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A Technique for Intra-procedural Blood Velocity Quantitation Using Time-resolved 2D Digital Subtraction Angiography

Overview
Journal CVIR Endovasc
Date 2021 Jan 7
PMID 33411087
Citations 5
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Abstract

Background: 2D digital subtraction angiography (DSA) is utilized qualitatively to assess blood velocity changes that occur during arterial interventions. Quantitative angiographic metrics, such as blood velocity, could be used to standardize endpoints during angiographic interventions.

Purpose: To assess the accuracy and precision of a quantitative 2D DSA (qDSA) technique and to determine its feasibility for in vivo measurements of blood velocity.

Materials And Methods: A quantitative DSA technique was developed to calculate intra-procedural blood velocity. In vitro validation was performed by comparing velocities from the qDSA method and an ultrasonic flow probe in a bifurcation phantom. Parameters of interest included baseline flow rate, contrast injection rate, projection angle, and magnification. In vivo qDSA analysis was completed in five different branches of the abdominal aorta in two 50 kg swine and compared to 4D Flow MRI. Linear regression, Bland-Altman, Pearson's correlation coefficient and chi squared tests were used to assess the accuracy and precision of the technique.

Results: In vitro validation showed strong correlation between qDSA and flow probe velocities over a range of contrast injection and baseline flow rates (slope = 1.012, 95% CI [0.989,1.035], Pearson's r = 0.996, p < .0001). The application of projection angle and magnification corrections decreased variance to less than 5% the average baseline velocity (p = 0.999 and p = 0.956, respectively). In vivo validation showed strong correlation with a small bias between qDSA and 4D Flow MRI velocities for all five abdominopelvic arterial vessels of interest (slope = 1.01, Pearson's r = 0.880, p = <.01, Bias = 0.117 cm/s).

Conclusion: The proposed method allows for accurate and precise calculation of blood velocities, in near real-time, from time resolved 2D DSAs.

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References
1.
Ionita C, Garcia V, Bednarek D, Snyder K, Siddiqui A, Levy E . Effect of injection technique on temporal parametric imaging derived from digital subtraction angiography in patient specific phantoms. Proc SPIE Int Soc Opt Eng. 2014; 9038:90380L. PMC: 4187403. DOI: 10.1117/12.2041347. View

2.
Lee C, Nagy P, Weaver S, Newman-Toker D . Cognitive and system factors contributing to diagnostic errors in radiology. AJR Am J Roentgenol. 2013; 201(3):611-7. DOI: 10.2214/AJR.12.10375. View

3.
Lin E, Lee R, Guo W, Wu F, Gehrisch S, Kowarschik M . Three-Dimensional Quantitative Color-Coding Analysis of Hepatic Arterial Flow Change during Chemoembolization of Hepatocellular Carcinoma. J Vasc Interv Radiol. 2018; 29(10):1362-1368. DOI: 10.1016/j.jvir.2018.04.012. View

4.
Wang D, Jin B, Lewandowski R, Ryu R, Sato K, Mulcahy M . Quantitative 4D transcatheter intraarterial perfusion MRI for monitoring chemoembolization of hepatocellular carcinoma. J Magn Reson Imaging. 2010; 31(5):1106-16. PMC: 2885358. DOI: 10.1002/jmri.22155. View

5.
Johnson K, Markl M . Improved SNR in phase contrast velocimetry with five-point balanced flow encoding. Magn Reson Med. 2010; 63(2):349-55. PMC: 3418793. DOI: 10.1002/mrm.22202. View