Artificial Intelligence And Advanced Vascular Imaging: Emerging Tools For Precision In Peripheral Arterial Disease Management
Abstract
Background: Peripheral arterial disease (PAD) is a growing global health issue, often underdiagnosed due to limitations in conventional imaging. Artificial intelligence (AI) offers new opportunities to improve PAD diagnosis and management.
Methods: This review summarizes recent advances in vascular imaging—such as duplex ultrasound, CTA, MRA, and intravascular modalities—and the integration of AI methods like machine learning and deep learning to enhance image interpretation and clinical decision-making.
Results: AI has shown high accuracy in detecting PAD lesions, automating plaque assessment, and predicting outcomes. These tools can match or exceed expert performance, yet real-world implementation faces barriers, especially in low-resource settings.
Conclusions: AI-enhanced imaging has strong potential to transform PAD care through more accurate, personalized diagnosis and treatment. Broader adoption will require addressing technical, regulatory, and infrastructure challenges
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