Non-BOLD: Imaging Blood Volume & Perfusion
Emmanuel L. Barbier1 and Jan M. Warnking1
1Grenoble Institute Neurosciences, Grenoble, France

Synopsis

The relation between the BOLD signal and brain physiology is complex. Among the physiological determinants of BOLD, the cerebral blood volume (CBV) and the cerebral blood flow (CBF) appear of interest: they may be mapped using MRI. In fact, the first functional MRI paper ever published was based on the mapping of CBV changes, soon followed by a CBF-based fMRI paper. In this course, we will review the main fMRI methods based on blood volume and blood flow.

Introduction

The relation between the BOLD signal and brain physiology is complex (1). Among the physiological determinants of BOLD, the cerebral blood volume (CBV) and the cerebral blood flow (CBF) appear of interest: they may be mapped using MRI (2). In fact, the first functional MRI paper ever published was based on the mapping of CBV changes (3), soon followed by a CBF-based fMRI paper (4). In this course, we will review fMRI methods based on blood volume and blood flow. These two fMRI approaches represent a small fraction of the fMRI-related scientific literature.
A Pubmed search (April 2021) yields:
  • fmri [Title/Abstract]: 48,089 articles
  • BOLD [Title/Abstract] fmri [Title/Abstract]: 7,105 articles
  • CBF [Title/Abstract] fmri [Title/Abstract]: 490 articles
  • ASL [Title/Abstract] fmri [Title/Abstract]: 311 articles
  • CBV [Title/Abstract] fmri [Title/Abstract]: 220 articles
  • VASO [Title/Abstract] fmri [Title/Abstract]: 49 articles
This search is most probably neither complete nor accurate, but it provides a rough estimate of the proportions of CBF-fMRI and of CBV-fMRI with respect to BOLD-fMRI.

CBF-fMRI methods

The potential of Arterial Spin Labeling (ASL) for fMRI has been evaluated as early as the beginning of the 90’s (4,5). The ASL method is by nature a subtraction approach: the perfusion-weighted ASL signal emerges from the suppression of the signal from static spins by subtraction of a control image and a labeled image, after inversion of the magnetization of the inflowing blood. Numerous methods have been proposed to achieve the ASL contrast:
  • in Continuous ASL (CASL), blood magnetization is continuously inverted at the carotid level during a few seconds;
  • in pseudo-continuous ASL (pCASL), the blood magnetization is inverted at the carotid level but using a fractionated RF pulse instead of a continuous one;
  • in Pulsed ASL (PASL), blood magnetization is inverted almost instantly in a large inversion slab;
  • in velocity-encoded ASL, blood that decelerates is inverted anywhere in the brain;
The temporal resolution of ASL acquisitions is low (compared to BOLD-fMRI) due to the need of performing interleaved control and label acquisitions. The multi-shot 3D-GRASE readouts that are recommended for baseline CBF measurements to optimize SNR (6) are not suitable for fMRI unless the task frequency is very low. Multi-slice gradient-echo EPI acquisitions are more commonly used in this context. There have been several attempts to improve ASL methods in view of fMRI. As early as 2000, TurboASL was proposed, a PASL approach in which the inversion time is larger than the TR to improve the temporal resolution (7). In Turbo-CASL, the control data is collected before labeled spins reach the imaging plane (8). Other approaches include DASL (9) , turbo-DASL (10), turbo-QUASAR. More recent developments include multiband and multi-echo acquisition schemes (11,12).
Regarding fMRI, both the label and the control images are sensitive to the BOLD effect (especially when acquired with gradient-echo EPI). As they are acquired several seconds apart, the label and control images will sample the BOLD response at different points along its slow, hemodynamic evolution. Consequently, the perfusion data that results from subtraction of adjacent pairs of BOLD sensitive images will be a combination of a true perfusion response plus the first derivative of the BOLD response times the TR (13). Several subtraction methods have been proposed: (a) standard pair-wise subtraction of control and tag images, (b) surround subtraction in which the difference between each image and the average of its two nearest neighbors is computed, and (c) subtraction of sinc-interpolated control and tag images which uses a larger number of tag and control images (5,13). As these approaches may be seen as different types of low pass filter, Liu and Wong proposed an ideal filter for this subtraction approach (14). As the use of differenced data suffers from loss in contrast efficiency, Mumford et al. recommend to explicitly include the control/label effect in the data modeling using Generalized Least Square (GLS) (8). In all cases, the use of short echo time and background suppression reduces the BOLD weighting in the pCASL signal, as observed in the PET-MRI comparison study (15).It is also important to minimize the effects of physiological noise. If cardiac and respiratory frequencies are monitored, the RETROICOR approach (16) may be used by Chen et al. mention in their review (17) that it should be applied to the tag and control images.
The inherent modulation of the perfusion-weighted signal by the alternation of control and tag conditions makes the ASL signal insensitive to low-frequency fluctuations in the MRI signal. For this reason, ASL is well suited to study slow fMRI paradigms, such as for pharmacological fMRI (18,19).
Outside of applications for pharmacological fMRI, the most common use of ASL in fMRI is in conjunction with BOLD fMRI, either to better understand BOLD and/or ASL signal properties (20) or to examine the physiological processes during the fMRI task more closely, for example using calibrated BOLD experiments (21). Combined ASL/BOLD acquisitions most often rely on dual-echo or multi-echo readouts, permitting to separate the BOLD and ASL signal contributions from their TE-dependence (11,22) or use separate interleaved acquisitions for BOLD and ASL (23,24).
The major drawback of ASL is its low SNR. As magnetic fields above 3 T become more common, ASL could benefit from the longer blood T1. However, SAR issues prevent the use of pCASL at repetition times compatible with fMRI (25), and PASL approaches remain the most commonly used techniques at 7 T and beyond (26).

CBV-fMRI: with contrast agent

The most clinically used method to map CBV is the Susceptibility Contrast method such as in the Dynamic Susceptibility contrast approach (DSC). It relies on the intravenous injection of a contrast agent, a Gd-chelate (2).
A paramagnetic contrast agent alters the magnetic landscape in and around the microvessels, up to a distance comparable to the diameter of the vessels. This alteration of the magnetic landscape yields a broader distribution of resonance frequencies in the voxel and thereby a shorter T2* and, because of water movements in this landscape during the echo-time, T2. When the blood volume fraction is small (a few percent), the reduction in transverse relaxation rate is proportional to the blood volume for T2* and more sensitive to microvessels (capillaries) for T2 (27,28). This susceptibility contrast produces robust estimates of CBV.
However, the rapid extravasation and relatively short plasmatic half-life of this contrast agent prevent its use for fMRI studies (in their seminal paper, Belliveau et al. used two injections of contrast agent (3)). Instead, iron oxide nanoparticles do not extravasate and have a longer plasmatic half-life (29,30). Their plasmatic concentration can remain relatively stable for a few tens of minutes and thereby allows the acquisition of high resolution CBV maps (31). Once injected, changes in blood oxygenation marginally contribute to the MRI signal, which is strongly dominated by changes in CBV. Mandeville named this approach “IRON” fMRI (30). Because the use of iron oxide nanoparticles is not authorized in Humans, IRON fMRI has been used almost exclusively in animal models, as early as 1998 (32,33) and in different species (34). After the approval by the FDA in 2009 of ultrasmall superparamagnetic iron oxide particles as an iron replacement therapy for patients with chronic kidney disease (Ferumoxytol (35)), a few research studies evaluated their off-label use of in healthy subjects (36–38).
The largest advantage of iron-based CBV-fMRI is its contrast to noise: a least a factor 2, compared to BOLD contrast. This effect is event larger at low magnetic field (a factor ~3 at 3T) (30). However, the IRON approach exhibits a larger impulse response than the BOLD approach. Thereby, IRON approach are not well suited for event-related fMRI protocols. Also, like for BOLD-fMRI, the angle of the vessel to the main magnetic field affect the signal: in case the main orientation of vessels in the voxel is parallel to the main magnetic field, this voxel will lack fMRI contrast (39). Again, in these studies, a CNR gain of approximately 2–3 is reported compared to BOLD fMRI. As a shorter echo time may be used for iron-based CBV-fMRI, less susceptibility-related signal dropouts were observed (e.g. in the inferior frontal and temporal lobes)(37). Resting-state-fMRI obtained with BOLD of CBV contrast were comparable but small differences in the detected networks were however reported (36). As iron-based CBV-fMRI is a quantitative approach, it is also well suited for pharmacological fMRI (40–43). In 2015, FDA issued a warning about serious, potentially fatal allergic reactions that can occur with Ferumoxytol.

CBV-fMRI: without contrast agent

CBV-fMRI may also be performed without using a contrast: the vascular space occupancy (VASO) approach (44).
This approach relies on nulling of the blood signal using a non-selective inversion pulse. When the blood signal is null, a slice selective excitation pulse yields access the signal from the parenchymal tissue. Thereby, changes in cerebral blood volume (CBV) can be assessed through changes in this parenchymal tissue signal (or extravascular tissue signal). When CBV increases, the parenchymal tissue signal decreases. This approach relies on the fact that the T1 of blood may be considered as constant throughout the brain (i.e. independent of blood oxygenation and hematocrit). This approach does not provide an absolute estimate of CBV changes, as opposed to iron-based CBV-fMRI methods. To obtain absolute CBV changes from VASO data, an additional measure of the CBV at rest is required.
To minimize the contribution of BOLD-related signal change, the shortest possible echo time is required (44). Indeed, a BOLD contrast (increase in T2* due to the dilution of desoxyhemoglobin) would increase the signal level and thereby masks in part the signal decrease expected in the VASO experiment. Moreover, the contribution of CSF should be accounted for (45). To avoid contribution of flow effects, TR should be long enough (TR > 3s in Humans at 3T) and the coil used for non-selective inversion should have a large enough coverage to avoid the inflow of non-inverted spins during the measurement time (46).
This original VASO approach was single slice. A multislice and then a 3D version, based on the 3D GRASE sequence, were then proposed (47–49). Other improvements were also proposed such as magnetization-transfer VASO (MT-VASO)(50) or inflow-based VASO (i-VASO)(51). In 2012, a review of the technical developments made around VASO was published (52).
At magnetic fields above 3T, VASO faces several issues: blood and tissue T1 become more comparable, BOLD contamination becomes stronger, and performing a homogeneous non-selective inversion becomes more challenging (inhomogeneous RF fields, no possibility to use a body coil because of SAR issue). In this setting, to improve the functional CBV sensitivity, the use of a shorter TR and a slab-selective inversion (SI-VASO) was proposed (53). This approach was further developed into a slice-saturation slab-selective approach (SS-SI-VASO) (54). This approach, limited to one or a few slices, offers the advantage of allowing higher spatial resolution. At a preclinical level and using a 9.4T MRI system, the CBV-fMRI approach appeared to be more sensitive to signals variations located in the middle cortical layer (53). In healthy volunteers at 7T, the CBV-fMRI variations were higher deep in the cortex while, for BOLD, signal variations were higher at the surface (54). Several layer-fMRI VASO studies were performed, as reviewed on this blog: https://layerfmri.com. The access to high spatial resolution was used to map input and output activity of the primary motor cortex or the cortical representation of individual fingers (55,56). Recently, an approach in which a continuous nulling of blood magnetization is achieved was introduced to improve the CBV-fMRI contrast and to simultaneously obtain CBF-fMRI contrast (57).

Other non-BOLD fMRI methods

At the preclinical level, and sometimes in Human, several alternative fMRI methods have been evaluated, in order to escape from the ‘vascular filter’. One can briefly mention the following sources of contrast with a few references (among many more):
  • MR spectroscopy (58–61)
  • Mn enhanced MRI (62–64) (Mn is toxic, used only in animals)
  • Diffusion MRI (65)
  • Chemical Enhanced Saturation Transfer (CEST) MRI (66)

Conclusions

BOLD fMRI data are easier to acquire and post-process while CBF- and CBV-fMRI requires special sequences, sometimes the use of a contrast agent, and specific post-processing means. This strongly limits their use. However, CBF-fMRI and CBV-fMRI provide more quantitative estimates and may position hemodynamic changes closer to the site of neuronal activity (5,44,67,68), as BOLD contributions mostly originate from draining veins. Thereby, CBF-fMRI and CBV-fMRI can help further investigate the neurovascular coupling, a point of interest in case of brain disease when neurovascular coupling can be altered. Fine differences are also observed between BOLD, CBV, and CBF resting-state fMRI data, challenging our understanding of the neurovascular coupling across the brain (69). Finally BOLD-fMRI and CBF-fMRI acquisitions may be combined to obtain, using an additional calibration, an estimate of changes in CMRO2 (21).

Acknowledgements

No acknowledgement found.

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Proc. Intl. Soc. Mag. Reson. Med. 29 (2021)