Automated Spatial Vessel Wall Inhomogeneity Detection in Phantoms and in-Vivo Using Adaptive Pulse Wave Imaging

PROJECT TITLE :

Adaptive Pulse Wave Imaging Automated Spatial Vessel Wall Inhomogeneity Detection in Phantoms and in-Vivo

ABSTRACT:

Imaging the mechanical characteristics of the artery wall may aid in the diagnosis of vascular disease. As a metric of arterial stiffness, pulse wave velocity (PWV) has been associated to cardiovascular mortality. Imaging the propagation of pulse waves with great spatial and temporal resolution is possible with pulse wave imaging (PWI). Here, we provide an adaptive PWI technique that automatically partitions heterogeneous vessels into segments characterised by the most homogenous pulse wave propagation, resulting in more accurate PWV estimations. A silicone phantom with a soft-stiff interface was used to test this method. In the stiff-to-soft and soft-to-stiff pulse wave transmission directions, the interface's detection error was 4.67 0.73 mm and 3.64 0.14 mm, respectively. Using this method, 11 mice had their aortas monitored in vivo for the advancement of atherosclerosis. A high-fat diet resulted in an increase in the PWV of 3.17 m/sec compared to 2.55 m/sec at the 10-week mark and 3.76 m/sec at the 20-week mark (3.76 m/sec vs. 2.55 m/sec). High-fat diets resulted in an increasing number of segments in the imaging aortas, which indicated an increase in the artery wall's inhomogeneity. Adaptive PWI was also evaluated in aneurysmal mice aortas in vivo to see how well it performed. A mean error of 0.680.44 mm was found in the detection of aneurysmal borders. At long last, preliminary success was demonstrated in vivo in the carotid arteries of healthy and atherosclerotic humans (n = 3 in each case). As a result, adaptive PWI was successful in detecting stiffness inhomogeneity at its early onset and tracking atherosclerosis progression while it was occurring in the body.

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