"MR Fingerprinting for Imaging Brain Hemodynamics and Oxygenation".
Authors
Affiliations (2)
Affiliations (2)
- Université Grenoble Alpes, INSERM U1216, Grenoble Institut Neurosciences, GIN, Grenoble, France.
- Université Grenoble Alpes, NSERM US17, CNRS UAR3552, CHU Grenoble Alpes, IRMaGe, Grenoble, France.
Abstract
Over the past decade, several studies have explored the potential of magnetic resonance fingerprinting (MRF) for the quantification of brain hemodynamics, oxygenation, and perfusion. Recent advances in simulation models and reconstruction frameworks have also significantly enhanced the accuracy of vascular parameter estimation. This review provides an overview of key vascular MRF studies, emphasizing advancements in geometrical models for vascular simulations, novel sequences, and state-of-the-art reconstruction techniques incorporating machine learning and deep learning algorithms. Both pre-clinical and clinical applications are discussed. Based on these findings, we outline future directions and development areas that need to be addressed to facilitate their clinical translation. EVIDENCE LEVEL: N/A. TECHNICAL EFFICACY: Stage 1.