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Proceedings Paper

Use of 3D-printed patient-specific neurovascular phantoms to investigate the correlation between disease severity and quantitative angiography results
Author(s): Lauren M. Shepard; Kelsey N. Sommer; Eric Paccione; Maxim Mokin; Adnan H. Siddiqui; Kenneth V. Snyder; Elad I. Levy; Jason M. Davies; Stephen Rudin; Ciprian N. Ionita
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Paper Abstract

Purpose: 3D printed Patient-Specific Neurovascular Phantoms (3DP-PSNP) containing significant portions of the neurovasculature can be used to develop and test new diagnostic tools. The purpose of this research is to assess the use of 3DP-PSNP to study the correlation between Angiographic Parametric Imaging (API) features and the severity of carotid artery disease. Materials and Methods: We developed 3DP-PSNP for twenty patients with carotid atherosclerosis and performed two studies. In the first study, we used three phantoms with complete Circle of Willis (COW) with none, moderate and severe stenosis respectively. In the second experiment, all phantoms regardless of the COW structure were used. 3DP-PSNPs were connected in a simulated physiological pulsatile flow loop and Digital Subtractive Angiography (DSA) was performed by injecting 10 ml of contrast at 10 mL/s. An API software calculated imaging biomarkers: time-to-peak TTP, mean transit time MTT, time to arrival TTA, peak height PH, and area under the curve AUC for both carotids. Results: For none, moderate, and severe stenosis respectively, absolute mean percent differences between diseased vs. contralateral carotids were: 1.9%, 8.1%, 32.3% TTP; 6.8%, 7.5%, 41.0% TTA; 13.2%, 12.4%, 6.4% MTT; 8.7%, 11.3%, 97.6% PH; and 10.3%, 22.6%, 100% AUC. Injection parameters did not cause significant change to the difference between diseased and contralateral carotids. The second experiment showed strong correlation between the TTA and location of the stenosis, regardless of COW configuration. Conclusions: Overall, API was assessed in 3DP-PSNPs and shown to have increasing differences between diseased and contralateral carotid arteries with increasing severity.

Paper Details

Date Published: 2 March 2020
PDF: 9 pages
Proc. SPIE 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, 1131806 (2 March 2020); doi: 10.1117/12.2548213
Show Author Affiliations
Lauren M. Shepard, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. (United States)
Kelsey N. Sommer, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. (United States)
Eric Paccione, Univ. at Buffalo (United States)
Maxim Mokin, Univ. of South Florida (United States)
Adnan H. Siddiqui, 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, 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)
Stephen Rudin, 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. 11318:
Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications
Po-Hao Chen; Thomas M. Deserno, Editor(s)

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