Natural History of Cerebral Aneurysms: Risk Factors for Rupture and Implications for Management

Area of Science:

• Neurosurgery
• Medical Imaging
• Artificial Intelligence

Background:

• Intracranial aneurysms affect 2-3% of adults, posing risks of rupture, high morbidity, mortality, and economic costs.
• Traditional risk assessment relies on population-based models, which may not capture individual patient risks effectively.

Purpose of the Study:

• To review the impact of cerebral aneurysm epidemiology on risk stratification.
• To emphasize the integration of clinical risk scales with advanced imaging and artificial intelligence (AI).
• To advocate for a dynamic, multimodal approach for optimizing cerebral aneurysm management.

Main Methods:

• Review of current literature on intracranial aneurysm epidemiology.
• Analysis of the integration of computational neuroimaging, computational tools, and AI in risk assessment.
• Evaluation of advanced imaging and AI for enhanced stratification and monitoring.

Main Results:

• Advances in computational neuroimaging and AI enable a shift from population-based to individualized risk assessment.
• Integration of clinical risk scales with advanced imaging and AI improves risk stratification and monitoring.
• Multimodal approaches leveraging technological and scientific advances are crucial for quantifying risk.

Conclusions:

• A dynamic, multimodal approach is essential for optimizing cerebral aneurysm management.
• Leveraging technological and scientific advances can quantify risk more effectively.
• Individualized risk assessment using advanced imaging and AI holds promise for improved patient outcomes.