The results of this study demonstrate that the newly developed AI-based 3D tool is a highly accurate and efficient method for extracting morphological features from pre-operative CTA images for EVAR planning in AAA patients. The AI tool showed good agreement with manually extracted measurements, adhering to the European Society for Vascular Surgery (ESVS) 2024 guidelines for EVAR, and significantly reduced the time required for data extraction. The implementation of this AI tool in clinical practice could lead to more standardized and efficient pre-operative planning, reducing the potential for errors in stent graft sizing.

Given the increasing demand for EVAR procedures and the growing complexity of AAA cases, the tool’s ability to save time without sacrificing accuracy could be a breakthrough for busy surgical teams, enabling faster decision-making and more streamlined workflows. With the increasing demand for EVAR procedures and the growing complexity of AAA cases, the integration of AI tools into clinical practice is a crucial step toward improving the quality and efficiency of care.