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Lareyre F, Behrendt CA, Chaudhuri A, Lee R, Carrier M, Adam C, Lê CD, Raffort J. Applications of artificial intelligence for patients with peripheral artery disease. J Vasc Surg 2023; 77:650-658.e1. [PMID: 35921995 DOI: 10.1016/j.jvs.2022.07.160] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 05/06/2022] [Accepted: 07/19/2022] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Applications of artificial intelligence (AI) have been reported in several cardiovascular diseases but its interest in patients with peripheral artery disease (PAD) has been so far less reported. The aim of this review was to summarize current knowledge on applications of AI in patients with PAD, to discuss current limits, and highlight perspectives in the field. METHODS We performed a narrative review based on studies reporting applications of AI in patients with PAD. The MEDLINE database was independently searched by two authors using a combination of keywords to identify studies published between January 1995 and December 2021. Three main fields of AI were investigated including natural language processing (NLP), computer vision and machine learning (ML). RESULTS NLP and ML brought new tools to improve the screening, the diagnosis and classification of the severity of PAD. ML was also used to develop predictive models to better assess the prognosis of patients and develop real-time prediction models to support clinical decision-making. Studies related to computer vision mainly aimed at creating automatic detection and characterization of arterial lesions based on Doppler ultrasound examination or computed tomography angiography. Such tools could help to improve screening programs, enhance diagnosis, facilitate presurgical planning, and improve clinical workflow. CONCLUSIONS AI offers various applications to support and likely improve the management of patients with PAD. Further research efforts are needed to validate such applications and investigate their accuracy and safety in large multinational cohorts before their implementation in daily clinical practice.
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Affiliation(s)
- Fabien Lareyre
- Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, Antibes, France; Université Côte d'Azur, INSERM U1065, C3M, Nice, France.
| | - Christian-Alexander Behrendt
- Research Group GermanVasc, Department of Vascular Medicine, University Heart and Vascular Centre UKE Hamburg, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Arindam Chaudhuri
- Bedfordshire-Milton Keynes Vascular Centre, Bedfordshire Hospitals NHS Foundation Trust, Bedford, UK
| | - Regent Lee
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Marion Carrier
- Laboratory of Applied Mathematics and Computer Science (MICS), CentraleSupélec, Université Paris-Saclay, Paris, France
| | - Cédric Adam
- Laboratory of Applied Mathematics and Computer Science (MICS), CentraleSupélec, Université Paris-Saclay, Paris, France
| | - Cong Duy Lê
- Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, Antibes, France; Université Côte d'Azur, INSERM U1065, C3M, Nice, France
| | - Juliette Raffort
- Université Côte d'Azur, INSERM U1065, C3M, Nice, France; Clinical Chemistry Laboratory, University Hospital of Nice, Nice, France; AI Institute 3IA Côte d'Azur, Université Côte d'Azur, Côte d'Azur, France
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Serra R, Bracale UM, Barbetta A, Ielapi N, Licastro N, Gallo A, Fregola S, Turchino D, Gasbarro V, Mastroroberto P, de Franciscis S. PredyCLU: A prediction system for chronic leg ulcers based on fuzzy logic; part II-Exploring the arterial side. Int Wound J 2020; 17:987-991. [PMID: 32285613 DOI: 10.1111/iwj.13360] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/17/2020] [Accepted: 03/20/2020] [Indexed: 11/27/2022] Open
Abstract
Peripheral arterial disease (PAD) and its most severe form, critical limb ischaemia (CLI), are very common clinical conditions related to atherosclerosis and represent the major causes of morbidity, mortality, disability, and reduced quality of life (QoL), especially for the onset of ischaemic chronic leg ulcers (ICLUs) and the subsequent need of amputation in affected patients. Early identification of patients at risk of developing ICLUs may represent the best form of prevention and appropriate management. In this study, we used a Prediction System for Chronic Leg Ulcers (PredyCLU) based on fuzzy logic applied to patients with PAD. The patient population consisted of 80 patients with PAD, of which 40 patients (30 males [75%] and 10 females [25%]; mean age 66.18 years; median age 67.50 years) had ICLUs and represented the case group. Forty patients (100%) (27 males [67.50%] and 13 females [32.50%]; mean age 66.43 years; median age 66.50 years) did not have ICLUs and represented the control group. In patients of the case group, the higher was the risk calculated with the PredyCLU the more severe were the clinical manifestations recorded. In this study, the PredyCLU algorithm was retrospectively applied on a multicentre population of 80 patients with PAD. The PredyCLU algorithm provided a reliable risk score for the risk of ICLUs in patients with PAD.
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Affiliation(s)
- Raffaele Serra
- Interuniversity Center of Phlebolymphology (CIFL), International Research and Educational Program in Clinical and Experimental Biotechnology", Catanzaro, Italy.,Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy
| | - Umberto M Bracale
- Department of Public Health, University of Naples "Federico II", Naples, Italy
| | - Andrea Barbetta
- Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy
| | - Nicola Ielapi
- Interuniversity Center of Phlebolymphology (CIFL), International Research and Educational Program in Clinical and Experimental Biotechnology", Catanzaro, Italy.,Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy.,Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
| | - Noemi Licastro
- Interuniversity Center of Phlebolymphology (CIFL), International Research and Educational Program in Clinical and Experimental Biotechnology", Catanzaro, Italy.,Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy
| | - Alessandro Gallo
- Interuniversity Center of Phlebolymphology (CIFL), International Research and Educational Program in Clinical and Experimental Biotechnology", Catanzaro, Italy.,Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy
| | - Salvatore Fregola
- Interuniversity Center of Phlebolymphology (CIFL), International Research and Educational Program in Clinical and Experimental Biotechnology", Catanzaro, Italy.,Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy
| | - Davide Turchino
- Department of Public Health, University of Naples "Federico II", Naples, Italy
| | - Vincenzo Gasbarro
- Interuniversity Center of Phlebolymphology (CIFL), International Research and Educational Program in Clinical and Experimental Biotechnology", Catanzaro, Italy.,Department of Morphology, Surgery and Experimental Medicine, University of Ferrara, Ferrara, Italy
| | - Pasquale Mastroroberto
- Department of Experimental and Clinical Medicine, University of Catanzaro, Catanzaro, Italy
| | - Stefano de Franciscis
- Interuniversity Center of Phlebolymphology (CIFL), International Research and Educational Program in Clinical and Experimental Biotechnology", Catanzaro, Italy.,Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy
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