Evidence map›Paper›PMID 35982769›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering

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

Kyle A Williams, Allison Shields, S V Setlur Nagesh, Daniel R Bednarek, Stephen Rudin, Ciprian N Ionita

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Kyle A WilliamsDepartment of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228.
Allison ShieldsCanon Stroke and Vascular Research Center, Buffalo, NY 14208.
S V Setlur NageshCanon Stroke and Vascular Research Center, Buffalo, NY 14208.
Daniel R BednarekCanon Stroke and Vascular Research Center, Buffalo, NY 14208.
Stephen RudinDepartment of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228.
Ciprian N IonitaDepartment of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228.

Funding

High Speed Angiography at 1000 frames per secondR01EB030092 · NIBIB · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI RUDIN, STEPHEN · 2020 to 2023
$2.6M
NIBIB NIH HHS R01 EB030092
6 · The paper itself

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.

Indexed as

1000 fpsAngiographyCDGHigh Speed AngiographyVelocimetry

Identifiers

PMID35982769
PMCPMC9385177

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.