MR Vascular Fingerprinting with 3D realistic blood vessel structures and machine learning to assess oxygenation changes in human volunteers

The MR vascular fingerprinting (MRvF) approach extends the concept of MR fingerprinting to the study of microvascular properties and functions. Encouraging results have been obtained in healthy human volunteers as well as in stroke and tumor models in rats. However, it has been suggested that the method has a low sensitivity to blood oxygenation measurements. We improved the MRvF approach by using simulations with 3D realistic blood vessels from animal microscopy, new fingerprint-pattern organization and machine learning tools. The method was tested in retrospective data acquired in healthy-human volunteers while breathing different gas mixtures (Hyperoxia (100%O2), Normoxia (21%O2), hypoxia (14%O2)).