Arterial spin labeling for quantitative functional MRI

Quantification of errors in cerebral blood flow measurements due to dispersion in arterial spin labelling

The accuracy of cerebral blood flow (CBF) measurements using arterial spin labelling (ASL) is particularly affected by dispersion. In spite of this, however, the current recommended implementation of ASL - the white paper (WP) - does not account for dispersion, which leads to the introduction of errors in CBF. In fact, these errors are also likely to vary with the arterial transit time (ATT), which is the transport time from the labelling region to the tissue. Using pseudo-continuous ASL, this study assesses a variety of dispersion models in comparison with the WP quantification formula, enabling the errors introduced by the WP to be quantified. In particular, this study shows that the WP quantification only holds for ATTs below 1.25s - and that this ATT value reduces further as dispersion occurs. The levels of dispersion beyond which the WP introduces significant error are also quantified, such that provided the dispersion levels fall below the thresholds determined in this study, the WP can still measure CBF with reasonable accuracy.

Cerebral blood volume changes during brain activation

Cerebral blood volume (CBV) changes significantly with brain activation, whether measured using positron emission tomography, functional magnetic resonance imaging (fMRI), or optical microscopy. If cerebral vessels are considered to be impermeable, the contents of the skull incompressible, and the skull itself inextensible, task- and hypercapnia-related changes of CBV could produce intolerable changes of intracranial pressure. Because it is becoming clear that CBV may be useful as a well-localized marker of neural activity changes, a resolution of this apparent paradox is needed. We have explored the idea that much of the change in CBV is facilitated by exchange of water between capillaries and surrounding tissue. To this end, we developed a novel hemodynamic boundary-value model and found approximate solutions using a numerical algorithm. We also constructed a macroscopic experimental model of a single capillary to provide biophysical insight. Both experiment and theory model capillary membranes as elastic and permeable. For a realistic change of input pressure, a relative pipe volume change of 21±5% was observed when using the experimental setup, compared with the value of approximately 17±1% when this quantity was calculated from the mathematical model. Volume, axial flow, and pressure changes are in the expected range.