3D Quantified Morphologic Predictors of Intracranial Aneurysm Instability: A Longitudinal Study

Area of Science:

• Neurosurgery
• Radiology
• Medical Imaging

Background:

• Current prediction models for intracranial aneurysm growth and rupture are suboptimal.
• There is a need for longitudinal studies using standardized morphological parameters.
• Three-dimensional (3D) quantified morphological parameters can potentially improve prediction accuracy.

Purpose of the Study:

• To identify standardized 3D quantified morphological parameters as predictors of aneurysm growth or rupture.
• To evaluate the predictive performance of these parameters in a longitudinal study.
• To enhance the accuracy of intracranial aneurysm management.

Main Methods:

• Retrospective case-cohort design using a database of unruptured intracranial aneurysms (UIAs).
• Annotation of aneurysms on baseline CTA or MRA images and quantification of 3D morphological parameters.
• Application of univariable and multivariable Cox proportional hazards models with inverse sampling probability weights.

Main Results:

• A total of 327 aneurysms were analyzed; 73% remained stable, 21% grew, 2% grew with rupture, and 4% ruptured without growth.
• Major axis and shape index were retained in multivariable models for growth (c-statistic 0.56) and rupture (c-statistic 0.85) prediction.
• The shape index demonstrated higher predictive power for rupture (HR 3.33) than for growth (HR 1.53).

Conclusions:

• Major axis and shape index are candidate 3D morphological predictors for UIA growth and rupture.
• These parameters exhibited good discriminative power for rupture prediction in the studied cohort.
• External validation and integration with existing clinical models are necessary for clinical application.