MR vascular fingerprinting: A new approach to compute cerebral blood volume, mean vessel radius, and oxygenation maps in the human brain

Abstract

In the present study, we describe a fingerprinting approach to analyze the time evolution of the MR signal and retrieve quantitative information about the microvascular network. We used a Gradient Echo Sampling of the Free Induction Decay and Spin Echo (GESFIDE) sequence and defined a fingerprint as the ratio of signals acquired pre and post injection of an iron based contrast agent. We then simulated the same experiment with an advanced numerical tool that takes a virtual voxel containing blood vessels as input, then computes microscopic magnetic fields and water diffusion effects, and eventually derives the expected MR signal evolution. The parameters inputs of the simulations (cerebral blood volume [CBV], mean vessel radius [R], and blood oxygen saturation [SO2]) were varied to obtain a dictionary of all possible signal evolutions. The best fit between the observed fingerprint and the dictionary was then determined using least square minimization. This approach was evaluated in 5 normal subjects and the results were compared to those obtained using more conventional MR methods, steady-state contrast imaging for CBV and R and a global measure of oxygenation obtained from the superior sagittal sinus for SO2. The fingerprinting method enabled the creation of high-resolution parametric maps of the microvascular network showing expected contrast and fine details. Numerical values in gray matter (CBV=3.1±0.7%, R=12.6±2.4µm, SO2=59.5±4.7%) are consistent with literature reports and correlated with conventional MR approaches. SO2 values in white matter (53.0±4.0%) were slightly lower than expected. Numerous improvements can easily be made and the method should be useful to study brain pathologies.

MR Fingerprinting for Rapid Quantitative Abdominal Imaging

“…B 1 inhomogeneity is a well-known problem in 3.0 T imaging and is thus expected to affect the accuracy of relaxation property mapping (15,16,19). While it is less of an issue for MR fingerprinting studies with brain imaging at 1.5 T or 3.0 T, it is well known that large variation in B 1 is expected with abdominal imaging at 3.0 T because of the successfully used to obtain dynamic susceptibility contrast-enhanced perfusion images in the brain (26). Preliminary studies for obtaining diffusion and perfusion measurements simultaneously with relaxation property measurements have been reported (27,28).…”

MR Vascular Fingerprinting in Stroke and Brain Tumors Models

“…Such a fingerprint is sensitive to magnetic inhomogeneity-based dephasing but not to macroscopic B0, B1, and microscopic T 2 effects10. Because of the low signal-to-noise ratio (SNR), the last 8 echoes of the GESFIDE sequences were removed before computing the fingerprints.…”

“…Finding the closest match to the fingerprint/dictionary in terms of Euclidian distance allows a direct link between parameters entries of the simulations (in case of Ma et al 9, T 1 , T 2 , proton density, frequency shift) and the imaged voxel itself. We hypothesized in a recent study10 that similar tools could be used to analyze variations in the natural temporal evolution of the MR signal in tissue, resulting in quantitative information about the microvascular network at a sub-voxel imaging scale. In our first implementation, we proposed to use the MR signal decay in a spin echo experiment acquired before and after injection of contrast agent as a ‘vascular fingerprint’.…”

Quantitative β mapping for calibrated fMRI

“…All correlation values (r 2 ) were higher than 0.92, reflecting strong linear relationships. Since Feraheme has been used in humans (Christen et al, 2013; Christen et al, 2014; D'Arceuil et al, 2013), we chose this contrast agent to conduct detailed analysis of β across regions and states.…”

“…Additionally, we showed consistent results between Molday and Feraheme. Whereas Molday is used widely in animal studies, Feraheme has recently been applied in human fMRI studies as an efficient contrast agent for measuring CBV-weighted signal (Christen et al, 2013; Christen et al, 2014; D'Arceuil et al, 2013). Since the relationship between β and brain region or activity level was not hypothesized or tested previously, here we measured β values across different brain regions (in white and gray matter) and different brain states.…”