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Initial assessment of neuro pressure gradients in carotid stenosis using 3D printed patient-specific phantoms
Author(s): Lauren M. Shepard; Adnan H. Siddiqui M.D.; Kenneth V. Snyder; Elad I. Levy M.D.; Jason M. Davies; Ciprian N. Ionita
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Paper Abstract

Purpose: Investigate the use of neuro pressure gradients (NPG) to assess the impact of carotid artery disease on distal flow conditions using 3D printed patient-specific phantoms. Materials and Methods: Seven patients (five various degrees of carotid artery disease, two healthy) underwent 320- detector row CT angiography (Aquilion ONE, Canon Medical Systems). The internal carotid, vertebral, basilar arteries, as well as the Circle of Willis, middle cerebral arteries (MCA), anterior cerebral arteries (ACA), and posterior cerebral arteries (PCA) were segmented using a Vitrea workstation (Vital Images). The patient anatomy was manipulated in Autodesk Meshmixer and each phantom was 3D printed using material that simulates the compliance of vasculature, Tango+, using a Stratasys Eden260V printer. Phantoms were connected in a pulsatile flow loop with physiological flow rates. Distal resistance was manipulated to simulate physiological conditions. The pressure was measured in the proximal internal carotid arteries and the distal right and left MCA to calculate the neuro pressure gradient (NPG). Results: All seven phantoms were successfully tested in the simulated physiological flow loop. Neuro pressure gradients (NPG) were measured in each phantom and demonstrated a dependence on percent stenosis and Circle of Willis anatomy. NPG ranged -0.67 to 1.10 mmHg/cm and moderately correlated with the stenosis grade and location, and the Circle of Willis configuration. Conclusions: We have successfully assessed the feasibility of measuring NPG in 3D printed patient-specific neurovasculature phantoms with carotid artery disease.

Paper Details

Date Published: 15 March 2019
PDF: 11 pages
Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1095314 (15 March 2019); doi: 10.1117/12.2510279
Show Author Affiliations
Lauren M. Shepard, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. (United States)
Adnan H. Siddiqui M.D., Canon Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)
Kenneth V. Snyder, Canon Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)
Elad I. Levy M.D., Canon Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)
Jason M. Davies, Canon Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)
Ciprian N. Ionita, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. (United States)


Published in SPIE Proceedings Vol. 10953:
Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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