Computational surgery in the management of patients with abdominal aortic aneurysms: Opportunities, challenges, and future directions

被引:1
作者
D'Oria, Mario [1 ]
Raffort, Juliette [2 ]
Condino, Sara [3 ,4 ]
Cutolo, Fabrizio [3 ,4 ]
Bertagna, Giulia [5 ]
Berchiolli, Raffaella [5 ]
Scali, Salvatore [6 ]
Griselli, Filippo [1 ]
Troisi, Nicola [5 ]
Lepidi, Sandro [1 ]
Lareyre, Fabien [7 ]
机构
[1] Univ Trieste, Dept Med Surg & Hlth Sci, Div Vasc & Endovasc Surg, Str Fiume 447, I-34149 Trieste, Italy
[2] Univ Cote Azur, Ctr Natl Rech Sci, UMR7370, LP2M, Nice, France
[3] Univ Pisa, Dept Informat Engn, Pisa, Italy
[4] Univ Pisa, EndoCAS Ctr, Pisa, Italy
[5] Univ Pisa, Dept Translat Res & New Technol Med & Surg, Vasc Surg Unit, Pisa, Italy
[6] Univ Florida, Div Vasc Surg & Endovasc Therapy, Gainesville, FL USA
[7] Hosp Antibes Juan Les Pins, Dept Vasc Surg, Nice, France
关键词
Abdominal aortic aneurysm; Artificial intelligence; Machine learning; Computational surgery; ARTIFICIAL-INTELLIGENCE; REPAIR; PREDICTION; SIMULATION; MORTALITY;
D O I
10.1053/j.semvascsurg.2024.07.005
中图分类号
R61 [外科手术学];
学科分类号
摘要
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. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
引用
收藏
页码:298 / 305
页数:8
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