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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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