Published in

Surgical Technology Online, 2021

DOI: 10.52198/21.sti.38.cv1410

Links

Tools

Export citation

Search in Google Scholar

Blood Flow Quantification in Peripheral Arterial Disease: Emerging Diagnostic Techniques in Vascular Surgery

This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

Full text: Unavailable

Question mark in circle
Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

The assessment of local blood flow patterns in patients with peripheral arterial disease is clinically relevant, since these patterns are related to atherosclerotic disease progression and loss of patency in stents placed in peripheral arteries, through mechanisms such as recirculating flow and low wall shear stress (WSS). However, imaging of vascular flow in these patients is technically challenging due to the often complex flow patterns that occur near atherosclerotic lesions. While several flow quantification techniques have been developed that could improve the outcomes of vascular interventions, accurate 2D or 3D blood flow quantification is not yet used in clinical practice. This article provides an overview of several important topics that concern the quantification of blood flow in patients with peripheral arterial disease. The hemodynamic mechanisms involved in the development of atherosclerosis and the current clinical practice in the diagnosis of this disease are discussed, showing the unmet need for improved and validated flow quantification techniques in daily clinical practice. This discussion is followed by a showcase of state-of-the-art blood flow quantification techniques and how these could be used before, during and after treatment of stenotic lesions to improve clinical outcomes. These techniques include novel ultrasound-based methods, Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD). The last section discusses future perspectives, with advanced (hybrid) imaging techniques and artificial intelligence, including the implementation of these techniques in clinical practice.