Comprehensive Management of Intracranial Aneurysms Using Artificial Intelligence: An Overview

Area of Science:

• Neurosurgery
• Medical Imaging
• Artificial Intelligence

Background:

• Intracranial aneurysms (IAs) are increasingly diagnosed due to advanced imaging.
• Ruptured IAs cause significant mortality and disability.
• Early detection and intervention are crucial for managing IA rupture risk.

Purpose of the Study:

• To review the latest advancements in AI for intracranial aneurysm management.
• To highlight AI's role in improving detection, risk assessment, and treatment outcomes.
• To discuss challenges and future directions for clinical AI deployment in neurovascular care.

Main Methods:

• Deep learning algorithms for precise aneurysm identification and segmentation.
• AI-powered analysis of large datasets for predicting aneurysm growth and rupture.
• Review of AI applications in microcatheter shaping and therapeutic outcome prediction.

Main Results:

• AI significantly enhances diagnostic sensitivity and accuracy in IA detection.
• AI provides valuable tools for forecasting aneurysm growth and rupture risk.
• AI facilitates improved decision-making for clinicians in managing intracranial aneurysms.

Conclusions:

• AI demonstrates significant potential in advancing the diagnosis and management of intracranial aneurysms.
• AI applications offer improved accuracy and predictive capabilities for IA rupture.
• Addressing challenges is key to successful clinical integration of AI in neurovascular interventions.