Artificial Intelligence-Powered Technologies for the Management of Vascular Diseases: Building Guidelines and Moving Forward Evidence Generation

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

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.

Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review

Cardiovascular diseases (CVDs) are significant health issues that result in high death rates globally. Early detection of cardiovascular events may lower the occurrence of acute myocardial infarction and reduce death rates in people with CVDs. Traditional data analysis is inadequate for managing multidimensional data related to the risk prediction of CVDs, heart attacks, medical image interpretations, therapeutic decision-making, and disease prognosis due to the complex pathological mechanisms and multiple factors involved. Artificial intelligence (AI) is a technology that utilizes advanced computer algorithms to extract information from large databases, and it has been integrated into the medical industry. AI methods have shown the ability to speed up the advancement of diagnosing and treating CVDs such as heart failure, atrial fibrillation, valvular heart disease, hypertrophic cardiomyopathy, congenital heart disease, and more. In clinical settings, AI has shown usefulness in diagnosing cardiovascular illness, improving the efficiency of supporting tools, stratifying and categorizing diseases, and predicting outcomes. Advanced AI algorithms have been intricately designed to analyze intricate relationships within extensive healthcare data, enabling them to tackle more intricate jobs compared to conventional approaches.

Editor's Choice -- European Society for Vascular Surgery (ESVS) 2024 Clinical Practice Guidelines on the Management of Abdominal Aorto-Iliac Artery Aneurysms

OBJECTIVE

The European Society for Vascular Surgery (ESVS) has developed clinical practice guidelines for the care of patients with aneurysms of the abdominal aorta and iliac arteries in succession to the 2011 and 2019 versions, with the aim of assisting physicians and patients in selecting the best management strategy.

METHODS

The guideline is based on scientific evidence completed with expert opinion on the matter. By summarising and evaluating the best available evidence, recommendations for the evaluation and treatment of patients have been formulated. The recommendations are graded according to a modified European Society of Cardiology grading system, where the strength (class) of each recommendation is graded from I to III and the letters A to C mark the level of evidence.

RESULTS

A total of 160 recommendations have been issued on the following topics: Service standards, including surgical volume and training; Epidemiology, diagnosis, and screening; Management of patients with small abdominal aortic aneurysm (AAA), including surveillance, cardiovascular risk reduction, and indication for repair; Elective AAA repair, including operative risk assessment, open and endovascular repair, and early complications; Ruptured and symptomatic AAA, including peri-operative management, such as permissive hypotension and use of aortic occlusion balloon, open and endovascular repair, and early complications, such as abdominal compartment syndrome and colonic ischaemia; Long term outcome and follow up after AAA repair, including graft infection, endoleaks and follow up routines; Management of complex AAA, including open and endovascular repair; Management of iliac artery aneurysm, including indication for repair and open and endovascular repair; and Miscellaneous aortic problems, including mycotic, inflammatory, and saccular aortic aneurysm. In addition, Shared decision making is being addressed, with supporting information for patients, and Unresolved issues are discussed.

CONCLUSION

The ESVS Clinical Practice Guidelines provide the most comprehensive, up to date, and unbiased advice to clinicians and patients on the management of abdominal aorto-iliac artery aneurysms.