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Updated: Aug 12, 2025

Endovascular Perforation Model for Subarachnoid Hemorrhage Combined with Magnetic Resonance Imaging MRI
Published on: December 16, 2021
Radiographic predictors of aneurysmal etiology in patients with aneurysmal pattern subarachnoid hemorrhage
Karl Baumgartner1, Aiden Meyer2, Daniel Mandel3
11Warren Alpert Medical School of Brown University.
Objective:
Spontaneous angiogram-negative nonperimesencephalic subarachnoid hemorrhage (an-NPSAH) can represent a diagnostic and management dilemma. The authors sought to determine radiographic predictors of aneurysmal etiology based on admission noncontrast head CT scans.
Methods:
The authors performed a retrospective cohort study of prospectively collected data from consecutive patients who were admitted for spontaneous subarachnoid hemorrhage (SAH) with suspected aneurysmal etiology to an academic center from 2016 to 2021. They compared blood thickness in the basal cisterns and sylvian fissures and modified Graeb scores on admission head CT scans between the two groups and subsequently developed a predictive model to identify aneurysmal etiology.
Results:
Of 259 included patients (mean age 56 years [SD 12.7 years]; 55% female), 209 had aneurysmal SAH (aSAH) and 50 had an-NPSAH. The median modified Graeb scores were similar for aSAH and an-NPSAH (6 [IQR 2-10] vs 3.5 [IQR 0-8.5], p = 0.33). The mean blood thickness was greater in the sylvian fissure (p = 0.010) and interhemispheric cisterns (p = 0.002), and there was a greater median degree of extension of blood in the sylvian fissures (p = 0.001) in aSAH than in an-NPSAH patients, but the mean blood thickness was less in the prepontine cistern (p = 0.014). The authors' scoring model was constructed based on differences in radiographic features. Receiver operating characteristic curve analysis showed acceptable accuracy in predicting aneurysmal etiology (area under the curve 0.71, 95% CI 0.62-0.79).
Conclusions:
There are differences in radiographic features on admission head CT between an-NPSAH and aSAH patients. The authors' proposed risk stratification model may be considered for further development and use in clinical practice in the future.
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