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Proceedings Paper

Quantitative estimation of flow rate to fill the intravascular volume (FRIV) for CT myocardial perfusion imaging
Author(s): Hao Wu; Brendan L. Eck; Jacob Levi; Anas Fares; Hiram G. Bezerra; David L. Wilson
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Paper Abstract

Model-based analysis of CT myocardial perfusion imaging (CT-MPI) constrains the form of the impulse response according to physiologic assumptions and includes parameters such as flow that can be physiologically interpreted. However, if too many parameters exist in the model, it can lead to unreliable parameter estimates. A strangeness of perfusion models is that flow does not explicitly depend on the time delay of bolus arrival, yet a stenosis creates a measurable time delay along an affected vessel. To address this, we propose a new metric, flow-rate-to-fill-theintravascular- volume (FRIV), which is the intravascular blood volume divided by (time-delay + intravascular-transittime). This index is affected both by the appearance time as well as a reduced amount of contrast agent flowing in the affected vessel tree. We evaluate FRIV for a model from the literature, adiabatic approximation of tissue homogeneity (AATH) and compare to myocardial blood flow (MBF). For evaluation, we use a physiologic simulator, digital CT-MPI phantom at different x-ray dose level, and in vivo CT-MPI data from a porcine model with and without partial occlusion of the LAD coronary artery with known pressure-wire fractional flow reserve. FRIV shows much better precision than MBF. For example, at simulated MBF=100-mL/min-100g and nominal dose (200mAs) in the digital simulator, MBF and FRIV give coefficients of variation (CV) of 0.33 and 0.09, respectively, using the AATH model. At 50% nominal dose (100mAs) results are 0.45 and 0.16, respectively. In a porcine model of coronary artery stenosis, FRIV shows higher CNR than MBF and properly detects ischemia.

Paper Details

Date Published: 28 February 2020
PDF: 7 pages
Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 113171K (28 February 2020); doi: 10.1117/12.2549838
Show Author Affiliations
Hao Wu, Case Western Reserve Univ. (United States)
Brendan L. Eck, Case Western Reserve Univ. (United States)
Jacob Levi, Case Western Reserve Univ. (United States)
Anas Fares, Harrington Heart & Vascular Institute, Univ. Hospitals of Cleveland (United States)
Hiram G. Bezerra, Harrington Heart & Vascular Institute, Univ. Hospitals of Cleveland (United States)
David L. Wilson, Case Western Reserve Univ. (United States)


Published in SPIE Proceedings Vol. 11317:
Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor S. Gimi, Editor(s)

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