MR perfusion studies with T1-weighted echo planar imaging

High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results

This report evaluates several methods to map relative cerebral blood flow (rCBF) by applying both parametric and nonparametric techniques to deconvolve high resolution dynamic MRI measurements of paramagnetic bolus passages with noninvasively determined arterial inputs. We found a nonparametric (singular value decomposition (SVD)) deconvolution technique produced the most robust results, giving mean gray:white flow ratio of 2.7 +/- 0.5 (SEM) in six normal volunteers, in excellent agreement with recent PET literature values for age-matched subjects. Similar results were obtained by using a model-dependent approach that assumes an exponential residue function, but not for a Gaussian-shaped residue function or for either Fourier or regularization-based model-independent approaches. Pilot studies of our CBF mapping techniques in patients with tumor, stroke, and migraine aura demonstrated that these techniques can be readily used on data routinely acquired by using current echo planar imaging technology. By using these techniques, the authors visualized important regional hemodynamic changes not detectable with rCBV mapping algorithms.

Reduced transit-time sensitivity in noninvasive magnetic resonance imaging of human cerebral blood flow

Herein, we present a theoretical framework and experimental methods to more accurately account for transit effects in quantitative human perfusion imaging using endogenous magnetic resonance imaging (MRI) contrast. The theoretical transit time sensitivities of both continuous and pulsed inversion spin tagging experiments are demonstrated. We propose introducing a delay following continuous labeling, and demonstrate theoretically that introduction of a delay dramatically reduces the transit time sensitivity of perfusion imaging. The effects of magnetization transfer saturation on this modified continuous labeling experiment are also derived, and the assumption that the perfusion signal resides entirely within tissue rather than the arterial microvasculature is examined. We present results demonstrating the implementation of the continuous tagging experiment with delay on an echoplanar scanner for measuring cerebral blood flow (CBF) in normal volunteers. By varying the delay, we estimate transit times in the arterial system, values that are necessary for assessing the accuracy of our quantification. The effect of uncertainties in the transit time from the tagging plane to the arterial microvasculature and the transit time to the tissue itself on the accuracy of perfusion quantification is discussed and found to be small in gray matter but still potentially significant in white matter. A novel method for measuring T1, which is fast, insensitive to contamination by cerebrospinal fluid, and compatible with the application of magnetization transfer saturation, is also presented. The methods are combined to produce quantitative maps of resting and hypercarbic CBF.

Perfusion imaging of the human brain at 1.5 T using a single-shot EPI spin tagging approach

Single-shot echo planar imaging (EPI) techniques have been applied, in conjunction with arterial spin tagging approaches, to obtain images of cerebral blood flow in a single axial slice in the human brain. Serial studies demonstrate that cerebral blood flow images acquired in 8 min are reproducible, with a statistical precision of approximately +/-10 cc/100 g/min. The average value of cerebral blood flow in the slice is 51 +/- 11 cc/100 g/min for six normal subjects. The cerebral blood flow images contain two types of artifact, probably due to arterial and venous blood volume contributions, which must be overcome before the arterial spin tagging approach can be used for routine clinical studies.

A model for quantification of perfusion in pulsed labelling techniques

A model for quantification of perfusion in pulsed labelling techniques is described, based on solving the modified Bloch equation including the effects of flow. The model is designed to fit experimental data acquired in two separate measurements (inversion and control, or selective and non-selective inversions) for different inversion times using a biexponential. Although the signal contrast is 50% less than the continuous labelling technique, it seems more appropriate for human studies because of its lower power deposition, shorter transit time and the use of an interleaved acquisition. The importance is shown of including in the model the difference in relaxation time between blood and tissue. Neglecting this difference can lead to an overestimation of flow, which can be as big as 100% in white matter and 20% in grey matter.