Techniques for blood volume fMRI with VASO: From low-resolution mapping towards sub-millimeter layer-dependent applications

Abstract

Quantitative cerebral blood volume (CBV) fMRI has the potential to overcome several specific limitations of BOLD fMRI. It provides direct physiological interpretability and promises superior localization specificity in applications of sub-millimeter resolution fMRI applications at ultra-high magnetic fields (7T and higher). Non-invasive CBV fMRI using VASO (vascular space occupancy), however, is inherently limited with respect to its data acquisition efficiency, restricting its imaging coverage and achievable spatial and temporal resolution. This limitation may be reduced with recent advanced acceleration and reconstruction strategies that allow two-dimensional acceleration, such as in simultaneous multi-slice (SMS) 2D-EPI or 3D-EPI in combination with CAIPIRINHA field-of-view shifting. In this study, we sought to determine the functional sensitivity and specificity of these readout strategies with VASO over a broad range of spatial resolutions; spanning from low spatial resolution (3mm) whole-cortex to sub-millimeter (0.75mm) slab-of-cortex (for cortical layer-dependent applications). In the thermal-noise-dominated regime of sub-millimeter resolutions, 3D-EPI-VASO provides higher temporal stability and sensitivity to detect changes in CBV compared to 2D-EPI-VASO. In this regime, 3D-EPI-VASO unveils task activation located in the cortical laminae with little contamination from surface veins, in contrast to the cortical surface weighting of GE-BOLD fMRI. In the physiological-noise-dominated regime of lower resolutions, however, 2D-SMS-VASO shows superior performance compared to 3D-EPI-VASO. Due to its superior sensitivity at a layer-dependent level, 3D-EPI VASO promises to play an important role in future neuroscientific applications of layer-dependent fMRI.

Trial registration: ClinicalTrials.gov NCT00001360.

Keywords: 3D-EPI; 7 T MRI; Cerebral blood volume; Layer-dependent fMRI; SS-SI VASO; Simultaneous multi-slice; Vascular space occupancy.

Copyright © 2016 Elsevier Inc. All rights reserved.

Figures

Fig. 1. Magnetization preparation, readout, and sequence timing

Schematic depiction of one TR in the SS-SI-VASO sequence. (A) and (B) show the timing of the most relevant RF and gradient events for 2D-SMS and 3D-segmented-EPI, respectively. Zoomed views of the corresponding readout modules for individual slices and k-space segments are depicted in (D)–(E). Every TR starts with a ‘global’ adiabatic inversion pulse. A phase skip is used to control the inversion efficiency and the inflow of fast, un-inverted blood. The VASO images are acquired around the blood-nulling time at TI1 = 1.1 s after successive application of the multi-band/slab-selective RF excitation pulses for 2D-SMS and 3D acquisitions, respectively. The multi-band factor varies between 1 and 3 in this study (SMS-factor = 3 in (D)). The phase-encoding and read gradients for the acquisition of the individual slices or k-space segments are accompanied with blipped-CAIPI gradients in slice/segment-direction for controlled aliasing of nearby slices. In this study the corresponding FOV-shift factor varied between 1 and 1/3 (FoV-shift = 1/2 in (D)–(E)). A second set of images is acquired at TI2 = 2.6 s containing BOLD-signal-weighting without CBV-weighting. Example brain volumes from every readout are depicted next to their RF and gradient events. Since, the effective TI can vary across slices in the 2D-SMS approach in the range of 200 ms, clear borders of the individual SMS slabs can be seen from the corresponding steps in T1-weighting (blue arrows in (A)).

Fig. 2. tSNR across resolutions

Results of VASO tSNR for 0.75 mm, 1.5 mm and 3 mm resolutions are shown for one participant in (A)–(B). For the protocols with (low) resolutions of 1.5 mm and 3 mm, 2D-SMS VASO provides higher tSNR values compared to 3D-segmented-EPI. At sub-millimeter resolutions of 0.75 mm, however, the tSNR of 3D-segmented-EPI surpasses that of 2D-SMS EPI. For best visibility, the dynamic range of the color bars is adjusted for each resolution, but it is kept identical for 2D-SMS and 3D-segmented-EPI. tSNR results in (C) refer to experiments, where slice-acquisition parameters are kept the same but the slice thickness is varied. Different voxel volumes refer to different slice thicknesses. It can be seen that in the physiological-noise-dominated regime of voxel volumes with few microliters, 2D-SMS-EPI performs better than 3D-segmented-EPI. However, in the thermal-noise-dominated regime at sub-microliters resolutions, 3D-segmented-EPI has higher signal stability. Fig. (E)–(H) show the same for the BOLD contrast. Similarly to VASO, also the BOLD stability is better for 3D-segmented-EPI at ultra high resolutions, while 2D-SMS is better for conventional resolutions. Note that the ceiling effect is slightly stronger in BOLD compared to VASO. Consequently, the advantage of 3D-segmented-EPI compared to 2D-SMS EPI is visible at smaller voxel sizes only. All given tSNR/SNR values in (A)–(C) and (E)–(F) refer to mean values across participants within ROIs of M1.

Fig. 3. Stability of tSNR results across participants

The higher temporal stability of sub millimeter voxels shown for one representative subject in Fig. 2 is consistent across participants of the study. For both, BOLD and VASO time series, tSNR values are higher for 3D-segmented-EPI compared to 2D-EPI. Note that BOLD and VASO figures are acquired simultaneously, while 3D-segmented-EPI and 2D-EPI figures are acquired in separate experiments 12 minutes apart. Hence, due to participants head motion between experiment, the slice position can be minimally different. Since the slice positioning and slice tilting was adjusted to be perpendicular to the participants individual M1 cortex, the FOV contains different brain regions for different participants.

Fig. 4. Functional results across resolutions

Functional activation results for 0.75 mm, 1.5 mm and 3 mm resolutions are shown for one subject in (A)–(F) for 3D-segmented-EPI and (G)–(L) for 2D-SMS, respectively. The depicted participant and the depicted slices are the same as shown in Fig. 2(A)–(B). For the sake of comparison, functional maps of BOLD signal changes are shown next to the VASO results. Note that BOLD signal changes are acquired simultaneously with VASO, while 3D-segmented-EPI and 2D-SMS data are acquired in two separate experiments ≈ 14 min apart. Also note that the functional contrasts and the color bars are differently optimized across resolutions, but they are the same for 3D-segmented-EPI and 2D-SMS results. For low resolutions of 3 mm in (E)–(F) and (K)–(L), functional maps don’t show strong qualitative differences for contralateral M1. Independent of contrast and readout-strategy, the high tSNR values (Fig. 2) result in sensitivities well above the detection threshold in all cases. At 1.5 mm resolution, the higher specificity of CBV-sensitive fMRI starts to pay off. E.g. two sides of the central sulcus can be better separated with CBV-fMRI compared to BOLD (blue arrows in ((C)–(D) and (I)–(J)). At 0.75 mm resolution, layer-dependent activity features become visible in CBV-fMRI results (green arrows in (A) and (G)), while the BOLD results appear less specific (green arrows in (B) and (H)).

Fig. 5. Susceptibility to task correlated head motion artefacts

Fig. 5 (A) depicts the SPM motion parameter of pitch rotation across one representative 10 min Valsalva experiment. The vertical black bars represent the periodes of breathhold. Clear task correlated motion can be seen. The “sawtooth” pattern between breathholding periodes refers to TR locked paced breathing. Fig. (B) and (C) show the effect of head tilting in 2D-SMS VASO and 3D-segmented-EPI VASO. In 2D-SMS VASO, the different effective inversion time across slices results in different signal intensities. Hence, after retrospective motion correction (MOCO), this signal discontinuity is resampled into agacent slices (red ellypses). This results in task-correlated signal changes visible in the axial plane, rendering any CBV interpretation impossible. In 3D-segmented-EPI VASO on the other hand, the homogenious signal intensity allowes restrospective motion correction without such artefacts.

Fig. 6. Usefulness for layer-dependent applications

fMRI responses across cortical depth. (A)–(B) show the section of the functional activity maps that are used to assess the applicability of VASO and BOLD contrast for layer-dependent fMRI. (C)–(D) depict the cortical profile of VASO and BOLD signal changes across cortical depth. The VASO signal change appears to be strongest along two cortical depths; upper cortical layers and deeper cortical layers. In BOLD, a similar pattern can be seen, however, it is overlaid on top of a strong gradient of largest BOLD signal change above the cortical surface, decreasing with cortical depth. Data presented in (A)–(D) refer to the same dataset as schown in Fig. 2(B), (F) and Fig. 4(G)–(H). The approximate position of cytoarchitectonically defined cortical layers can be given from stained post-mortem tissue samples (Stüber et al., 2014) (in (E) SMI- 311, IHC, cell staining is used). The vertical in this Fig. are manually overlaid based on the different cell types visible in (E). (F) portrays the collapsed SMI density plotted as a function of cortical depth, i.e. the y-axis refers to the sum of all gray values within every column of Fig. (E). For most quantitative layer-dependent activity interpretation, the laminar responses must be considered with respect to the baseline vasculature. (G) presents the micro vessel distribution of M1 as shown in (Duvernoy et al., 1981). The corresponding baseline CBV is shown in (H) as a function of cortical depth. Data shown in (H) are derived as the sum of gray values in columns of Fig. (G). Data shown in (E)–(H) refer to single-subject post mortem samples and correspond to different individuals as the data acquired in this study (A)–(D).