Imaging Characterisation of Peripheral Artery Disease: A Scoping Review on Current Classifications and New Insights Brought by Artificial Intelligence

IF 1.4 Q3 PERIPHERAL VASCULAR DISEASE

EJVES Vascular Forum Pub Date : 2025-01-01 DOI:10.1016/j.ejvsvf.2025.06.003

Fabien Lareyre , Lisa Guzzi , Bahaa Nasr , Ahmed Alouane , Sébastien Goffart , Andréa Chierici , Hervé Delingette , Juliette Raffort

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Abstract

Objectives

Several scan and imaging classifications have been described for the management of patients with peripheral artery disease (PAD). In parallel, artificial intelligence (AI) has brought new insights in vascular imaging analysis. This scoping review aimed to summarise imaging classification for PAD and to discuss how AI could be used to enhance these systems.

Methods

Medline was searched for relevant studies that addressed imaging classification and use of AI in PAD vascular imaging. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) protocol was followed.

Results

Thirty four articles were included. This paper provides an overview and discusses the advantages and limits of current imaging classifications used to characterise atherosclerotic lesions as well as calcifications in patients with PAD. AI offers new opportunities to enhance automatic detection and classification of PAD lesions, with potentially new techniques that could be used to assess vascular calcification and identify radiomic patterns.

Conclusion

AI has brought new opportunities to improve imaging software to facilitate robust and reproducible analysis of lower limb arterial lesions. In the future, such applications may contribute to improved clinical workflow and help decision making.

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外周动脉疾病的影像学表征：对当前分类和人工智能带来的新见解的综述

目的介绍了外周动脉疾病（PAD）患者的几种扫描和影像学分类。与此同时，人工智能（AI）为血管成像分析带来了新的见解。本综述旨在总结PAD的成像分类，并讨论如何使用人工智能来增强这些系统。方法检索medline上有关图像分类和人工智能在PAD血管成像中的应用的相关研究。遵循系统评价和荟萃分析扩展范围评价的首选报告项目（PRISMA-ScR）协议。结果共纳入34篇文献。本文概述并讨论了目前用于PAD患者动脉粥样硬化病变和钙化特征的影像学分类的优点和局限性。人工智能为增强PAD病变的自动检测和分类提供了新的机会，其潜在的新技术可用于评估血管钙化和识别放射学模式。结论人工智能为改进成像软件提供了新的机会，有助于对下肢动脉病变进行稳健、可重复的分析。在未来，这样的应用可能有助于改善临床工作流程和帮助决策。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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