4D Flow MRI for Characterization of Intracranial Vascular Networks

Aristova, Maria

doi:https://doi.org/10.21985/n2-kqq6-q091

Work

4D Flow MRI for Characterization of Intracranial Vascular Networks

Public

Download PDF

Download All Files (.zip)

4D Flow MRI is a phase-contrast magnetic resonance imaging method that enables direct measurement of velocities in three orthogonal directions throughout the heartbeat. This permits direct quantification of hemodynamic parameters, including flow, mean velocity, peak velocity, and pulsatility, for individual cerebral vessels. Despite ongoing research into neurovascular applications of 4D flow MRI, clinical applicability remains limited due to long scan times, operator-dependent and time-intensive post-processing workflow, and concomitant lack of clinically validated hemodynamic biomarkers. These issues complicate the potential clinical application of 4D flow to brain arteriovenous malformations (AVMs). AVMs are direct connections between arterial and venous circulations via a low-resistance nidus, or nest, of vessels that allow blood to bypass the capillary network of the brain. These malformations can be life-threatening, but due to their rarity and variability between individuals few quantitative hemodynamic metrics are available to inform clinical risk stratification. Current treatment planning and management do not systematically rely on quantitative hemodynamic biomarkers. The goal of this work is to identify and validate a 4D Flow MRI imaging pathway for AVM, including an optimal imaging sequence, scanning settings, and post-processing workflow. This approach relies on dual-velocity encoding 4D flow MRI, an extension of 4D flow that trades temporal resolution for increased velocity dynamic range. This approach has been validated in studies of the neurovasculature. To reduce acquisition time while preserving dynamic range, a novel, Variable Resolution Dual Venc 4D Flow MRI sequence was developed. The new sequence was tested in a purpose-built, MR-compatible and realistic experimental model of the neurovasculature. This was followed by a study in healthy volunteers. The spatial resolution and undersampling approaches that enable accurate quantification were rigorously investigated in vitro. and validated in data from healthy volunteers and AVM patients. Finally, the post-processing workflow was expanded to integrate the concept of a Flow Distribution Network Graph. This is a new paradigm for standardized data storage and analysis that preserves information concerning the connectivity of intracranial vessels. This approach has considerable potential to facilitate standardized derivation of quantitative biomarkers that adapt to highly variable individual neurovascular anatomy while preserving information concerning the connectivity of intracranial vessels. Taken together, these innovations provide a valuable roadmap for further 4D Flow studies of AVMs and other serious pathologies impacting the hemodynamics of neurovascular networks.

Creator