Jacco A. de Zwart

High-field MRI of brain cortical substructure based on signal phase

The ability to detect brain anatomy and pathophysiology with MRI is limited by the contrast-to-noise ratio (CNR), which depends on the contrast mechanism used and the spatial resolution. In this work, we show that in MRI of the human brain, large improvements in contrast to noise in high-resolution images are possible by exploiting the MRI signal phase at high magnetic field strength. Using gradient-echo MRI at 7.0 tesla and a multichannel detector, a nominal voxel size of 0.24 × 0.24 × 1.0 mm3 (58 nl) was achieved. At this resolution, a strong phase contrast was observed both between as well as within gray matter (GM) and white matter (WM). In gradient-echo phase images obtained on normal volunteers at this high resolution, the CNR between GM and WM ranged from 3:1 to 20:1 over the cortex. This CNR is an almost 10-fold improvement over conventional MRI techniques that do not use image phase, and it is an ≈100-fold improvement when including the gains in resolution from high-field and multichannel detection. Within WM, phase contrast appeared to be associated with the major fiber bundles, whereas contrast within GM was suggestive of the underlying layer structure. The observed phase contrast is attributed to local variations in magnetic susceptibility, which, at least in part, appeared to originate from iron stores. The ability to detect cortical substructure from MRI phase contrast at high field is expected to greatly enhance the study of human brain anatomy in vivo.

Low frequency BOLD fluctuations during resting wakefulness and light sleep: A simultaneous EEG-fMRI study †

Recent blood oxygenation level dependent functional MRI (BOLD fMRI) studies of the human brain have shown that in the absence of external stimuli, activity persists in the form of distinct patterns of temporally correlated signal fluctuations. In this work, we investigated the spontaneous BOLD signal fluctuations during states of reduced consciousness such as drowsiness and sleep. For this purpose, we performed BOLD fMRI on normal subjects during varying levels of consciousness, from resting wakefulness to light (non‐slow wave) sleep. Depth of sleep was determined based on concurrently acquired EEG data. During light sleep, significant increases in the fluctuation level of the BOLD signal were observed in several cortical areas, among which visual cortex was the most significant. Correlations among brain regions involved with the default‐mode network persisted during light sleep. These results suggest that activity in areas such as the default‐mode network and primary sensory cortex, as measured from BOLD fMRI fluctuations, does not require a level of consciousness typical of wakefulness. Hum Brain Mapp, 2008.

Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal

Heart rate fluctuations occur in the low-frequency range (<0.1 Hz) probed in functional magnetic resonance imaging (fMRI) studies of resting-state functional connectivity and most fMRI block paradigms and may be related to low-frequency blood-oxygenation-level-dependent (BOLD) signal fluctuations. To investigate this hypothesis, temporal correlations between cardiac rate and resting-state fMRI signal timecourses were assessed at 3 T. Resting-state BOLD fMRI and accompanying physiological data were acquired and analyzed using cross-correlation and regression. Time-shifted cardiac rate timecourses were included as regressors in addition to established physiological regressors (RETROICOR (Glover, G.H., Li, T.Q., Ress, D., 2000. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med 44, 162-167) and respiration volume per unit time (Birn, R.M., Diamond, J.B., Smith, M.A., Bandettini, P.A., 2006b. Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. NeuroImage 31, 1536-1548). Significant correlations between the cardiac rate and BOLD signal timecourses were revealed, particularly negative correlations in gray matter at time shifts of 6-12 s and positive correlations at time shifts of 30-42 s (TR=6 s). Regressors consisting of cardiac rate timecourses shifted by delays of between 0 and 24 s explained an additional 1% of the BOLD signal variance on average over the whole brain across 9 subjects, a similar additional variance to that explained by respiration volume per unit time and RETROICOR regressors, even when used in combination with these other physiological regressors. This suggests that including such time-shifted cardiac rate regressors will be beneficial for explaining physiological noise variance and will thereby improve the statistical power in future task-based and resting-state fMRI studies.

Layer-specific variation of iron content in cerebral cortex as a source of MRI contrast

Recent advances in high-field MRI have dramatically improved the visualization of human brain anatomy in vivo. Most notably, in cortical gray matter, strong contrast variations have been observed that appear to reflect the local laminar architecture. This contrast has been attributed to subtle variations in the magnetic properties of brain tissue, possibly reflecting varying iron and myelin content. To establish the origin of this contrast, MRI data from postmortem brain samples were compared with electron microscopy and histological staining for iron and myelin. The results show that iron is distributed over laminae in a pattern that is suggestive of each region’s myeloarchitecture and forms the dominant source of the observed MRI contrast.

Susceptibility Contrast in High Field MRI of Human Brain as a Function of Tissue Iron Content

Magnetic susceptibility provides an important contrast mechanism for MRI. Increasingly, susceptibility-based contrast is being exploited to investigate brain tissue microstructure and to detect abnormal levels of brain iron as these have been implicated in a variety of neuro-degenerative diseases. However, it remains unclear to what extent magnetic susceptibility-related contrast at high field relates to actual brain iron concentrations. In this study, we performed susceptibility weighted imaging as a function of field strength on healthy brains in vivo and post-mortem brain tissues at 1.5 T, 3 T and 7 T. Iron histology was performed on the tissue samples for comparison. The calculated susceptibility-related parameters R(2)(*) and signal frequency shift in four iron-rich regions (putamen, globus pallidus, caudate, and thalamus) showed an almost linear dependence (r>or=0.90 for R(2)(*); r>or=0.83 for phase, p<0.01) on field strength, suggesting that potential ferritin saturation effects are not relevant to susceptibility-weighted contrast for field strengths up to 7 T. The R(2)(*) dependence on the putative (literature-based) iron concentration was 0.048 Hz/T/ppm. The histological data from brain samples confirmed the linear dependence of R(2)(*) on field strength and showed a slope against iron concentration of 0.0099 Hz/T/ppm dry-weight, which is equivalent to 0.05 Hz/T/ppm wet-weight and closely matched the calculated value in vivo. These results confirm the validity of using susceptibility-weighted contrast as an indicator of iron content in iron-rich brain regions. The absence of saturation effects opens the way to exploit the benefits of MRI at high field strengths for the detection of iron distributions with high sensitivity and resolution.

Design of a SENSE‐optimized high‐sensitivity MRI receive coil for brain imaging

An 8‐channel receive‐only detector array was developed for SENSE MRI of human brain. The coil geometry was based on a gapped element design and used ultra‐high impedance preamplifiers for mutual decoupling of the elements. Computer simulations of the electric and magnetic fields showed that excellent signal‐to‐noise ratio (SNR) and SENSE performance could be achieved by placing the coil elements close to the head and maintaining a substantial gap between the elements. Measurements with a 1.5 T prototype coil showed a 2.7‐fold improvement of the SNR averaged over the brain compared to a conventional quadrature birdcage receive coil and an average geometrical noise amplification factor (g‐value) of 1.06 and 1.38 for rate‐2 and rate‐3 SENSE, respectively. Magn Reson Med 47:1218–1227, 2002. Published 2002 Wiley‐Liss, Inc.

Signal-to-noise ratio and parallel imaging performance of a 16-channel receive-only brain coil array at 3.0 Tesla†

The performance of a 16‐channel receive‐only RF coil for brain imaging at 3.0 Tesla was investigated using a custom‐built 16‐channel receiver. Both the image signal‐to‐noise ratio (SNR) and the noise amplification (g‐factor) in sensitivity‐encoding (SENSE) parallel imaging applications were quantitatively evaluated. Furthermore, the performance was compared with that of hypothetical coils with one, two, four, and eight elements (n) by combining channels in software during image reconstruction. As expected, both the g‐factor and SNR improved substantially with n. Compared to an equivalent (simulated) single‐element coil, the 16‐channel coil showed a 1.87‐fold average increase in brain SNR. This was mainly due to an increase in SNR in the peripheral brain (an up to threefold SNR increase), whereas the SNR increase in the center of the brain was 4%. The incremental SNR gains became relatively small at large n, with a 9% gain observed when n was increased from 8 to 16. Compared to the (larger) product birdcage head coil, SNR increased by close to a factor of 2 in the center, and by up to a factor of 6 in the periphery of the brain. For low SENSE acceleration (rate‐2), g‐factors leveled off for n > 4, and improved only slightly (1.4% averaged over brain) going from n = 8 to n = 16. Improvements in g for n > 8 were larger for higher acceleration rates, with the improvement for rate‐3 averaging 12.0%. Magn Reson Med 51:22–26, 2004. Published 2003 Wiley‐Liss, Inc.

Sources of functional magnetic resonance imaging signal fluctuations in the human brain at rest: a 7 T study ☆

Signal fluctuations in functional magnetic resonance imaging (fMRI) can result from a number of sources that may have a neuronal, physiologic or instrumental origin. To determine the relative contribution of these sources, we recorded physiological (respiration and cardiac) signals simultaneously with fMRI in human volunteers at rest with their eyes closed. State-of-the-art technology was used including high magnetic field (7 T), a multichannel detector array and high-resolution (3 mm(3)) echo-planar imaging. We investigated the relative contribution of thermal noise and other sources of variance to the observed fMRI signal fluctuations both in the visual cortex and in the whole brain gray matter. The following sources of variance were evaluated separately: low-frequency drifts due to scanner instability, effects correlated with respiratory and cardiac cycles, effects due to variability in the respiratory flow rate and cardiac rate, and other sources, tentatively attributed to spontaneous neuronal activity. We found that low-frequency drifts are the most significant source of fMRI signal fluctuations (3.0% signal change in the visual cortex, TE=32 ms), followed by spontaneous neuronal activity (2.9%), thermal noise (2.1%), effects due to variability in physiological rates (respiration 0.9%, heartbeat 0.9%), and correlated with physiological cycles (0.6%). We suggest the selection and use of four lagged physiological noise regressors as an effective model to explain the variance related to fluctuations in the rates of respiration volume change and cardiac pulsation. Our results also indicate that, compared to the whole brain gray matter, the visual cortex has higher sensitivity to changes in both the rate of respiration and the spontaneous resting-state activity. Under the conditions of this study, spontaneous neuronal activity is one of the major contributors to the measured fMRI signal fluctuations, increasing almost twofold relative to earlier experiments under similar conditions at 3 T.

Application of Sensitivity-Encoded Echo-Planar Imaging for Blood Oxygen Level-Dependent Functional Brain Imaging

The benefits of sensitivity‐encoded (SENSE) echo‐planar imaging (EPI) for functional MRI (fMRI) based on blood oxygen level‐dependent (BOLD) contrast were quantitatively investigated at 1.5 T. For experiments with 3.4 × 3.4 × 4.0 mm3 resolution, SENSE allowed the single‐shot EPI image acquisition duration to be shortened from 24.1 to 12.4 ms, resulting in a reduced sensitivity to geometric distortions and T  *2 blurring. Finger‐tapping fMRI experiments, performed on eight normal volunteers, showed an overall 18% loss in t‐score in the activated area, which was substantially smaller than expected based on the image signal‐to‐noise ratio (SNR) and g‐factor, but similar to the loss predicted by a model that takes physiologic noise into account. Magn Reson Med 48:1011–1020, 2002. Published 2002 Wiley‐Liss, Inc.

Modulation of spontaneous fMRI activity in human visual cortex by behavioral state

The phenomenon of spontaneous fMRI activity is increasingly being exploited to investigate the connectivity of functional networks in human brain with high spatial-resolution. Although mounting evidence points towards a neuronal contribution to this activity, its functional role and dependence on behavioral state remain unclear. In this work, we used BOLD fMRI at 7 T to study the modulation of spontaneous activity in occipital areas by various behavioral conditions, including resting with eyes closed, eyes open with visual fixation, and eyes open with fixation and focal visual stimulation. Spontaneous activity was separated from evoked activity and from signal fluctuations related to cardiac and respiratory cycles. We found that spontaneous activity in visual areas was substantially reduced (amplitude (44%) and coherence (25%)) with the fixation conditions relative to the eyes-closed condition. No significant further modulation was observed when the visual stimulus was added. The observed dependence on behavioral condition suggests that part of spontaneous fMRI signal fluctuations represents neuronal activity. Possible mechanisms for the modulation of spontaneous activity by behavioral state are discussed. The observed linear superposition of spontaneous fMRI activity with focal evoked activity related to visual processing has important implications for fMRI studies, which ideally should take into account the effect of spontaneous activity to properly define brain activations during task conditions.