Abstract
Computational surgery (CS) is an interdisciplinary field that uses mathematical models and algorithms to focus specifically on operative planning, simulation and outcomes analysis to improve surgical care provision. As the digital revolution transforms the surgical work environment through broader adoption of artificial intelligence (AI) and machine learning (ML), close collaboration between surgeons and computational scientists is not only unavoidable but will become essential. In this review we will summarize the main advances, as well as ongoing challenges and prospects that surround the implementation of CS techniques in vascular surgery, with a particular focus on the care of patients affected by abdominal aortic aneurysms (AAA). Several key areas of AAA care delivery including patient-specific modelling, virtual surgery simulation, intraoperative imaging guided surgery, predictive analytics, as well as biomechanical analysis and machine learning will be discussed.The overarching goals of these CS applications is to improve the precision and accuracy of AAA repair procedures while enhancing safety and long-term outcomes. Accordingly, computational surgery has the potential to significantly enhance patient care across the entire surgical journey, from pre-operative planning and intra-operative decision-making to post-operative surveillance. Moreover, CS-based approaches offer promising opportunities to augment AAA repair quality by enabling precise preoperative simulations, real-time intraoperative navigation, and robust postoperative monitoring. However, integrating these advanced computer-based technologies into medical research and clinical practice presents new challenges. These include addressing technical limitations, ensuring accuracy and reliability, and managing unique ethical considerations associated with their use. Thorough evaluation of these aspects of advanced computations techniques in AAA management is crucial before widespread integration into healthcare systems can be achieved.
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