The rapid adoption of artificial intelligence (AI) into everyday use has presented multiple issues for surgical educators to consider. In this article, the authors discuss some of the ethical aspects of academic integrit...The rapid adoption of artificial intelligence (AI) into everyday use has presented multiple issues for surgical educators to consider. In this article, the authors discuss some of the ethical aspects of academic integrity and the use of AI. These issues include the importance of understanding the current limits of AI and the inherent biases of the technology. The authors further discuss the ethical considerations of the use of AI in surgical training and in clinical use, with an emphasis on vascular surgery.
Semin Vasc Surg
· 2023 Sep · PMID 37863621
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Artificial intelligence and machine learning (AI/ML)-enabled tools are shifting from theoretical or research-only applications to mature, clinically useful tools. The goal of this article was to provide a scoping review...Artificial intelligence and machine learning (AI/ML)-enabled tools are shifting from theoretical or research-only applications to mature, clinically useful tools. The goal of this article was to provide a scoping review of the most mature AI/ML-enabled technologies reviewed and cleared by the US Food and Drug Administration relevant to the field of vascular surgery. Despite decades of slow progress, this landscape is now evolving rapidly, with more than 100 AI/ML-powered tools being approved by the US Food and Drug Administration each year. Within the field of vascular surgery specifically, this review identified 17 companies with mature technologies that have at least one US Food and Drug Administration clearance, all occurring between 2016 and 2022. The maturation of these technologies appears to be accelerating, with improving regulatory clarity and clinical uptake. The early AI/ML-powered devices extend or amplify clinically entrenched platform technologies and tend to be focused on the diagnosis or evaluation of time-sensitive, clinically important pathologies (eg, reading Digital Imaging and Communications in Medicine-compliant computed tomography images to identify pulmonary embolism), or when physician efficiency or time savings is improved (eg, preoperative planning and intraoperative guidance). The majority (>75%) of these technologies are at the intersection of radiology and vascular surgery. It is becoming increasingly important that the contemporary vascular surgeon understands this shifting paradigm, as these once-nascent technologies are finally maturing and will be encountered with increasingly regularity in daily clinical practice.
Chronic limb-threatening ischemia (CLTI) is the most advanced form of peripheral artery disease. CLTI has an extremely poor prognosis and is associated with considerable risk of major amputation, cardiac morbidity, morta...Chronic limb-threatening ischemia (CLTI) is the most advanced form of peripheral artery disease. CLTI has an extremely poor prognosis and is associated with considerable risk of major amputation, cardiac morbidity, mortality, and poor quality of life. Early diagnosis and targeted treatment of CLTI is critical for improving patient's prognosis. However, this objective has proven elusive, time-consuming, and challenging due to existing health care disparities among patients. In this article, we reviewed how artificial intelligence (AI) and machine learning (ML) can be helpful to accurately diagnose, improve outcome prediction, and identify disparities in the treatment of CLTI. We demonstrate the importance of AI/ML approaches for management of these patients and how available data could be used for computer-guided interventions. Although AI/ML applications to mitigate health care disparities in CLTI are in their infancy, we also highlighted specific AI/ML methods that show potential for addressing health care disparities in CLTI.
Despite advances in prevention, detection, and treatment, cardiovascular disease is a leading cause of mortality and represents a major health problem worldwide. Artificial intelligence and machine learning have brought...Despite advances in prevention, detection, and treatment, cardiovascular disease is a leading cause of mortality and represents a major health problem worldwide. Artificial intelligence and machine learning have brought new insights to the management of vascular diseases by allowing analysis of huge and complex datasets and by offering new techniques to develop advanced imaging analysis. Artificial intelligence-based applications have the potential to improve prognostic evaluation and evidence-based decision making and contribute to vascular therapeutic decision making. In this scoping review, we provide an overview on how artificial intelligence could help in vascular surgical clinical decision making, highlighting potential benefits, current limitations, and future challenges.
Cardiovascular disease represents a source of major health problems worldwide, and although medical and technical advances have been achieved, they are still associated with high morbidity and mortality rates. Personaliz...Cardiovascular disease represents a source of major health problems worldwide, and although medical and technical advances have been achieved, they are still associated with high morbidity and mortality rates. Personalized medicine would benefit from novel tools to better predict individual prognosis and outcomes after intervention. Artificial intelligence (AI) has brought new insights to cardiovascular medicine, especially with the use of machine learning techniques that allow the identification of hidden patterns and complex associations in health data without any a priori assumptions. This review provides an overview on the use of artificial intelligence-based prediction models in vascular diseases, specifically focusing on aortic aneurysm, lower extremity arterial disease, and carotid stenosis. Potential benefits include the development of precision medicine in patients with vascular diseases. In addition, the main challenges that remain to be overcome to integrate artificial intelligence-based predictive models in clinical practice are discussed.
The regulatory environment in the United States has not kept pace with the rapidly developing market for artificial intelligence (AI)-enabled devices. The number of AI-enabled devices has increased year after year. All o...The regulatory environment in the United States has not kept pace with the rapidly developing market for artificial intelligence (AI)-enabled devices. The number of AI-enabled devices has increased year after year. All of these devices are registered or cleared by the US Food and Drug Administration through exempt or 510(k) premarket notification pathways, and the majority are related to the radiology or cardiovascular spaces. US Food and Drug Administration guidance has not yet addressed the unique challenges of AI-enabled devices, including development, comprehensibility, and continuously learning models. The liability aspects of AI-enabled devices deployed into use by clinicians in practice have yet to be addressed. Future guidance from government regulatory sources will be necessary as the field moves forward.
Application of artificial intelligence (AI) has revolutionized the utilization of big data, especially in patient care. The potential of deep learning models to learn without a priori assumption, or without prior learnin...Application of artificial intelligence (AI) has revolutionized the utilization of big data, especially in patient care. The potential of deep learning models to learn without a priori assumption, or without prior learning, to connect seemingly unrelated information mixes excitement alongside hesitation to fully understand AI's limitations. Bias, ranging from data collection and input to algorithm development to finally human review of algorithm output affects AI's application to clinical patient presents unique challenges that differ significantly from biases in traditional analyses. Algorithm fairness, a new field of research within AI, aims to mitigate bias by evaluating the data at the preprocessing stage, optimizing during algorithm development, and evaluating algorithm output at the postprocessing stage. As the field continues to develop, being cognizant of the inherent biases and limitations related to black box decision making, biased data sets agnostic to patient-level disparities, wide variation of present methodologies, and lack of common reporting standards will require ongoing research to provide transparency to AI and its applications.
The promise of artificial intelligence (AI) in health care has propelled a significant uptrend in the number of clinical trials in AI and global market spending in this novel technology. In vascular surgery, this technol...The promise of artificial intelligence (AI) in health care has propelled a significant uptrend in the number of clinical trials in AI and global market spending in this novel technology. In vascular surgery, this technology has the ability to diagnose disease, predict disease outcomes, and assist with image-guided surgery. As we enter an era of rapid change, it is critical to evaluate the ethical concerns of AI, particularly as it may impact patient safety and privacy. This is particularly important to discuss in the early stages of AI, as technology frequently outpaces the policies and ethical guidelines regulating it. Issues at the forefront include patient privacy and confidentiality, protection of patient autonomy and informed consent, accuracy and applicability of this technology, and propagation of health care disparities. Vascular surgeons should be equipped to work with AI, as well as discuss its novel risks to patient safety and privacy.
Semin Vasc Surg
· 2023 Sep · PMID 37863614
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Artificial intelligence (AI)-based technologies have garnered interest across a range of disciplines in the past several years, with an even more recent interest in various health care fields, including Vascular Surgery....Artificial intelligence (AI)-based technologies have garnered interest across a range of disciplines in the past several years, with an even more recent interest in various health care fields, including Vascular Surgery. AI offers a unique ability to analyze health data more quickly and efficiently than could be done by humans alone and can be used for clinical applications such as diagnosis, risk stratification, and follow-up, as well as patient-used applications to improve both patient and provider experiences, mitigate health care disparities, and individualize treatment. As with all novel technologies, AI is not without its risks and carries with it unique ethical considerations that will need to be addressed before its broad integration into health care systems. AI has the potential to revolutionize the way care is provided to patients, including those requiring vascular care.
Deep learning, a subset of machine learning within artificial intelligence, has been successful in medical image analysis in vascular surgery. Unlike traditional computer-based segmentation methods that manually extract...Deep learning, a subset of machine learning within artificial intelligence, has been successful in medical image analysis in vascular surgery. Unlike traditional computer-based segmentation methods that manually extract features from input images, deep learning methods learn image features and classify data without making prior assumptions. Convolutional neural networks, the main type of deep learning for computer vision processing, are neural networks with multilevel architecture and weighted connections between nodes that can "auto-learn" through repeated exposure to training data without manual input or supervision. These networks have numerous applications in vascular surgery imaging analysis, particularly in disease classification, object identification, semantic segmentation, and instance segmentation. The purpose of this review article was to review the relevant concepts of machine learning image analysis and its application to the field of vascular surgery.
Dossabhoy SS, Ho VT, Ross EG
… +2 more, Rodriguez F, Arya S
Semin Vasc Surg
· 2023 Sep · PMID 37863612
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In the past decade, artificial intelligence (AI)-based applications have exploded in health care. In cardiovascular disease, and vascular surgery specifically, AI tools such as machine learning, natural language processi...In the past decade, artificial intelligence (AI)-based applications have exploded in health care. In cardiovascular disease, and vascular surgery specifically, AI tools such as machine learning, natural language processing, and deep neural networks have been applied to automatically detect underdiagnosed diseases, such as peripheral artery disease, abdominal aortic aneurysms, and atherosclerotic cardiovascular disease. In addition to disease detection and risk stratification, AI has been used to identify guideline-concordant statin therapy use and reasons for nonuse, which has important implications for population-based cardiovascular disease health. Although many studies highlight the potential applications of AI, few address true clinical workflow implementation of available AI-based tools. Specific examples, such as determination of optimal statin treatment based on individual patient risk factors and enhancement of intraoperative fluoroscopy and ultrasound imaging, demonstrate the potential promise of AI integration into clinical workflow. Many challenges to AI implementation in health care remain, including data interoperability, model bias and generalizability, prospective evaluation, privacy and security, and regulation. Multidisciplinary and multi-institutional collaboration, as well as adopting a framework for integration, will be critical for the successful implementation of AI tools into clinical practice.
In recent years, artificial intelligence (AI) has permeated different aspects of vascular surgery to solve challenges in clinical practice. Although AI in vascular surgery is still in its early stages, there have been pr...In recent years, artificial intelligence (AI) has permeated different aspects of vascular surgery to solve challenges in clinical practice. Although AI in vascular surgery is still in its early stages, there have been promising developments in its applications to vascular diagnosis, risk stratification, and outcome prediction. By establishing a baseline knowledge of AI, vascular surgeons are better equipped to use and interpret the data from these types of projects. This review aims to provide an overview of the fundamentals of AI and highlight its role in helping vascular surgeons overcome the challenges of clinical practice. In addition, we discuss the limitations of AI and how they affect AI applications.
Vascular specialists remain in high demand in current practice and commonly oversee care delivery for a variety of clinical emergencies. Accordingly, the contemporary vascular surgeon must be facile with treating a spect...Vascular specialists remain in high demand in current practice and commonly oversee care delivery for a variety of clinical emergencies. Accordingly, the contemporary vascular surgeon must be facile with treating a spectrum of problems, including a complex, heterogeneous group of acute arteriovenous thromboembolic and bleeding diatheses. It has been documented previously that there are substantial current workforce limitations placing constraints on vascular surgical care provision. Moreover, with the aging at-risk population, there remains a considerable national urgency to improve timely diagnoses, specialty consultation, and appropriate transfer of patients to centers of excellence capable of providing a comprehensive compendium of emergency vascular services. Clinical decision aids, simulation training, and regionalization of nonelective vascular problems are all strategies that have been increasingly recognized to address these service gaps. Notably, clinical research in vascular surgery has traditionally focused on identification of patient- and procedure-related factors that influence outcomes by using resource-intensive causal inference methodology. By comparison, large data sets have only more recently been recognized to be a valuable tool that can provide heuristic algorithms to address more complex health care problems. Such data can be manipulated to generate clinical risk scores and decision aids, as well as robust outcome descriptions, which stand to inform stakeholders regarding best practice. The purpose of this review was to provide a robust overview of the lessons derived from the application of big data, risk prediction, and simulation in the management of vascular emergencies.
The management of emergencies related to the aorta requires a multidisciplinary approach involving various health care professionals. Despite technological advancements in treatment methods, the risks and mortality rates...The management of emergencies related to the aorta requires a multidisciplinary approach involving various health care professionals. Despite technological advancements in treatment methods, the risks and mortality rates associated with surgery remain high. In the emergency department, definitive diagnosis is usually obtained through computed tomography angiography, and management focuses on controlling blood pressure and treating symptoms to prevent further deterioration. Preoperative resuscitation is the main focus, followed by intraoperative management aimed at stabilizing the patient's hemodynamics, controlling bleeding, and protecting vital organs. After the operation, factors such as organ protection, transfusion management, pain control, and overall patient care must be taken into account. Endovascular techniques are becoming more common in surgical treatment, but they also present new challenges in terms of complications and outcomes. It is recommended that patients with suspected ruptured abdominal aortic aneurysms be transferred to facilities with both open and endovascular treatment options and a track record of successful outcomes to ensure the best patient care and long-term results. To achieve optimal patient outcomes, close collaboration and regular case discussions between health care professionals are necessary, as well as participation in educational programs to promote a culture of teamwork and continuous improvement.
Multimodal imaging is the incorporation of two or more imaging modalities during the same examination, and it has both diagnostic and treatment applications. The use of image fusion for intraoperative guidance in endovas...Multimodal imaging is the incorporation of two or more imaging modalities during the same examination, and it has both diagnostic and treatment applications. The use of image fusion for intraoperative guidance in endovascular interventions is being extended increasingly to the field of vascular surgery, especially in the context of hybrid operating rooms. The aim of this work was to perform a review and narrative synthesis of the available literature in order to report on current applications of multimodal imaging in diagnosis and treatment of emergent vascular conditions. Of 311 records selected in the initial search, 10 articles were included in the present review: 4 cohort studies and 6 case reports. The authors have presented their experience in treating ruptured abdominal aortic aneurysms; aortic dissections; traumas; standard endovascular aortic aneurysm repair, with or without deterioration of renal function; and complex endovascular aortic aneurysm repair, and reported on the long-term clinical results. Although the current literature about multimodal imaging application in emergency vascular conditions is limited, this review highlights the potential of image fusion in hybrid angio-surgical suites, especially for diagnosing and performing treatment in the same operating room, avoiding patient transfer, and allowing procedures with zero or low-dose contrast mean.
Vascular surgical emergencies are common in vascular surgical care and require complex decision making and multidisciplinary care. They are especially challenging when they occur in patients with unique physiological cha...Vascular surgical emergencies are common in vascular surgical care and require complex decision making and multidisciplinary care. They are especially challenging when they occur in patients with unique physiological characteristics, such as pediatric, pregnant, and frail patients. Among the pediatric and pregnant population, vascular emergencies are rare. This rarity challenges accurate and timely diagnosis of the vascular emergency. This landscape review summarizes these three unique populations' epidemiology and emergency vascular considerations. Understanding the epidemiology is the foundation for accurate diagnosis and subsequent management. Considering each population's unique characteristics is crucial to the emergent vascular surgical interventions decision making. Collaborative and multidisciplinary care is vital in gaining expertise in managing these special populations and achieving optimal patient outcomes.
Severe surgical site infections (SSIs) are a frequent nosocomial complication after vascular interventions, an important cause of postoperative morbidity, and a substantial burden to the health care system. Patients unde...Severe surgical site infections (SSIs) are a frequent nosocomial complication after vascular interventions, an important cause of postoperative morbidity, and a substantial burden to the health care system. Patients undergoing arterial interventions are at elevated risk of SSIs, possibly because of the presence of several risk factors in this patient population. In this review, we examined the available clinical evidence for the prevention, treatment, and prognostication of postoperative severe SSIs after vascular exposure in the groin and other body areas. Results from studies evaluating preoperative, intraoperative, and postoperative preventive strategies and several treatment options are reviewed. In addition, risk factors for surgical wound infections are analyzed in detail and related evidence from the literature is highlighted. Although several measures have been implemented over the time to prevent them, SSIs continue to pose a substantial health care and socioeconomic challenge. Therefore, strategies to decrease the risk and improve the treatment of SSIs for the high-risk vascular patient population should be the focus of continuing improvement and critical review. This review aimed at identifying and reviewing the current evidence for preventing, treating, and performing stratification according to the prognosis of postoperative severe SSIs after vascular exposure in the groin and other body areas.
A direct percutaneous arterial and venous approach to the common femoral vessel has become the first option in most large-bore percutaneous vascular and cardiac procedures, making the issue of access site-related complic...A direct percutaneous arterial and venous approach to the common femoral vessel has become the first option in most large-bore percutaneous vascular and cardiac procedures, making the issue of access site-related complications (ASCs) a pressing clinical concern. ASCs represent a potentially limb-threating and/or life-threatening scenario that alters the clinical success of the procedure and contributes to increased length of stay and resource utilization. Preoperative assessment of risk factors for ASCs should be well known before planning an endovascular percutaneous procedure and early diagnosis is necessary for prompt treatment. Several percutaneous and surgical approaches have been reported in case of ASCs, according to the different etiologies of these complications. The aim of this review was to report the incidence of ASCs in vascular and cardiac large-bore procedures, diagnosis, and available treatments according to the latest available literature.
"Acute venous problems" refers to a group of disorders that affect the veins and result in sudden and severe symptoms. They can be classified based on the pathological triggering mechanisms, such as thrombosis and/or mec..."Acute venous problems" refers to a group of disorders that affect the veins and result in sudden and severe symptoms. They can be classified based on the pathological triggering mechanisms, such as thrombosis and/or mechanical compression, and their consequences, including symptoms, signs, and complications. The management and therapeutic approach depend on the severity of the disease, the location, and the involvement of the vein segment. Although summarizing these conditions can be challenging, the objective of this narrative review was to provide an overview of the most common acute venous problems. This will include an exhaustive yet concise and practical description of each condition. The multidisciplinary approach remains one of the major advantages in dealing with these conditions, maximizing the results and the prevention of complications.