Locally Low-Rank Denoising of Multi-Echo Functional MRI Data With Application in Resting-State Analysis.

OBJECTIVES: Locally low-rank (LLR) denoising of functional magnetic resonance imaging (fMRI) time series image data is extended to multi-echo (ME) data. The proposed method extends the capabilities of non-physiologic noise suppression beyond single-echo applications with a dedicated ME algorithm. MATERIALS AND METHODS: Following an institutional review board (IRB) approved protocol, resting-state fMRI data were acquired in 7 healthy subjects. A compact 3T scanner enabled whole-brain acquisition of multiband ME fMRI data at high spatial resolution (1.4 × 1.4 × 2.8 mm 3 ) with a 1810 ms repetition time (TR). Image data were denoised with ME-LLR preceding functional processing. The results of connectivity maps generated from denoised data were compared with maps generated with equivalent processing of non-denoised images. To assess ME-LLR as a method to reduce scan time, comparisons were made between maps computed from image data with full and retrospectively truncated durations. Assessments were completed with seed-based connectivity analyses using echo-combined image data. In a feasibility assessment, nondenoised and denoised full-duration echo-combined data were equivalently processed with independent component analysis (ICA) and compared. RESULTS: ME-LLR denoising yielded strengthened resting-state network connectivity maps after nuisance regression and seed-based connectivity analysis. In assessing ME-LLR as a scan reduction mechanism, maps generated from denoised data at half scan time showed comparable quality with maps generated from full-duration, non-denoised data, at both single subject and group levels. ME-LLR substantially increased temporal signal-to-noise ratio (tSNR) for image data respective to each individual echo and for image data after nuisance regression. Among echo-specific image volumes, increases in tSNR yielded by ME-LLR were most pronounced for image data with the longest echo time and thereby lowest SNR. ICA showed resting-state networks consistently identified between non-denoised and denoised data, with clearer demarcation of networks for ME-LLR. CONCLUSIONS: ME-LLR is demonstrated to suppress non-physiologic noise, enhance functional connectivity map quality, and could potentially facilitate scan time reduction in ME-fMRI.

Improved Resting-State Functional MRI Using Multi-Echo Echo-Planar Imaging on a Compact 3T MRI Scanner with High-Performance Gradients.

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

Minimizing susceptibility-induced BOLD sensitivity loss in multi-band accelerated fMRI using point spread function mapping and gradient reversal.

Objective. Interleaved reverse-gradient fMRI (RG-fMRI) with a point-spread-function (PSF) mapping-based distortion correction scheme has the potential to minimize signal loss in echo-planar-imaging (EPI). In this work, the RG-fMRI is further improved by imaging protocol optimization and application of reverse Fourier acquisition.Approach. Multi-band imaging was adapted for RG-fMRI to improve the temporal and spatial resolution. To better understand signal dropouts in forward and reverse EPIs, a simple theoretical relationship between echo shift and geometric distortion was derived and validated by the reliable measurements using PSF mapping method. After examining practical imaging protocols for RG-fMRI in three subjects on both a conventional whole-body and a high-performance compact 3 T, the results were compared and the feasibility to further improve the RG-fMRI scheme were explored. High-resolution breath-holding RG-fMRI was conducted with nine subjects on the compact 3 T and the fMRI reliability improvement in high susceptibility brain regions was demonstrated. Finally, reverse Fourier acquisition was applied to RG-fMRI, and its benefit was assessed by a simulation study based on the breath-holding RG-fMRI data.Main results. The temporal and spatial resolution of the multi-band RG-fMRI became feasible for whole-brain fMRI. Echo shift measurements from PSF mapping well estimated signal dropout effects in the EPI pair and were useful to further improve the RG-fMRI scheme. Breath-holding RG-fMRI demonstrated improved fMRI reliability in high susceptibility brain regions. Reverse partial Fourier acquisition omitting the late echoes could further improve the temporal or spatial resolution for RG-fMRI without noticeable signal degradation and spatial resolution loss.Significance. With the improved imaging scheme, RG-fMRI could reliably investigate the functional mechanisms of the human brain in the temporal and frontal areas suffering from susceptibility-induced functional sensitivity loss.

Enhanced clinical task-based fMRI metrics through locally low-rank denoising of complex-valued data.

OBJECTIVE: This study investigates a locally low-rank (LLR) denoising algorithm applied to source images from a clinical task-based functional MRI (fMRI) exam before post-processing for improving statistical confidence of task-based activation maps. METHODS: Task-based motor and language fMRI was obtained in eleven healthy volunteers under an IRB approved protocol. LLR denoising was then applied to raw complex-valued image data before fMRI processing. Activation maps generated from conventional non-denoised (control) data were compared with maps derived from LLR-denoised image data. Four board-certified neuroradiologists completed consensus assessment of activation maps; region-specific and aggregate motor and language consensus thresholds were then compared with nonparametric statistical tests. Additional evaluation included retrospective truncation of exam data without and with LLR denoising; a ROI-based analysis tracked t-statistics and temporal SNR (tSNR) as scan durations decreased. A test-retest assessment was performed; retest data were matched with initial test data and compared for one subject. RESULTS: fMRI activation maps generated from LLR-denoised data predominantly exhibited statistically significant (p = 4.88×10-4 to p = 0.042; one p = 0.062) increases in consensus t-statistic thresholds for motor and language activation maps. Following data truncation, LLR data showed task-specific increases in t-statistics and tSNR respectively exceeding 20 and 50% compared to control. LLR denoising enabled truncation of exam durations while preserving cluster volumes at fixed thresholds. Test-retest showed variable activation with LLR data thresholded higher in matching initial test data. CONCLUSION: LLR denoising affords robust increases in t-statistics on fMRI activation maps compared to routine processing, and offers potential for reduced scan duration while preserving map quality.

New analysis method for functional brain imaging: White noise removed T2* variation mapping using multi-echo EPI.

BACKGROUND: Generally, the analysis of functional magnetic resonance imaging (fMRI) using echo-planar imaging (EPI) data is based on independent component analysis (ICA) and the general linear model (GLM). The application of these two approaches is highly independent, like GLM is for task-related activation mapping, and ICA is for resting-state imaging. Herein, we propose white noise-removed T2*-variation mapping as a new analysis method for fMRI that integrates the two conventional mapping approaches. NEW METHOD: We derived the standard deviation to the mean-square ratio of the true T2* signal from the multi-echo EPI (ME-EPI) dataset. For the true T2*-variation-based value, we removed the S0 (initial signal intensity) and white noise component from the variation in the EPI signal using signal-coherence analysis of the echo time (TE) dataset and slope analysis of the TE-variated coefficient of variation of the ME-EPI dataset. RESULTS: The activation mapping for a visual task and resting-state imaging by the proposed method showed the reliable activation map in the visual cortex area and area for the typical default mode network, with white noise and the S0 component removed. COMPARISON WITH EXISTING METHODS: Conventional analyses for fMRI cannot be applied to both activation mapping and resting-state imaging, with white noise removed, while the proposed method can be applied. CONCLUSIONS: We demonstrated white noise-removed true T2*-variation-based mapping as a new functional brain analysis approach. We expect the method allows studying in which that the association between task timing and brain activity is somewhat uncertain, such as studies of emotion and awareness.

Application of Adaptive Image Receive Coil Technology for Whole-Brain Imaging.

OBJECTIVE. The Adaptive Image Receive (AIR) radiofrequency coil is an emergent technology that is lightweight and flexible and exhibits electrical characteristics that overcome many of the limitations of traditional rigid coil designs. The purpose of this study was to apply the AIR coil for whole-brain imaging and compare the performance of a prototype AIR coil array with the performance of conventional head coils. SUBJECTS AND METHODS. A phantom and 15 healthy adult participants were imaged. A prototype 16-channel head AIR coil was compared with conventional 8-and 32-channel head coils using clinically available MRI sequences. During consensus review, two board-certified neuroradiologists graded the AIR coil compared with an 8-channel coil and a 32-channel coil on a 5-point ordinal scale in multiple categories. One- and two-sided Wilcoxon signed rank tests were performed. Noise covariance matrices and geometry factor (g-factor) maps were calculated. RESULTS. The signal-to-noise ratio, structural sharpness, and overall image quality scores of the prototype 16-channel AIR coil were better than those of the 8-channel coil but were not as good as those of the 32-channel coil. Noise covariance matrices showed stable performance of the AIR coil across participants. The median g-factors for the 16-channel AIR coil were, overall, less than those of the 8-channel coil but were greater than those of the 32-channel coil. CONCLUSION. On average, the prototype 16-channel head AIR coil outperformed a conventional 8-channel head coil but did not perform as well as a conventional 32-channel head coil. This study shows the feasibility of the novel AIR coil technology for imaging the brain and provides insight for future coil design improvements.

The benefit of high-performance gradients on echo planar imaging for BOLD-based resting-state functional MRI.

Improved gradient performance in an MRI system reduces distortion in echo planar imaging (EPI), which has been a key imaging method for functional studies. A lightweight, low-cryogen compact 3T MRI scanner (C3T) is capable of achieving 80 mT m-1 gradient amplitude with 700 T m-1 s-1 slew rate, in comparison with a conventional whole-body 3T MRI scanner (WB3T, 50 mT m-1 with 200 T m-1 s-1). We investigated benefits of the high-performance gradients in a high-spatial-resolution (1.5 mm isotropic) functional MRI study. Reduced echo spacing in the EPI pulse sequence inherently leads to less severe geometric distortion, which provided higher accuracy than with WB3T for registration between EPI and anatomical images. The cortical coverage of C3T datasets was improved by more accurate signal depiction (i.e. less dropout or pile-up). Resting-state functional analysis results showed that greater magnitude and extent in functional connectivity (FC) for the C3T than the WB3T when the selected seed region is susceptible to distortions, while the FC matrix for well-known brain networks showed little difference between the two scanners. This shows that the improved quality in EPI is particularly valuable for studying certain brain regions typically obscured by severe distortion.

Low-temperature large-area fabrication of ZnO nanowires on flexible plastic substrates by solution-processible metal-seeded hydrothermal growth.

We have developed the low-temperature conformal ZnO nanowire fabrication on flexible plastic substrates by utilizing the solution-processible metal seed-assisted hydrothermal ZnO crystallization. Structural evolution of ZnO nanowires controlled by major parameters involving growth temperature, growth time, and seed coating condition, has been systematically investigated towards uniform and large-area growth of conformal ZnO nanowires. Direct ZnO nanowire growth on flexible plastics without undergoing the high-temperature seed sintering has been realized by developing the low-temperature Ag-seeded hydrothermal ZnO nanowire growth. The nanoporous Ag layer favorable for ZnO crystal nucleation and continued nanowire growth can be reduced from the Ag ion solution coating at the temperature as low as 130 °C. This tactfully enables the selective hydrothermal growth of ZnO nanowires on the Ag patterns on flexible plastics. Such an all-solution-processible low-temperature fabrication protocol may provide an essential and practical solution to develop many diverse applications including wearable and transparent electronics, sensors, and photocatalytic devices. As one example, we demonstrate that a transparent UV sensor can be devised based on the ZNW growth on the Ag micromesh electrode.

Reducing PNS with minimal performance penalties via simple pulse sequence modifications on a high-performance compact 3T scanner.

One of the major concerns associated with high-performance gradients is peripheral nerve stimulation (PNS) of the subject during MRI exams. Since the installation, more than 680 volunteer subjects (patients and controls) have been scanned on a compact 3 T MRI system with high-performance gradients, capable of 80 mT m-1 gradient amplitude and 700 T m-1 s-1 slew rate simultaneously. Despite PNS concerns associated with the high-performance gradients, due to the smaller physical dimensions of the gradient coils, minimal or no PNS sensation was reported with most pulse sequences. The exception was PNS reported by only five of 252 subjects (about 2%) scanned with a specific 3D fast spin echo pulse sequence (3DFLAIR). Rather than derating the entire system performance across all pulse sequences and all gradient lobes, we addressed reported PNS effect with a simple and specific modification to the targeted lobes of the problematic pulse sequence. in addition, the PNS convolutional model was adapted to predict sequence-specific PNS threshold level and its reduction after derating. The effectiveness of the targeted pulse sequence modification was demonstrated by successfully re-scanning four of the subjects who previously reported PNS sensations without further reported PNS. The pulse sequence modification did not result in noticeable degradation of image quality or substantial increase in scan time. The results demonstrated that PNS was rarely reported on the compact 3 T, and when it was, utilizing a specific modification of the gradient waveform causing PNS was an effective strategy, rather than derating the performance of the entire gradient system.

Distortion-free imaging: A double encoding method (DIADEM) combined with multiband imaging for rapid distortion-free high-resolution diffusion imaging on a compact 3T with high-performance gradients.

BACKGROUND: Distortion-free, high-resolution diffusion imaging using DIADEM (Distortion-free Imaging: A Double Encoding Method), proposed recently, has great potential for clinical applications. However, it can suffer from prolonged scan times and its reliability for quantitative diffusion imaging has not been evaluated. PURPOSE: To investigate the clinical feasibility of DIADEM-based high-resolution diffusion imaging on a novel compact 3T (C3T) by evaluating the reliability of quantitative diffusion measurements and utilizing both the high-performance gradients (80 mT/m, 700 T/m/s) and the sequence optimization with the navigator acquisition window reduction and simultaneous multislice (multiband) imaging. STUDY TYPE: Prospective feasibility study. PHANTOM/SUBJECTS: Diffusion quality control phantom scans to evaluate the reliability of quantitative diffusion measurements; 36 normal control scans for B0 -field mapping; six healthy and two patient subject scans with a brain tumor for comparisons of diffusion and anatomical imaging. FIELD STRENGTH/SEQUENCE: 3T; the standard single-shot echo-planar-imaging (EPI), multishot DIADEM diffusion, and anatomical (2D-FSE [fast-spin-echo], 2D-FLAIR [fluid-attenuated-inversion-recovery], and 3D-MPRAGE [magnetization prepared rapid acquisition gradient echo]) imaging. ASSESSMENT: The scan time reduction, the reliability of quantitative diffusion measurements, and the clinical efficacy for high-resolution diffusion imaging in healthy control and brain tumor volunteers. STATISTICAL TEST: Bland-Altman analysis. RESULTS: The scan time for high in-plane (0.86 mm2 ) resolution, distortion-free, and whole brain diffusion imaging were reduced from 10 to 5 minutes with the sequence optimizations. All of the mean apparent diffusion coefficient (ADC) values in phantom were within the 95% confidence interval in the Bland-Altman plot. The proposed acquisition with a total off-resonance coverage of 597.2 Hz wider than the expected bandwidth of 500 Hz in human brain could yield a distortion-free image without foldover artifacts. Compared with EPI, therefore, this approach allowed direct image matching with the anatomical images and enabled improved delineation of the tumor boundaries. DATA CONCLUSION: The proposed high-resolution diffusion imaging approach is clinically feasible on C3T due to a combination of hardware and sequence improvements. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;51:296-310.

The effect of spiral trajectory correction on pseudo-continuous arterial spin labeling with high-performance gradients on a compact 3T scanner.

PURPOSE: To demonstrate the feasibility of pseudo-continuous arterial-spin-labeled (pCASL) imaging with 3D fast-spin-echo stack-of-spirals on a compact 3T scanner (C3T), to perform trajectory correction for eddy-current-induced deviations in the spiral readout of pCASL imaging, and to assess the correction effect on perfusion-related images with high-performance gradients (80 mT/m, 700T/m/s) of the C3T. METHODS: To track eddy-current-induced artifacts with Archimedean spiral readout, the spiral readout in pCASL imaging was performed with 5 different peak gradient slew rate (Smax ) values ranging from 70 to 500 T/m/s. The trajectory for each Smax was measured using a dynamic field camera and applied in a density-compensated gridding image reconstruction in addition to the nominal trajectory. The effect of the trajectory correction was assessed with perfusion-weighted (ΔM) images and proton-density-weighted images as well as cerebral blood flow (CBF) maps, obtained from 10 healthy volunteers. RESULTS: Blurring artifact on ΔM images was mitigated by the trajectory correction. CBF values on the left and right calcarine cortices showed no significant difference after correction. Also, the signal-to-noise ratio of ΔM images improved, on average, by 7.6% after correction (P < .001). The greatest improvement of 12.1% on ΔM images was achieved with a spiral readout using Smax of 300~400 T/m/s. CONCLUSION: Eddy currents can cause spiral trajectory deviation, which leads to deformation of the CBF map even in cases of low value Smax . The trajectory correction for spiral-readout-based pCASL produces more reliable results for perfusion imaging. These results suggest that pCASL is feasible on C3T with high-performance gradients.

Estimation of vocational aptitudes using functional brain networks.

The success of human life in modern society is highly dependent on occupation. Therefore, it is very important for people to identify and develop a career plan that best suits their aptitude. Traditional test batteries for vocational aptitudes are not oriented to measure developmental changes in job suitability because repeated measurements can introduce bias as the content of the test batteries is learned. In this study, we attempted to objectively assess vocational aptitudes by measuring functional brain networks and identified functional brain networks that intrinsically represented vocational aptitudes for 19 job divisions in a General Aptitude Test Battery. In addition, we derived classifiers based on these networks to predict the aptitudes of our test participants for each job division. Our results suggest that the measurement of brain function can indeed yield an objective evaluation of vocational aptitudes; this technique will enable a person to follow changes in one's job suitability with additional training or learning, paving a new way to advise people on career development.

A Set of Functional Brain Networks for the Comprehensive Evaluation of Human Characteristics.

Many human characteristics must be evaluated to comprehensively understand an individual, and measurements of the corresponding cognition/behavior are required. Brain imaging by functional MRI (fMRI) has been widely used to examine brain function related to human cognition/behavior. However, few aspects of cognition/behavior of individuals or experimental groups can be examined through task-based fMRI. Recently, resting state fMRI (rs-fMRI) signals have been shown to represent functional infrastructure in the brain that is highly involved in processing information related to cognition/behavior. Using rs-fMRI may allow diverse information about the brain through a single MRI scan to be obtained, as rs-fMRI does not require stimulus tasks. In this study, we attempted to identify a set of functional networks representing cognition/behavior that are related to a wide variety of human characteristics and to evaluate these characteristics using rs-fMRI data. If possible, these findings would support the potential of rs-fMRI to provide diverse information about the brain. We used resting-state fMRI and a set of 130 psychometric parameters that cover most human characteristics, including those related to intelligence and emotional quotients and social ability/skill. We identified 163 brain regions by VBM analysis using regression analysis with 130 psychometric parameters. Next, using a 163 × 163 correlation matrix, we identified functional networks related to 111 of the 130 psychometric parameters. Finally, we made an 8-class support vector machine classifiers corresponding to these 111 functional networks. Our results demonstrate that rs-fMRI signals contain intrinsic information about brain function related to cognition/behaviors and that this set of 111 networks/classifiers can be used to comprehensively evaluate human characteristics.

Estimation of physiological sources of nonlinearity in blood oxygenation level-dependent contrast signals.

Blood oxygenation level-dependent (BOLD) contrast appears through a variation in the transverse relaxation rate of magnetic resonance signals induced by neurovascular coupling and is known to have nonlinear characteristics along echo time (TE) due to the intra-vasculature. However, the physiological causes of this nonlinearity are unclear. We attempted to estimate the physiological information related to the nonlinearity of BOLD signals by using a two-compartment model. For this purpose, we used a multi-echo gradient-echo echo-planar imaging sequence and developed a computational method to estimate the physiological information from the TE-dependent BOLD signals. The results showed that the average chemical exchange time in the intra-vasculature varied during stimulation, which might be the essential source of the nonlinearity.

Fast Imaging Technique for fMRI: Consecutive Multishot Echo Planar Imaging Accelerated with GRAPPA Technique.

This study was to evaluate the proposed consecutive multishot echo planar imaging (cmsEPI) combined with a parallel imaging technique in terms of signal-to-noise ratio (SNR) and acceleration for a functional imaging study. We developed cmsEPI sequence using both consecutively acquired multishot EPI segments and variable flip angles to minimize the delay between segments and to maximize the SNR, respectively. We also combined cmsEPI with the generalized autocalibrating partially parallel acquisitions (GRAPPA) method. Temporal SNRs were measured at different acceleration factors and number of segments for functional sensitivity evaluation. We also examined the geometric distortions, which inherently occurred in EPI sequence. The practical acceleration factors, R = 2 or R = 3, of the proposed technique improved the temporal SNR by maximally 18% in phantom test and by averagely 8.2% in in vivo experiment, compared to cmsEPI without parallel imaging. The data collection time was decreased in inverse proportion to the acceleration factor as well. The improved temporal SNR resulted in better statistical power when evaluated on the functional response of the brain. In this study, we demonstrated that the combination of cmsEPI with the parallel imaging technique could provide the improved functional sensitivity for functional imaging study, compensating for the lower SNR by cmsEPI.

Microscopic functional specificity can be predicted from fMRI signals in ventral visual areas.

Functional areas specialized for recognition can be activated by a non-preferred stimulus as well as a preferred stimulus. The functional magnetic resonance imaging signals detected in response to different stimuli in an area may have the same or different amplitudes. However, it is uncertain whether the responses originate from the same neuronal populations or heterogeneous ones. To address this concern, we propose a novel method that uses multi-echo echo-planar imaging sequences to evaluate changes in the transverse relaxation profile caused by stimulation. According to this method, the areas related with visual recognition, i.e. fusiform face area and parahippocampal place area, have different transverse relaxation profiles to preferred and non-preferred stimuli, which can be considered as reflecting a difference in neuronal population processing stimuli in those areas. The proposed method can be useful for probing the microscopic functional specificity of brain areas.