Literature DB >> 35982769

2D vessel contrast dilution gradient (CDG) analysis using 1000 fps high speed angiography (HSA) for velocity distribution estimation.

Kyle A Williams1,2, Allison Shields2,3,4, S V Setlur Nagesh2,4, Daniel R Bednarek2,3,4, Stephen Rudin1,2,3,4, Ciprian N Ionita1,2,3,4.   

Abstract

Purpose: Contrast dilution gradient (CDG) analysis is a technique used to extract velocimetric 2D information from digitally subtracted angiographic (DSA) acquisitions. This information may then be used by clinicians to quantitatively assess the effects of endovascular treatment on flow conditions surrounding pathologies of interest. The method assumes negligible diffusion conditions, making 1000 fps high speed angiography (HSA), in which diffusion between 1 ms frames may be neglected, a strong candidate for velocimetric analysis using CDG. Previous studies have demonstrated the success of CDG analysis in obtaining velocimetric one-dimensional data at the arterial centerline of simple vasculature. This study seeks to resolve velocity distributions across the entire vessel using 2D-CDG analysis with HSA acquisitions. Materials and
Methods: HSA acquisitions for this study were obtained in vitro with a benchtop flow loop at 1000 fps using the XC-Actaeon (Direct Conversion Inc.) photon counting detector. 2D-CDG analyses were compared with computational fluid dynamics (CFD) via automatic co-registration of the results from each velocimetry method. This comparison was performed using mean absolute error between pixel values in each method (after temporal averaging).
Results: CDG velocity magnitudes were slightly under approximated relative to CFD results (mean velocity: 27 cm/s, mean absolute error: 4.3 cm/s) as a result of incomplete contrast filling. Relative 2D spatial velocity distributions in CDG analysis agreed well with CFD distributions qualitatively. Conclusions: CDG may be used to obtain velocity distributions in and surrounding vascular pathologies provided diffusion is negligible relative to convection in the flow, given a continuous gradient of contrast.

Entities:  

Keywords:  1000 fps; Angiography; CDG; High Speed Angiography; Velocimetry

Year:  2022        PMID: 35982769      PMCID: PMC9385177          DOI: 10.1117/12.2611790

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  13 in total

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3.  The Rheology of Blood Flow in a Branched Arterial System.

Authors:  Shewaferaw S Shibeshi; William E Collins
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4.  Evaluation of embolic deflection device using optical particle tracking.

Authors:  Ciprian N Ionita; Daniel R Bednarek; Stephen Rudin
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2013-03-29

5.  Flow modification in canine intracranial aneurysm model by an asymmetric stent: studies using digital subtraction angiography (DSA) and image-based computational fluid dynamics (CFD) analyses.

Authors:  Yiemeng Hoi; Ciprian N Ionita; Rekha V Tranquebar; Kenneth R Hoffmann; Scott H Woodward; Dale B Taulbee; Hui Meng; Stephen Rudin
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2006-03-13

6.  Evaluation of an asymmetric stent patch design for a patient specific intracranial aneurysm using Computational Fluid Dynamic (CFD) calculations in the Computed Tomography (CT) derived lumen.

Authors:  Minsuok Kim; Ciprian Ionita; Rekha Tranquebar; Kenneth R Hoffmann; Dale B Taulbee; Hui Meng; Stephen Rudin
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2006

7.  Characterization of velocity patterns produced by pulsatile and constant flows using 1000 fps high-speed angiography (HSA).

Authors:  A Shields; S V Setlur Nagesh; C Ionita; D R Bednarek; S Rudin
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2021-02-15

8.  Evaluation of methods to derive blood flow velocity from 1000 fps high-speed angiographic sequences (HSA) using optical flow (OF) and computational fluid dynamics (CFD).

Authors:  A Shields; S V Setlur Nagesh; C Ionita; D R Bednarek; S Rudin
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2021-02-15

9.  Treatment Planning for Image-Guided Neuro-Vascular Interventions Using Patient-Specific 3D Printed Phantoms.

Authors:  M Russ; R O'Hara; S V Setlur Nagesh; M Mokin; C Jimenez; A Siddiqui; D Bednarek; S Rudin; C Ionita
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2015-03-19

10.  Challenges in hemodynamics assessment in complex neurovascular geometries using computational fluid dynamics and benchtop flow simulation in 3D printed patient specific phantoms.

Authors:  Eric Paccione; Ciprian N Ionita
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2021-02-15
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