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

High-Speed Angiography Neurointerventional Radiology Neurovascular Disease Optical Flow X-Ray Particle Image Velocimetry

Journal

Proceedings of SPIE--the International Society for Optical Engineering
ISSN: 0277-786X
Titre abrégé: Proc SPIE Int Soc Opt Eng
Pays: United States
ID NLM: 101524122

Informations de publication

Date de publication:
Feb 2021
Historique:
entrez: 5 3 2021
pubmed: 6 3 2021
medline: 6 3 2021
Statut: ppublish

Résumé

In order to accurately quantify rapidly changing blood flow velocities, as typically seen in the neurovasculature, high temporal resolution is necessary. Current methods to extract velocity data from angiographic image sequences are generally limited to 30 fps or less. High-speed angiography (HSA) with a maximal frame rate of 1000 fps can be used to evaluate time-dependent flow details normally averaged out with lower frame rates. For new HSA image sequences, two different quantitative methods were utilized to extract high-temporal resolution velocity changes: X-Ray Particle Image Velocimetry (X-PIV) and optical flow (OF). A variety of flow conditions were examined in a range of patient-specific 3D-printed phantoms. Both pulsatile and constant flow settings were investigated. X-PIV was performed using radiopaque sub-millimeter microspheres, which were tracked throughout the image sequence to provide accurate, but limited sampling of the velocity field within the 3D-printed models. Also, an open source optical flow algorithm, OpenOpticalFlow, was used to perform velocity estimation based on the spatio-temporal intensity changes of iodinated contrast wavefronts. Periodic changes in velocity within each phantom ROI can be illustrated throughout the pulsatile cycle capture by the high-speed detector. In the constant flow sequences, changes in velocity across the phantom geometry can be seen. The ability to accurately measure detailed velocity distributions and velocity changes throughout various flow conditions at high temporal resolution enables further insight into the evaluation and treatment of neurovascular disease states.

Identifiants

pubmed: 33664537
doi: 10.1117/12.2580888
pmc: PMC7929359
mid: NIHMS1670799
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NIBIB NIH HHS
ID : R01 EB030092
Pays : United States

Références

Sci Rep. 2015 Mar 06;5:8840
pubmed: 25744850

Auteurs

A Shields (A)

Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY.

S V Setlur Nagesh (SV)

Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY.

C Ionita (C)

Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY.

D R Bednarek (DR)

Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY.

S Rudin (S)

Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY.

Classifications MeSH