{"title":"Computer Science meets Vascular Surgery: Keeping a pulse on artificial intelligence","authors":"Carly Thaxton , Alan Dardik","doi":"10.1053/j.semvascsurg.2023.05.003","DOIUrl":"10.1053/j.semvascsurg.2023.05.003","url":null,"abstract":"<div><p><span>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<span> 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, </span></span>risk stratification<span>, and follow-up, as well as patient-used applications to improve both patient and provider experiences, mitigate health care disparities<span>, 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.</span></span></p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589450/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46546498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nathan L. Liang , Timothy K. Chung , David A. Vorp
{"title":"The regulatory environment for artificial intelligence–enabled devices in the United States","authors":"Nathan L. Liang , Timothy K. Chung , David A. Vorp","doi":"10.1053/j.semvascsurg.2023.05.005","DOIUrl":"10.1053/j.semvascsurg.2023.05.005","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43104778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Protecting patient safety and privacy in the era of artificial intelligence","authors":"Andrea Alonso, Jeffrey J. Siracuse","doi":"10.1053/j.semvascsurg.2023.06.002","DOIUrl":"10.1053/j.semvascsurg.2023.06.002","url":null,"abstract":"<div><p><span>The promise of artificial intelligence (AI) in health care has propelled a significant uptrend in the number of </span>clinical trials<span><span><span> in AI and global market spending in this novel technology. In vascular surgery<span>, 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 </span></span>informed consent, accuracy and applicability of this technology, and propagation of </span>health care disparities. Vascular surgeons should be equipped to work with AI, as well as discuss its novel risks to patient safety and privacy.</span></p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47012857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amir Behzad Bagheri , Mohammad Dehghan Rouzi , Navid Alemi Koohbanani , Mohammad H. Mahoor , M.G. Finco , Myeounggon Lee , Bijan Najafi , Jayer Chung
{"title":"Potential applications of artificial intelligence and machine learning on diagnosis, treatment, and outcome prediction to address health care disparities of chronic limb-threatening ischemia","authors":"Amir Behzad Bagheri , Mohammad Dehghan Rouzi , Navid Alemi Koohbanani , Mohammad H. Mahoor , M.G. Finco , Myeounggon Lee , Bijan Najafi , Jayer Chung","doi":"10.1053/j.semvascsurg.2023.06.003","DOIUrl":"10.1053/j.semvascsurg.2023.06.003","url":null,"abstract":"<div><p><span><span>Chronic limb-threatening ischemia (CLTI) is the most advanced form of </span>peripheral artery disease. CLTI has an extremely poor prognosis and is associated with considerable risk of major amputation, cardiac morbidity, mortality, and poor </span>quality of life<span><span>. 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 </span>health care disparities<span> among patients. In this article, we reviewed how artificial intelligence (AI) and machine learning (ML) can be helpful to accurately diagnose, improve outcome prediction<span>, 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.</span></span></span></p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49684798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mature artificial intelligence– and machine learning–enabled medical tools impacting vascular surgical care: A scoping review of late-stage, US Food and Drug Administration–approved or cleared technologies relevant to vascular surgeons","authors":"David P. Stonko, Caitlin W. Hicks","doi":"10.1053/j.semvascsurg.2023.06.001","DOIUrl":"10.1053/j.semvascsurg.2023.06.001","url":null,"abstract":"<div><p><span><span>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 </span>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 </span>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.</p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589449/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49684761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fabien Lareyre , Arindam Chaudhuri , Christian-Alexander Behrendt , Alexandre Pouhin , Martin Teraa , Jonathan R. Boyle , Riikka Tulamo , Juliette Raffort
{"title":"Artificial intelligence–based predictive models in vascular diseases","authors":"Fabien Lareyre , Arindam Chaudhuri , Christian-Alexander Behrendt , Alexandre Pouhin , Martin Teraa , Jonathan R. Boyle , Riikka Tulamo , Juliette Raffort","doi":"10.1053/j.semvascsurg.2023.05.002","DOIUrl":"10.1053/j.semvascsurg.2023.05.002","url":null,"abstract":"<div><p><span><span>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 </span>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 </span><em>a priori</em><span> assumptions. This review provides an overview on the use of artificial intelligence–based prediction models in vascular diseases, specifically focusing on aortic aneurysm<span>, lower extremity arterial disease<span><span>, and carotid stenosis. Potential benefits include the development of precision medicine </span>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.</span></span></span></p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43168363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Libby Weaver , Laura T. Boitano , Brian J. Fazzone , Jonathan R. Krebs , Andrea H. Denton , Pranav Kapoor , Corey A. Kalbaugh , Jessica P. Simons
{"title":"Sex differences in outcomes of exercise therapy for patients with intermittent claudication: A scoping review","authors":"M. Libby Weaver , Laura T. Boitano , Brian J. Fazzone , Jonathan R. Krebs , Andrea H. Denton , Pranav Kapoor , Corey A. Kalbaugh , Jessica P. Simons","doi":"10.1053/j.semvascsurg.2023.08.001","DOIUrl":"10.1053/j.semvascsurg.2023.08.001","url":null,"abstract":"<div><p><span>Exercise therapy<span> is first-line treatment for </span></span>intermittent claudication<span><span> due to peripheral artery disease. We sought to synthesize the literature on sex differences in response to exercise therapy for the treatment of intermittent claudication due to peripheral artery disease. A scoping review was performed (1997 to 2023) using Ovid MEDLINE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Embase, SPORTDiscus, and Web of Science. Articles were included if they were a scientific report of any measures of health-related </span>quality of life<span> or walking performance after an intervention that included a structured walking program. Of the 13 studies, 11 included measures of walking distance; 7 included measures of walking time, 5 included measures of walking speed, and 4 included quality of life measures. Overall, exercise therapy resulted in significant improvements across most measures of walking performance for both men and females. When comparing magnitudes of outcome improvement by sex, results of walking-based measures were contradictory; some studies noted no difference and others found superior outcomes for men. Results of quality of life–based measures were also contradictory, with some finding no difference and others reporting substantially more improvement for females. Both men and females experienced considerable improvement in walking performance and quality of life with exercise therapy. Evidence regarding the differential effect of exercise therapy on outcomes by sex for intermittent claudication is limited and contradictory. Further efforts should be directed at using standardized interventions and metrics for measuring the outcomes that match the indications for intervention in these patients to better understand the expected benefits and any variance according to sex.</span></span></p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45944735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Considerations in the Application of Artificial Intelligence in Vascular Surgical Education","authors":"D. Rigberg, J. Jim","doi":"10.1053/j.semvascsurg.2023.07.004","DOIUrl":"https://doi.org/10.1053/j.semvascsurg.2023.07.004","url":null,"abstract":"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.","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43684457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mature AI/ML-Enabled Medical Tools Impacting Vascular Surgical Care: A scoping review of late-stage, FDA approved/cleared technologies relevant to vascular surgeons","authors":"David P. Stonko, C. Hicks","doi":"10.1053/j.semvascsurg.2023.06.001","DOIUrl":"https://doi.org/10.1053/j.semvascsurg.2023.06.001","url":null,"abstract":"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.","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46777706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amirbehzad Bagheri, Mohammad Dehghan Rouzi, Navid Alemi Koohbanani, M. Mahoor, MG Finco, Myeounggon Lee, B. Najafi, Jayer Chung
{"title":"Potential applications of artificial intelligence (AI) and machine learning (ML) on diagnosis, treatment, outcome prediction to address health care disparities of chronic limb-threatening ischemia (CLTI)","authors":"Amirbehzad Bagheri, Mohammad Dehghan Rouzi, Navid Alemi Koohbanani, M. Mahoor, MG Finco, Myeounggon Lee, B. Najafi, Jayer Chung","doi":"10.1053/j.semvascsurg.2023.06.003","DOIUrl":"https://doi.org/10.1053/j.semvascsurg.2023.06.003","url":null,"abstract":"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.","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45834884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}