Computational surgery in the management of patients with abdominal aortic aneurysms: Opportunities, challenges, and future directions.
Humans
Aortic Aneurysm, Abdominal
/ surgery
Patient-Specific Modeling
Surgery, Computer-Assisted
/ adverse effects
Treatment Outcome
Predictive Value of Tests
Machine Learning
Models, Cardiovascular
Forecasting
Diffusion of Innovation
Vascular Surgical Procedures
/ adverse effects
Clinical Decision-Making
Endovascular Procedures
/ adverse effects
Abdominal aortic aneurysm
Artificial intelligence
Computational surgery
Machine learning
Journal
Seminars in vascular surgery
ISSN: 1558-4518
Titre abrégé: Semin Vasc Surg
Pays: United States
ID NLM: 8809602
Informations de publication
Date de publication:
Sep 2024
Sep 2024
Historique:
received:
14
05
2024
revised:
13
07
2024
accepted:
22
07
2024
medline:
15
9
2024
pubmed:
15
9
2024
entrez:
14
9
2024
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 39277345
pii: S0895-7967(24)00043-7
doi: 10.1053/j.semvascsurg.2024.07.005
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
298-305Informations de copyright
Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
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.