_1837_MOESM1_ESM.pdf (293 kb)
Supplementary material 1 (PDF 293 kb)


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Copyright information

© CARS 2018

Authors and Affiliations

  • Felicitas J. Detmer
    • 1
    Email author
  • Bong Jae Chung
    • 1
  • Fernando Mut
    • 1
  • Martin Slawski
    • 2
  • Farid Hamzei-Sichani
    • 3
  • Christopher Putman
    • 4
  • Carlos Jiménez
    • 5
  • Juan R. Cebral
    • 1
  1. 1.Bioengineering Department, Volgenau School of EngineeringGeorge Mason UniversityFairfaxUSA
  2. 2.Statistics DepartmentGeorge Mason UniversityFairfaxUSA
  3. 3.Department of Neurological SurgeryUniversity of MassachusettsWorcesterUSA
  4. 4.Interventional Neuroradiology UnitInova Fairfax HospitalFalls ChurchUSA
  5. 5.Neurosurgery DepartmentUniversity of AntioquiaMedellínColombia

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