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

Autor: D'Oria M; Division of Vascular and Endovascular Surgery, Department of Medical Surgical and Health Sciences, University of Trieste, Strada di Fiume 447, 34149, Trieste, Italy. Electronic address: mario.doria88@outlook.com., Raffort J; Université Côte d'Azur, Le Centre National de la Recherche Scientifique, UMR7370, LP2M, Nice, France., Condino S; Department of Information Engineering, University of Pisa, Pisa, Italy; EndoCAS Center, University of Pisa, Pisa, Italy., Cutolo F; Department of Information Engineering, University of Pisa, Pisa, Italy; EndoCAS Center, University of Pisa, Pisa, Italy., Bertagna G; Vascular Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Italy., Berchiolli R; Vascular Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Italy., Scali S; Division of Vascular Surgery and Endovascular Therapy, University of Florida, Gainesville, FL., Griselli F; Division of Vascular and Endovascular Surgery, Department of Medical Surgical and Health Sciences, University of Trieste, Strada di Fiume 447, 34149, Trieste, Italy., Troisi N; Vascular Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Italy., Lepidi S; Division of Vascular and Endovascular Surgery, Department of Medical Surgical and Health Sciences, University of Trieste, Strada di Fiume 447, 34149, Trieste, Italy., Lareyre F; Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, France.
Jazyk: angličtina
Zdroj: Seminars in vascular surgery [Semin Vasc Surg] 2024 Sep; Vol. 37 (3), pp. 298-305. Date of Electronic Publication: 2024 Aug 06.
DOI: 10.1053/j.semvascsurg.2024.07.005
Abstrakt: 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.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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