Rapid three-dimensional functional magnetic resonance imaging of the initial negative BOLD response

Existence of Initial Dip for BCI: An Illusion or Reality

A tight coupling between the neuronal activity and the cerebral blood flow (CBF) is the motivation of many hemodynamic response (HR)-based neuroimaging modalities. The increase in neuronal activity causes the increase in CBF that is indirectly measured by HR modalities. Upon functional stimulation, the HR is mainly categorized in three durations: (i) initial dip, (ii) conventional HR (i.e., positive increase in HR caused by an increase in the CBF), and (iii) undershoot. The initial dip is a change in oxygenation prior to any subsequent increase in CBF and spatially more specific to the site of neuronal activity. Despite additional evidence from various HR modalities on the presence of initial dip in human and animal species (i.e., cat, rat, and monkey); the existence/occurrence of an initial dip in HR is still under debate. This article reviews the existence and elusive nature of the initial dip duration of HR in intrinsic signal optical imaging (ISOI), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS). The advent of initial dip and its elusiveness factors in ISOI and fMRI studies are briefly discussed. Furthermore, the detection of initial dip and its role in brain-computer interface using fNIRS is examined in detail. The best possible application for the initial dip utilization and its future implications using fNIRS are provided.

Motion correction for functional MRI with three-dimensional hybrid radial-Cartesian EPI

Purpose

Subject motion is a major source of image degradation for functional MRI (fMRI), especially when using multishot sequences like three‐dimensional (3D EPI). We present a hybrid radial‐Cartesian 3D EPI trajectory enabling motion correction in k‐space for functional MRI.

Methods

The EPI “blades” of the 3D hybrid radial‐Cartesian EPI sequence, called TURBINE, are rotated about the phase‐encoding axis to fill out a cylinder in 3D k‐space. Angular blades are acquired over time using a golden‐angle rotation increment, allowing reconstruction at flexible temporal resolution. The self‐navigating properties of the sequence are used to determine motion parameters from a high temporal‐resolution navigator time series. The motion is corrected in k‐space as part of the image reconstruction, and evaluated for experiments with both cued and natural motion.

Results

We demonstrate that the motion correction works robustly and that we can achieve substantial artifact reduction as well as improvement in temporal signal‐to‐noise ratio and fMRI activation in the presence of both severe and subtle motion.

Conclusion

We show the potential for hybrid radial‐Cartesian 3D EPI to substantially reduce artifacts for application in fMRI, especially for subject groups with significant head motion. The motion correction approach does not prolong the scan, and no extra hardware is required. Magn Reson Med 78:527–540, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Exploitation of temporal redundancy in compressed sensing reconstruction of fMRI studies with a prior-based algorithm (PICCS)

PURPOSE

Compressed sensing is a technique used to accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. While it has proven particularly useful in dynamic imaging procedures such as cardiac cine, very few authors have applied it to functional magnetic resonance imaging (fMRI). The purpose of the present study was to check whether the prior image constrained compressed sensing (PICCS) algorithm, which is based on an available prior image, can improve the statistical maps in fMRI better than other strategies that also exploit temporal redundancy.

METHODS

PICCS was compared to spatiotemporal total variation (TTV) and k-t FASTER, since they have already demonstrated high performance and robustness in other MRI applications, such as cardiac cine MRI and resting state fMRI, respectively. The prior image for PICCS was the average of all undersampled data. Both PICCS and TTV were solved using the split Bregman formulation. K-t FASTER algorithm relies on matrix completion to reconstruct the undersampled k-spaces. The three algorithms were evaluated using two datasets with high and low signal-to-noise ratio (SNR)-BOLD contrast-acquired in a 7 T preclinical MRI scanner and retrospectively undersampled at various rates (i.e., acceleration factors). The authors evaluated their performance in terms of the sensitivity/specificity of BOLD detection through receiver operating characteristic curves and by visual inspection of the statistical maps.

RESULTS

With high SNR studies, PICCS performed similarly to the state-of-the-art algorithms TTV and k-t FASTER and provided consistent BOLD signal at the ROI. In scenarios with low SNR and high acceleration factors, PICCS still provided consistent maps and higher sensitivity/specificity than TTV, whereas k-t FASTER failed to provide significant maps.

CONCLUSIONS

The authors performed a comparison between three reconstructions (PICCS, TTV, and k-t FASTER) that exploit temporal redundancy in fMRI. The prior-based algorithm, PICCS, preserved BOLD activation and sensitivity/specificity better than TTV and k-t FASTER in noisy scenarios. The PICCS algorithm can potentially reach an acceleration factor of ×8 and still provide BOLD contrast in the ROI with an area under the curve over 0.99.

High-throughput optogenetic functional magnetic resonance imaging with parallel computations

Optogenetic functional magnetic resonance imaging (of MRI) technology enables cell-type-specific, temporally precise neuronal control and the accurate, in vivo readout of the resulting activity across the entire brain. With the ability to precisely control excitation and inhibition parameters and accurately record the resulting activity, there is an increased need for a high-throughput method to bring the of MRI studies to their full potential. In this paper, an advanced system facilitating real-time fMRI with interactive control and analysis in a fraction of the MRI acquisition repetition time (TR) is proposed. With high-processing speed, sufficient time will be available for the integration of future developments that further enhance of MRI data or streamline the study. We designed and implemented a highly optimised, massively parallel system using graphics processing units (GPUs), which achieves the reconstruction, motion correction, and analysis of 3D volume data in approximately 12.80 ms. As a result, with a 750 ms TR and 4 interleaf fMRI acquisition, we can now conduct sliding window reconstruction, motion correction, analysis and display in approximately 1.7% of the TR. Therefore, a significant amount of time can now be allocated to integrating advanced but computationally intensive methods that improve image quality and enhance the analysis results within a TR. Utilising the proposed high-throughput imaging platform with sliding window reconstruction, we were also able to observe the much-debated initial dips in our of MRI data. Combined with methods to further improve SNR, the proposed system will enable efficient real-time, interactive, high-throughput of MRI studies.

Optimal compressed sensing reconstructions of fMRI using 2D deterministic and stochastic sampling geometries

BACKGROUND

Compressive sensing can provide a promising framework for accelerating fMRI image acquisition by allowing reconstructions from a limited number of frequency-domain samples. Unfortunately, the majority of compressive sensing studies are based on stochastic sampling geometries that cannot guarantee fast acquisitions that are needed for fMRI. The purpose of this study is to provide a comprehensive optimization framework that can be used to determine the optimal 2D stochastic or deterministic sampling geometry, as well as to provide optimal reconstruction parameter values for guaranteeing image quality in the reconstructed images.

METHODS

We investigate the use of frequency-space (k-space) sampling based on: (i) 2D deterministic geometries of dyadic phase encoding (DPE) and spiral low pass (SLP) geometries, and (ii) 2D stochastic geometries based on random phase encoding (RPE) and random samples on a PDF (RSP). Overall, we consider over 36 frequency-sampling geometries at different sampling rates. For each geometry, we compute optimal reconstructions of single BOLD fMRI ON & OFF images, as well as BOLD fMRI activity maps based on the difference between the ON and OFF images. We also provide an optimization framework for determining the optimal parameters and sampling geometry prior to scanning.

RESULTS

For each geometry, we show that reconstruction parameter optimization converged after just a few iterations. Parameter optimization led to significant image quality improvements. For activity detection, retaining only 20.3% of the samples using SLP gave a mean PSNR value of 57.58 dB. We also validated this result with the use of the Structural Similarity Index Matrix (SSIM) image quality metric. SSIM gave an excellent mean value of 0.9747 (max = 1). This indicates that excellent reconstruction results can be achieved. Median parameter values also gave excellent reconstruction results for the ON/OFF images using the SLP sampling geometry (mean SSIM > =0.93). Here, median parameter values were obtained using mean-SSIM optimization. This approach was also validated using leave-one-out.

CONCLUSIONS

We have found that compressive sensing parameter optimization can dramatically improve fMRI image reconstruction quality. Furthermore, 2D MRI scanning based on the SLP geometries consistently gave the best image reconstruction results. The implication of this result is that less complex sampling geometries will suffice over random sampling. We have also found that we can obtain stable parameter regions that can be used to achieve specific levels of image reconstruction quality when combined with specific k-space sampling geometries. Furthermore, median parameter values can be used to obtain excellent reconstruction results.

Enhancement of temporal resolution and BOLD sensitivity in real-time fMRI using multi-slab echo-volumar imaging

In this study, a new approach to high-speed fMRI using multi-slab echo-volumar imaging (EVI) is developed that minimizes geometrical image distortion and spatial blurring, and enables nonaliased sampling of physiological signal fluctuation to increase BOLD sensitivity compared to conventional echo-planar imaging (EPI). Real-time fMRI using whole brain 4-slab EVI with 286 ms temporal resolution (4mm isotropic voxel size) and partial brain 2-slab EVI with 136 ms temporal resolution (4×4×6 mm(3) voxel size) was performed on a clinical 3 Tesla MRI scanner equipped with 12-channel head coil. Four-slab EVI of visual and motor tasks significantly increased mean (visual: 96%, motor: 66%) and maximum t-score (visual: 263%, motor: 124%) and mean (visual: 59%, motor: 131%) and maximum (visual: 29%, motor: 67%) BOLD signal amplitude compared with EPI. Time domain moving average filtering (2s width) to suppress physiological noise from cardiac and respiratory fluctuations further improved mean (visual: 196%, motor: 140%) and maximum (visual: 384%, motor: 200%) t-scores and increased extents of activation (visual: 73%, motor: 70%) compared to EPI. Similar sensitivity enhancement, which is attributed to high sampling rate at only moderately reduced temporal signal-to-noise ratio (mean: -52%) and longer sampling of the BOLD effect in the echo-time domain compared to EPI, was measured in auditory cortex. Two-slab EVI further improved temporal resolution for measuring task-related activation and enabled mapping of five major resting state networks (RSNs) in individual subjects in 5 min scans. The bilateral sensorimotor, the default mode and the occipital RSNs were detectable in time frames as short as 75 s. In conclusion, the high sampling rate of real-time multi-slab EVI significantly improves sensitivity for studying the temporal dynamics of hemodynamic responses and for characterizing functional networks at high field strength in short measurement times.

Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty

Simultaneous multislice Echo Planar Imaging (EPI) acquisition using parallel imaging can decrease the acquisition time for diffusion imaging and allow full-brain, high-resolution functional MRI (fMRI) acquisitions at a reduced repetition time (TR). However, the unaliasing of simultaneously acquired, closely spaced slices can be difficult, leading to a high g-factor penalty. We introduce a method to create interslice image shifts in the phase encoding direction to increase the distance between aliasing pixels. The shift between the slices is induced using sign- and amplitude-modulated slice-select gradient blips simultaneous with the EPI phase encoding blips. This achieves the desired shifts but avoids an undesired "tilted voxel" blurring artifact associated with previous methods. We validate the method in 3× slice-accelerated spin-echo and gradient-echo EPI at 3 T and 7 T using 32-channel radio frequency (RF) coil brain arrays. The Monte-Carlo simulated average g-factor penalty of the 3-fold slice-accelerated acquisition with interslice shifts is <1% at 3 T (compared with 32% without slice shift). Combining 3× slice acceleration with 2× inplane acceleration, the g-factor penalty becomes 19% at 3 T and 10% at 7 T (compared with 41% and 23% without slice shift). We demonstrate the potential of the method for accelerating diffusion imaging by comparing the fiber orientation uncertainty, where the 3-fold faster acquisition showed no noticeable degradation.

Rapid 3D radial multi-echo functional magnetic resonance imaging

Functional magnetic resonance imaging with readouts at multiple echo times is useful for optimizing sensitivity across a range of tissue T2* values as well as for quantifying T2*. With single-shot acquisitions, both the minimum TE value and the number of TEs which it is possible to collect within a single TR are limited by the long echo-planar imaging readout duration (20-40 ms). In the present work, a multi-shot 3D radial acquisition which allows rapid whole-brain imaging at a range of echo times is proposed. The proposed 3D k-space coverage is implemented via a series of rotations of a single 2D interleaf. Data can be reconstructed at a variety of temporal resolutions from a single dataset, allowing for a flexible tradeoff between temporal resolution and BOLD contrast to noise ratio. It is demonstrated that whole-brain images at 5 echo times (TEs from 10 to 46 ms) can be acquired at a temporal rate as rapid as 400 ms/volume (3.75 mm isotropic resolution). Activation maps for a simultaneous motor/visual task consistent across multiple acceleration factors are obtained. Weighted combination of the echoes results in Z-scores that are significantly (p=0.016) higher than those resulting from any of the individual echo time images.

In contrast to BOLD: signal enhancement by extravascular water protons as an alternative mechanism of endogenous fMRI signal change

Despite the popularity and widespread application of functional magnetic resonance imaging (fMRI) in recent years, the physiological bases of signal change are not yet fully understood. Blood oxygen level-dependant (BOLD) contrast - attributed to local changes in blood flow and oxygenation, and therefore magnetic susceptibility - has become the most prevalent means of functional neuroimaging. However, at short echo times, spin-echo sequences show considerable deviations from the BOLD model, implying a second, non-BOLD component of signal change. This has been dubbed "signal enhancement by extravascular water protons" (SEEP) and is proposed to result from proton-density changes associated with cellular swelling. Given that such changes are independent of magnetic susceptibility, SEEP may offer new and improved opportunities for carrying out fMRI in regions with close proximity to air-tissue and/or bone-tissue interfaces (e.g., the prefrontal cortex and spinal cord), as well as regions close to large blood vessels, which may not be ideally suited for BOLD imaging. However, because of the interdisciplinary nature of the literature, there has yet to be a thorough synthesis, tying together the various and sometimes disparate aspects of SEEP theory. As such, we aim to provide a concise yet comprehensive overview of SEEP, including recent and compelling evidence for its validity, its current applications and its future relevance to the rapidly expanding field of functional neuroimaging. Before presenting the evidence for a non-BOLD component of endogenous functional contrast, and to enable a more critical review for the nonexpert reader, we begin by reviewing the fundamental principles underlying BOLD theory.

What's new in neuroimaging methods?

The rapid advancement of neuroimaging methodology and its growing availability has transformed neuroscience research. The answers to many questions that we ask about how the brain is organized depend on the quality of data that we are able to obtain about the locations, dynamics, fluctuations, magnitudes, and types of brain activity and structural changes. In this review an attempt is made to take a snapshot of the cutting edge of a small component of the very rapidly evolving field of neuroimaging. For each area covered, a brief context is provided along with a summary of a few of the current developments and issues. Then, several outstanding papers, published in the past year or so, are described, providing an example of the directions in which each area is progressing. The areas covered include functional magnetic resonance imaging (fMRI), voxel-based morphometry (VBM), diffusion tensor imaging (DTI), electroencephalography (EEG), magnetoencephalography (MEG), optical imaging, and positron emission tomography (PET). More detail is included on fMRI; its subsections include fMRI interpretation, new fMRI contrasts, MRI technology, MRI paradigms and processing, and endogenous oscillations in fMRI.