Title
Model-based blood flow quantification from DSA: quantitative evaluation on patient data and comparison with TCCD
Abstract
Purpose: To support intra-interventional decisions on diagnosis and treatment of cerebrovascular diseases, a method providing quantitative information about the blood flow in the vascular system is proposed. Method: This method combines rotational angiography to extract the 3D vessel geometry and digital subtraction angiography (DSA) to obtain the flow observations. A physical model of blood flow and contrast agent transport is used to predict the propagation of the contrast agent through the vascular system. In an iterative approach, the model parameters, including the volumetric blood flow rate, are adapted until the prediction matches the observations from the DSA. The flow estimation method was applied to patient data: For 24 patients, the volumetric blood flow rate was determined from angiographic images and for 17 patients, results were compared with transcranial color coded Doppler (TCCD) measurements. Results: The agreement of the x-ray based flow estimates with TCCD was reasonable (bias Delta(M) = 3%, correlation rho = 0.76) and reproducibility was clearly better than the reproducibility of the acquired TCCD measurements. Conclusion: Overall we conclude that it is feasible to model the contrast agent transport in patients and to utilize the flow model to quantify their blood flow with angiographic means.
Year
DOI
Venue
2012
10.1117/12.911095
Proceedings of SPIE
Keywords
Field
DocType
doppler effect
Biomedical engineering,Rotational angiography,Reproducibility,Artificial intelligence,Doppler effect,Angiography,Computer vision,Digital subtraction angiography,Blood flow,Data flow model,Flow estimation,Medical physics,Physics
Conference
Volume
ISSN
Citations 
8314
0277-786X
0
PageRank 
References 
Authors
0.34
0
10
Name
Order
Citations
PageRank
irina waechterstehle100.34
A Groth2588.80
Tom Bruijns311.30
Olivier Brina474.42
daniel a ruefenacht500.34
zsolt kulcsar600.68
v mendespereira700.34
fabienne perren841.43
David J. Hawkes94262470.26
Jürgen Weese1077492.69