Division of Vascular and Endovascular Surgery, Department of Medical Surgical and Health Sciences, University of Trieste, Strada di Fiume 447, 34149, Trieste, Italy.
Université Côte d'Azur, Le Centre National de la Recherche Scientifique, UMR7370, LP2M, Nice, France.
Semin Vasc Surg. 2024 Sep;37(3):298-305. doi: 10.1053/j.semvascsurg.2024.07.005. Epub 2024 Aug 6.
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 and machine learning, close collaboration between surgeons and computational scientists is not only unavoidable, but will become essential. In this review, the authors 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 (AAAs). Several key areas of AAA care delivery, including patient-specific modelling, virtual surgery simulation, intraoperative imaging-guided surgery, and 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, CS has the potential to significantly enhance patient care across the entire surgical journey, from preoperative planning and intraoperative decision making to postoperative 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 computation techniques in AAA management is crucial before widespread integration into health care systems can be achieved.
计算外科学(CS)是一个跨学科领域,它使用数学模型和算法专门关注手术规划、模拟和结果分析,以改善外科护理服务。随着数字革命通过更广泛地采用人工智能和机器学习来改变外科工作环境,外科医生和计算科学家之间的密切合作不仅是不可避免的,而且将变得至关重要。在这篇综述中,作者总结了 CS 技术在血管外科学中的主要进展、当前挑战和前景,特别关注接受腹主动脉瘤(AAA)治疗的患者。将讨论 AAA 护理提供的几个关键领域,包括患者特异性建模、虚拟手术模拟、术中成像引导手术和预测分析以及生物力学分析和机器学习。这些 CS 应用的总体目标是提高 AAA 修复手术的精确性和准确性,同时提高安全性和长期结果。因此,CS 有可能通过增强术前规划和术中决策的精确性,以及术后监测,显著改善整个手术过程中的患者护理。此外,基于 CS 的方法通过实现精确的术前模拟、实时术中导航和稳健的术后监测,为增强 AAA 修复质量提供了有前途的机会。然而,将这些先进的基于计算机的技术整合到医学研究和临床实践中提出了新的挑战。这些挑战包括解决技术限制、确保准确性和可靠性,以及管理与使用相关的独特伦理问题。在将这些先进的计算技术广泛整合到医疗保健系统之前,对 AAA 管理中这些方面进行全面评估至关重要。