A fast analysis method for non-invasive imaging of blood flow in individual cerebral arteries using vessel-encoded arterial spin labelling angiography.
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 angiographic images. This separation requires appropriate analysis for which a general Bayesian framework has previously been proposed. Here this framework is adapted for clinical dynamic angiographic imaging. This specifically addresses the issues of computational speed of the algorithm and the robustness required to deal with real patient data. An algorithm is proposed that can incorporate planning information about the arteries being imaged whilst adapting for subsequent patient movement. A fast maximum a posteriori solution is adopted and shown to be only marginally less accurate than Monte Carlo sampling under simulation. The final algorithm is demonstrated on in vivo data with analysis on a time scale of the order of 10min, from both a healthy control and a patient with a vertebro-basilar occlusion.
Institute of Biomedical Engineering, University of Oxford, Old Road Campus, Headington, Oxford OX3 7DQ, UK. michael.chappell@eng.ox.ac.uk
Michael A
MA
Chappell
Thomas W
TW
Okell
Stephen J
SJ
Payne
Peter
P
Jezzard
Mark W
MW
Woolrich
D000465:Algorithms; D001783:Blood Flow Velocity; D002536:Cerebral Arteries / Q000503:physiopathology*; D002560:Cerebrovascular Circulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013113:Spin Labels; D014715:Vertebrobasilar Insufficiency / Q000175:diagnosis* / Q000503:physiopathology*
D013113:Spin Labels