Integrating speckle tracking into routine carotid artery ultrasound protocols provides a reliable, angle-independent measurement of vascular stiffness to better assess cardiovascular risk.
Speckle tracking ultrasound for carotid artery stiffness assessment
Integrating speckle tracking into carotid artery duplex protocols offers a comprehensive method to measure vascular stiffness, potentially improving cardiovascular risk assessment compared to traditional pulse wave velocity.
Historically, pulse wave velocity (PWV) has been used to measure vascular stiffness, but is limited in its utility when certain vascular disease states are present, such as aneurysm or iliac stenosis. PWV can therefore only provide reliable assessment of global vascular stiffness in limited vascular pathology. Speckle tracking is a method of post-hoc ultrasound image analysis that can measure vascular stiffness in a more comprehensive manner. Evidence from in vitro as well as in vivo studies has validated these techniques in the assessment of strain, distensibility, modulus, and stiffness index (β) in the carotid arterial system. Unfortunately, despite the well-established correlation between vascular stiffness and cardiovascular morbidity and mortality, standard vascular laboratory ultrasound protocols do not include stiffness assessment. Herein, we present evidence in favor of integrating speckle tracking into carotid artery duplex protocols to measure vascular stiffness that can be utilized in medical management to modulate cardiovascular risk.
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J Gedney
Medical University of South Carolina
Jean Marie Ruddy
Vascular / Pulmonary Vascular
Cardiology & Vascular Research
Medical University of South Carolina
Pulmonary Vascular Research Institute
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Gedney et al. (Thu,) conducted a review in Cardiovascular risk. Speckle tracking ultrasound was evaluated. Integrating speckle tracking into routine carotid artery ultrasound protocols provides a reliable, angle-independent measurement of vascular stiffness to better assess cardiovascular risk.
synapsesocial.com/papers/6a11c6a037ecc83ca3fd3407 — DOI: https://doi.org/10.33425/2639-8486.1172
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