Share Email Print
cover

Proceedings Paper

Comparison of benchtop pressure gradient measurements in 3D printed patient specific cardiac phantoms with CT-FFR and computational fluid dynamic simulations
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Purpose: Various CT-FFR methods are being proposed as a non-invasive method to estimate cardiac disease severity. 3D printed patient specific cardiovascular models with high geometric accuracy can be used to simulate blood flow conditions and perform precise and repeatable benchtop flow experiments for validation of such methods. Materials and Methods: Twelve patient-specific 3D printed cardiac phantoms were created from CT Angiography (CTA) scans using a compliant 3D printing material. Pressure sensors were connected to the aortic root and distal ends of the three main coronary arteries to measure benchtop pressure gradients for each stenosed vessel. The patient geometries were used in Canon Medical Systems 1D fluid dynamics algorithm to calculate the CT- FFR. In addition, a 3D computational fluid dynamics simulation was done using ANSYS to estimate pressure gradients across the coronary arteries. Experimental data and 1D and 3D flow simulations were compared to the standard catheter lab FFR measurement (Invasive-FFR). Results: The average percent difference in Benchtop FFR/Invasive FFR, CT-FFR/Invasive FFR, and CFDFFR/Invasive FFR was 0.05, 0.06, and 0.07 respectively. The average time it took for the CT-FFR simulation was ~35 minutes and it took ~15 hours for the CFD-FFR simulation but can vary based on the number of iterations the user defines the software to run. Conclusions: Benchtop FFR proved to be highly accurate when compared to both 1D and 3D CFD software and therefore, 3D printing of patient specific coronary phantoms is a quality tool for CT-FFR software validation.

Paper Details

Date Published: 15 March 2019
PDF: 13 pages
Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109531P (15 March 2019); doi: 10.1117/12.2512118
Show Author Affiliations
Kelsey N. Sommer, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. Univ. at Buffalo (United States)
Lauren Shepard, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. Univ. at Buffalo (United States)
Vijay Iyer M.D., Canon Stroke and Vascular Research Ctr. Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)
Erin Angel, Canon Stroke and Vascular Research Ctr. Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)
Michael F. Wilson, Canon Stroke and Vascular Research Ctr. Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)
Frank J. Rybicki, The Ottawa Hospital Research Institute and the Department of Radiology, Univ. of Ottawa (Canada)
Dimitrios Mitsouras, Brigham and Women’s Hospital Dept of Radiology (United States)
Kanako Kunishima Kumamaru, Juntendo Univ. Department of Radiology (Japan)
Stephen Rudin, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. Univ. at Buffalo (United States)
Ciprian N. Ionita, Univ. at Buffalo (United States)
Canon Stroke and Vascular Research Ctr. Univ. at Buffalo (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)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray