7T-fMRI: Faster temporal resolution yields optimal BOLD sensitivity for functional network imaging specifically at high spatial resolution (original) (raw)
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Journal of Magnetic Resonance Imaging, 2003
Purpose: To investigate the sensitivity dependence of BOLD functional imaging on MRI acquisition parameters in motor stimulation experiments using a finger tapping paradigm. Materials and Methods: Gradient-echo echo-planar fMRI experiments were performed at 1.5 T and 3.0 T with varying acquisition echo time and bandwidth, and with a 4 mm isotropic voxel size. To analyze the BOLD sensitivity, the relative contributions of BOLD signal amplitude and thermal and physiologic noise sources were evaluated, and statistical t-scores were compared in the motor area. Results: At 1.5 T, the number of activated pixels and the average t-score showed a relatively broad optimum over a TE range of 60-160 msec. At 3.0 T, an optimum range was observed between TEs of 30-130 msec. Averaged over nine subjects, maxima in the number of pixels and t-score values were 59% and 18% higher at 3.0 T than at 1.5 T, respectively, an improvement that was lower than the observed 100% to 110% increase in signal-to-noise ratio at 3.0 T. Conclusion: The somewhat disappointing increase in tscores at 3.0 T was attributed to the increased contribution of physiologic noise at the higher field strength under the given experimental conditions. At both field strengths, reducing the effective image acquisition bandwidth from 35 to 17 Hz per pixel did not affect or only marginally affect the BOLD sensitivity.
2009
Introduction: fMRI studies generally employ gradient-echo (GE) BOLD contrast due to the limited signal change and signal-to-noise ratio (SNR) of spin echo (SE) BOLD contrast at standard field strength. Ultra-high field (7T) provides increased BOLD contrast-to-noise ratio (CNR) and decreases the contribution that large vessels make to GE BOLD contrast, due to higher capillary contribution and the suppression of intravascular BOLD signal as a result of shortened blood T2 [1]. However, the extravascular venous signal will still contribute to GE BOLD maps at 7T. In SE BOLD contrast, extravascular static dephasing effects around large vessels are refocused causing the SE signal to arise mainly due to microvascular effects [2, 3]. A limited number of studies have compared GE and SE BOLD contrast, and these have generally been restricted to the visual cortex (due to its large response) with data being acquired at relatively coarse spatial resolution [4]. Here, the increased BOLD CNR at 7T ...
Magnetic resonance imaging, 2006
Functional magnetic resonance imaging (fMRI) does not typically yield highly reproducible maps of brain activation. Maps can vary significantly even with constant scanning parameters and consistent task performance conditions (Liu et al., Magn. Reson. Med., 2004, 52:751-760). Reproducibility is even more of a problem when comparing fMRI signal magnitude and spatial extent of activation across scans involving different task performance levels, scan durations, pulse sequences or magnetic field strengths. In this report, the consistency of fMRI was reexamined by considering the relative spatial and temporal distribution of fMRI blood oxygen level dependent (BOLD) activation signals separately from the absolute magnitude of the activation signal in each brain area. Subjects repeatedly performed the same simple motor task but under a variety of imaging conditions, using both spiral and standard echo-planar pulse sequences and at 1.5- and 4.0-T magnetic field strengths. The results demons...
Magnetic Resonance Imaging, 1995
Functional magnetic resonance imaging (fMR1) is usually based on acquisition of alternating series of images under rest and an activation task (stimulus). Brain activation maps can be generated from fMRI data sets by applying several mathematical methods. Two methods of image postprocessing have been compared: (i) simple difference of mean values between rest and stimulation, and (ii) Student's t-test. The comparison shows that the difference method is very sensitive to arbitrary signal fluctuations as seen mainly in large vessels (e.g., in the sagittal sinus), leading to insignificantly activated spots in brain activation maps. In contrary, Student's t-test maps show strongly reduced sensitivity for fluctuations and have the advantage of giving activation thresholds by setting significance levels. This allows the comparison of activation strength between patient collectives by using a grid overlay tecbnique leading to an observer independent quantification of the stimulation effects. The method was able to reproduce previous findings of activation differences between healthy volunteers and schizophrenic patients. Moreover, a simple algorithm for the correction of slight bead movements during the functional imaging task is presented. The algorithm is based on shifting the fMRI data set relative to a reference image by maximizing the linear correlation coefficients. This leads to a further reduction of insignificant brain activation and to an improvement in brain activation map quality. methods providing objective criteria for brain acti-RECEIVED 7/11/94; ACCEPTED 2/14/95.
Journal of Magnetic Resonance Imaging, 1999
In 23 fMRI studies on six subjects, we examined activation in visual and motor tasks. We modeled the expected activation time course by convolving a temporal description of the behavioral task with an empirically determined impulse response function. We evaluated the signal activation intensity as both the number of activated voxels over arbitrary correlation thresholds and as the slope of the regression line between our modeled time course and the actual data. Whereas the voxel counting was strikingly unstable (standard deviation 74% in visual trials at a correlation of 0.5), the slope was relatively constant across trials and subjects (standard deviation F14%). Using Monte Carlo methods, we determined that the measured slope was largely independent of the contrast-to-noise ratio. Voxel counting is a poor proxy for activation intensity, with greatly increased scatter, much reduced statistical power, and increased type II error. The data support an alternative approach to functional magnetic resonance imaging (fMRI) that allows for quantitative comparisons of fMRI response magnitudes across trials and laboratories.
Spatial specificity of high-resolution, spin-echo BOLD, and CBF fMRI at 7 T
2004
With growing interest in noninvasive mapping of columnar organization and other small functional structures in the brain, achieving high spatial resolution and specificity in fMRI is of critical importance. We implemented a simple method for BOLD and perfusion fMRI with high spatial resolution and specificity. Increased spatial resolution was achieved by selectively exciting a slab of interest along the phase-encoding direction for EPI, resulting in a reduced FOV and number of phase-encoding steps. Improved spatial specificity was achieved by using SE EPI acquisition at high fields, where it is predominantly sensitive to signal changes in the microvasculature. Robust SE BOLD and perfusion fMRI were obtained with a nominal in-plane resolution up to 0.5 ؋ 0.5 mm 2 at 7 and 4 Tesla, and were highly reproducible under repeated measures. This methodology enables high-resolution and high-specificity studies of functional topography in the millimeter to submillimeter spatial scales of the human brain.
High-Field fMRI for Human Applications: An Overview of Spatial Resolution and Signal Specificity
The Open Neuroimaging Journal, 2011
In the last decade, dozens of 7 Tesla scanners have been purchased or installed around the world, while 3 Tesla systems have become a standard. This increased interest in higher field strengths is driven by a demonstrated advantage of high fields for available signal-to-noise ratio (SNR) in the magnetic resonance signal. Functional imaging studies have additional advantages of increases in both the contrast and the spatial specificity of the susceptibility based BOLD signal. One use of this resultant increase in the contrast to noise ratio (CNR) for functional MRI studies at high field is increased image resolution. However, there are many factors to consider in predicting exactly what kind of resolution gains might be made at high fields, and what the opportunity costs might be. The first part of this article discusses both hardware and image quality considerations for higher resolution functional imaging. The second part draws distinctions between image resolution, spatial specificity, and functional specificity of the fMRI signals that can be acquired at high fields, suggesting practical limitations for attainable resolutions of fMRI experiments at a given field, given the current state of the art in imaging techniques. Finally, practical resolution limitations and pulse sequence options for studies in human subjects are considered.
High-resolution, spin-echo BOLD, and CBF fMRI at 4 and 7 T
Magnetic Resonance in Medicine, 2002
With growing interest in noninvasive mapping of columnar organization and other small functional structures in the brain, achieving high spatial resolution and specificity in fMRI is of critical importance. We implemented a simple method for BOLD and perfusion fMRI with high spatial resolution and specificity. Increased spatial resolution was achieved by selectively exciting a slab of interest along the phase-encoding direction for EPI, resulting in a reduced FOV and number of phase-encoding steps. Improved spatial specificity was achieved by using SE EPI acquisition at high fields, where it is predominantly sensitive to signal changes in the microvasculature. Robust SE BOLD and perfusion fMRI were obtained with a nominal in-plane resolution up to 0.5 ؋ 0.5 mm 2 at 7 and 4 Tesla, and were highly reproducible under repeated measures. This methodology enables high-resolution and high-specificity studies of functional topography in the millimeter to submillimeter spatial scales of the human brain.
Enhanced fMRI Response Detection and Reduced Latency through Spatial Analysis of BOLD Signals
2008
In conventional functional magnetic resonance imaging (fMRI) analysis, activation is often inferred by examining only the intensity modulation of blood-oxygen-level dependent (BOLD) signal of each voxel in isolation or in small, local clusters. However, as has been recently demonstrated, activation can in fact be detected by examining the spatial modulation of the BOLD distribution within a region of interest (ROI). In this paper, we propose and demonstrate with real fMRI data that analyzing such spatial changes can enhance the effect size of fMRI response detection over using intensity information alone. Furthermore, we show that such spatial changes consistently and significantly antecede mean intensity changes in multiple ROIs. We hence foresee spatial analysis of BOLD distribution to be a promising direction to explore in complementing pure intensity-based approaches.