Oxford University Innovation Limited

Michael A Chappell

Thomas Okell

Peter Jezzard

James R Larkin

Manon Simard

Stephen J Payne

Flora A Kennedy McConnell

Mark Woolrich

Martin Craig

The present disclosure is directed to systems and methods of multiphase pseudo-continuous arterial spin labeling.

Methods and systems of multiphase arterial spin labeling

Disclosed are various embodiments for estimating the flow of blood through a blood vessel in a region of interest. Passage of a bolus of fluid through an imaged blood vessel over a period of time is tracked by a computing device. The computing device fits the tracked passage of the bolus of fluid to a modeled passage of the bolus of fluid. The computing device then estimates a volume of blood flow through the imaged blood vessel based at least in part on a fit of the tracked passage of the bolus of fluid to the modeled passage of the bolus of fluid.

Estimation of blood flow rates

Arterial spin labelling (ASL) MRI offers a non-invasive means to create blood-borne contrast in vivo for dynamic angiographic imaging. By spatial modulation of the ASL process it is possible to uniquely label individual arteries over a series of measurements, allowing each to be separately identified in the resulting images. This separation requires appropriate analysis for which a general framework has previously been proposed. Here the general framework is modified for fast analysis of non-invasive imaging of blood flow using vessel encoded arterial spin labelling (VE-ASL). This specifically addresses the issues of computational speed of the analysis and the robustness required to deal with real patient data. The modification applies various approaches for estimation of one or more parameters that change the way a vessel, for example an artery, is encoded to provide the fast analysis.

Fast analysis method for non-invasive imaging of blood flow using vessel-encoded arterial spin labelling

Systems and methods are disclosed for quantifying absolute blood volume flow rates by fitting a kinetic model incorporating blood volume, bolus dispersion and signal attenuation to dynamic angiographic data. A self-calibration method is described for both 2D and 3D data sets to convert the relative blood volume parameter into absolute units. The parameter values are then used to simulate the signal arising from a very short bolus, in the absence of signal attenuation, which can be readily encompassed within a vessel mask of interest. The volume flow rate can then be determined by calculating the blood volume within the vessel mask and dividing by the simulated bolus duration. This method is exemplified using non-contrast magnetic resonance imaging data from a flow phantom and the cerebral arteries of healthy volunteers and a patient with Moya-Moya disease acquired using a 2D vessel-encoded pseudo-continuous arterial spin labeling pulse sequence. This allows flow quantification in downstream vessels from each brain-feeding artery separately. The systems and methods can be of use in patients with a variety of cerebrovascular diseases, such as the assessment of collateral flow in patients with steno-occlusive disease or the evaluation of arteriovenous malformations.

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Oxford, United Kingdom

Michael A Chappell