Quantification of flow rates in short vessel segments from arterial spin labeling dynamic angiography
Flora A. Kennedy McConnell 1 , Thomas W. Okell 2 , Michael A. Chappell 1 , and Stephen J. Payne 1
Institute of Biomedical Engineering,
Department of Engineering Science, University of Oxford,
Oxford, Oxfordshire, United Kingdom,
Centre, Nuffield Department of Clinical Neurosciences,
University of Oxford, Oxford, Oxfordshire, United
Conventional angiography techniques only provide
qualitative information about cerebrovascular disease
and collateral blood flow. Here a novel mathematical
model for the quantification of blood flow rates from
dynamic MR angiography data is proposed. Fitting the
model to vessel-encoded pseudo-continuous arterial spin
labeled signals from a flow phantom allowed accurate
estimation of water flow rates in short vessel segments.
Applying the method to healthy volunteer data produced
brain-feeding artery flow rate estimates within
physiological norms. Also demonstrated was the potential
of the technique to identify and estimate flow through
often unseen, collateral vessels by fitting the model to
signals detected downstream.
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