THURSDAY, Jan. 8 (HealthDay News) -- A model of aneurysm rupture derived from measuring hundreds of aneurysms showed good accuracy in identifying the rupture status of another cohort of patients, according to research published in the January issue of the Journal of Neurosurgery.
Charles J. Prestigiacomo, M.D., of the University of Medicine and Dentistry of New Jersey in Newark, and colleagues analyzed computed tomography scans of 217 patients with 279 aneurysms (156 ruptured and 123 unruptured). They measured maximum aneurysm height, width, and neck size in the planes parallel and perpendicular to blood flow. The investigators tested these factors, as well as aneurysm location and volume, in a stepwise binary logistic regression model.
The authors applied their model in a new cohort of patients with 49 aneurysms, with image analysis and use of the model performed independently by two researchers blinded to the patients' clinical status. The model correctly predicted rupture status of 39 of 49 aneurysms with an accuracy of 80 percent and a sensitivity and specificity of 83 and 78 percent, respectively, the report indicates.
"Our binary logistic regression model represents the first time that such a technique has been applied and validated for use in predicting aneurysm rupture. Although at the present sensitivity and accuracy this model is not robust enough for clinical evaluation, it does provide a basis from which more sensitive, specific, accurate and complex models may be derived. Future studies combining dynamic flow characteristics and the bioelastic properties of tissue may further enhance these models," the authors conclude.
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