Quantification and correction of respiration induced dynamic field map changes in fMRI using 3D single shot techniques

Single-shot Echo Planar Time-resolved Imaging for multi-echo functional MRI and distortion-free diffusion imaging

Purpose

To develop EPTI, a multi-shot distortion-free multi-echo imaging technique, into a single-shot acquisition to achieve improved robustness to motion and physiological noise, increased temporal resolution, and high SNR efficiency for dynamic imaging applications.

Methods

A new spatiotemporal encoding was developed to achieve single-shot EPTI by enhancing spatiotemporal correlation in k-t space. The proposed single-shot encoding improves reconstruction conditioning and sampling efficiency, with additional optimization under various accelerations to achieve optimized performance. To achieve high SNR efficiency, continuous readout with minimized deadtime was employed that begins immediately after excitation and extends for an SNR-optimized length. Moreover, k-t partial Fourier and simultaneous multi-slice acquisition were integrated to further accelerate the acquisition and achieve high spatial and temporal resolution.

Results

We demonstrated that ss-EPTI achieves higher tSNR efficiency than multi-shot EPTI, and provides distortion-free imaging with densely-sampled multi-echo images at resolutions ~1.25-3 mm at 3T and 7T-with high SNR efficiency and with comparable temporal resolutions to ss-EPI. The ability of ss-EPTI to eliminate dynamic distortions common in EPI also further improves temporal stability. For fMRI, ss-EPTI also provides early-TE images (e.g., 2.9ms) to recover signal-intensity and functional-sensitivity dropout in challenging regions. The multi-echo images provide TE-dependent information about functional fluctuations, successfully distinguishing noise-components from BOLD signals and further improving tSNR. For diffusion MRI, ss-EPTI provides high-quality distortion-free diffusion images and multi-echo diffusion metrics.

Conclusion

ss-EPTI provides distortion-free imaging with high image quality, rich multi-echo information, and enhanced efficiency within comparable temporal resolution to ss-EPI, offering a robust and efficient acquisition for dynamic imaging.

Three-dimensional echo-shifted EPI with simultaneous blip-up and blip-down acquisitions for correcting geometric distortion

PURPOSE

EPI with blip-up/down acquisition (BUDA) can provide high-quality images with minimal distortions by using two readout trains with opposing phase-encoding gradients. Because of the need for two separate acquisitions, BUDA doubles the scan time and degrades the temporal resolution when compared to single-shot EPI, presenting a major challenge for many applications, particularly fMRI. This study aims at overcoming this challenge by developing an echo-shifted EPI BUDA (esEPI-BUDA) technique to acquire both blip-up and blip-down datasets in a single shot.

METHODS

A 3D esEPI-BUDA pulse sequence was designed by using an echo-shifting strategy to produce two EPI readout trains. These readout trains produced a pair of k-space datasets whose k-space trajectories were interleaved with opposite phase-encoding gradient directions. The two k-space datasets were separately reconstructed using a 3D SENSE algorithm, from which time-resolved B0 -field maps were derived using TOPUP in FSL and then input into a forward model of joint parallel imaging reconstruction to correct for geometric distortion. In addition, Hankel structured low-rank constraint was incorporated into the reconstruction framework to improve image quality by mitigating the phase errors between the two interleaved k-space datasets.

RESULTS

The 3D esEPI-BUDA technique was demonstrated in a phantom and an fMRI study on healthy human subjects. Geometric distortions were effectively corrected in both phantom and human brain images. In the fMRI study, the visual activation volumes and their BOLD responses were comparable to those from conventional 3D echo-planar images.

CONCLUSION

The improved imaging efficiency and dynamic distortion correction capability afforded by 3D esEPI-BUDA are expected to benefit many EPI applications.

Improving robustness of 3D multi-shot EPI by structured low-rank reconstruction of segmented CAIPI sampling for fMRI at 7T

Three-dimensional (3D) encoding methods are increasingly being explored as alternatives to two-dimensional (2D) multi-slice acquisitions in fMRI, particularly in cases where high isotropic resolution is needed. 3D multi-shot EPI acquisition, as the workhorse of 3D fMRI imaging, is susceptible to physiological fluctuations which can induce inter-shot phase variations, and thus reducing the achievable tSNR, negating some of the benefit of 3D encoding. This issue can be particularly problematic at ultra-high fields like 7T, which have more severe off-resonance effects. In this work, we aim to improve the temporal stability of 3D multi-shot EPI at 7T by improving its robustness to inter-shot phase variations. We presented a 3D segmented CAIPI sampling trajectory ("seg-CAIPI") and an improved reconstruction method based on Hankel structured low-rank matrix recovery. Simulation and in-vivo results demonstrate that the combination of the seg-CAIPI sampling scheme and the proposed structured low-rank reconstruction is a promising way to effectively reduce the unwanted temporal variance induced by inter-shot physiological fluctuations, and thus improve the robustness of 3D multi-shot EPI for fMRI.

Unsupervised physiological noise correction of functional magnetic resonance imaging data using phase and magnitude information (PREPAIR)

Of the sources of noise affecting blood oxygen level-dependent functional magnetic resonance imaging (fMRI), respiration and cardiac fluctuations are responsible for the largest part of the variance, particularly at high and ultrahigh field. Existing approaches to removing physiological noise either use external recordings, which can be unwieldy and unreliable, or attempt to identify physiological noise from the magnitude fMRI data. Data-driven approaches are limited by sensitivity, temporal aliasing, and the need for user interaction. In the light of the sensitivity of the phase of the MR signal to local changes in the field stemming from physiological processes, we have developed an unsupervised physiological noise correction method using the information carried in the phase and the magnitude of echo-planar imaging data. Our technique, Physiological Regressor Estimation from Phase and mAgnItude, sub-tR (PREPAIR) derives time series signals sampled at the slice TR from both phase and magnitude images. It allows physiological noise to be captured without aliasing, and efficiently removes other sources of signal fluctuations not related to physiology, prior to regressor estimation. We demonstrate that the physiological signal time courses identified with PREPAIR agree well with those from external devices and retrieve challenging cardiac dynamics. The removal of physiological noise was as effective as that achieved with the most used approach based on external recordings, RETROICOR. In comparison with widely used recording-free physiological noise correction tools-PESTICA and FIX, both performed in unsupervised mode-PREPAIR removed significantly more respiratory and cardiac noise than PESTICA, and achieved a larger increase in temporal signal-to-noise-ratio at both 3 and 7 T.

Increased very low frequency pulsations and decreased cardiorespiratory pulsations suggest altered brain clearance in narcolepsy

Background

Narcolepsy is a chronic neurological disease characterized by daytime sleep attacks, cataplexy, and fragmented sleep. The disease is hypothesized to arise from destruction or dysfunction of hypothalamic hypocretin-producing cells that innervate wake-promoting systems including the ascending arousal network (AAN), which regulates arousal via release of neurotransmitters like noradrenalin. Brain pulsations are thought to drive intracranial cerebrospinal fluid flow linked to brain metabolite transfer that sustains homeostasis. This flow increases in sleep and is suppressed by noradrenalin in the awake state. Here we tested the hypothesis that narcolepsy is associated with altered brain pulsations, and if these pulsations can differentiate narcolepsy type 1 from healthy controls.

Methods

In this case-control study, 23 patients with narcolepsy type 1 (NT1) were imaged with ultrafast fMRI (MREG) along with 23 age- and sex-matched healthy controls (HC). The physiological brain pulsations were quantified as the frequency-wise signal variance. Clinical relevance of the pulsations was investigated with correlation and receiving operating characteristic analysis.

Results

We find that variance and fractional variance in the very low frequency (MREG_vlf) band are greater in NT1 compared to HC, while cardiac (MREG_card) and respiratory band variances are lower. Interestingly, these pulsations differences are prominent in the AAN region. We further find that fractional variance in MREG_vlf shows promise as an effective bi-classification metric (AUC = 81.4%/78.5%), and that disease severity measured with narcolepsy severity score correlates with MREG_card variance (R = −0.48, p = 0.0249).

Conclusions

We suggest that our novel results reflect impaired CSF dynamics that may be linked to altered glymphatic circulation in narcolepsy type 1.

The flow of fluid surrounding and inside the human brain is thought to be caused by the movement of brain vessels, breathing and heart rate. These so called brain pulsations are linked to clearing waste from the brain. This process is increased during sleep and suppressed while we are awake. Narcolepsy is a neurological disease where the brain areas regulating being awake and asleep are affected. The diagnosis requires time-consuming hospital tests and is often delayed which has a prolonged negative impact on the patients. Here, we use brain imaging to investigate whether brain pulsations are altered in patients with narcolepsy, and if they can be utilized to differentiate patients with narcolepsy from healthy individuals. We find that narcolepsy affects all brain pulsations, and these findings show promise as an additional diagnostic tool that could help detect the disease earlier.

Järvelä et al. investigate if narcolepsy is associated with altered brain pulsations using ultrafast fMRI. They find differences in the brain pulsations between narcolepsy type 1 patients and healthy controls that may link to altered brain clearance in narcolepsy, have diagnostic potential and correlate with the severity of narcolepsy.

A k-space-based method to measure and correct for temporal B0 field variations in MR temperature imaging

PURPOSE

Present a method to use change in phase in repeated Cartesian k-space measurements to monitor the change in magnetic field for dynamic MR temperature imaging.

METHODS

The method is applied to focused ultrasound heating experiments in a gelatin phantom and an ex vivo salt pork sample, without and with simulated respiratory motion.

RESULTS

In each experiment, phase variations due to B0 field drift and respiration were readily apparent in the measured phase difference. With correction, the SD of the temperature over time was reduced from 0.18°C to 0.14°C (no breathing) and from 0.81°C to 0.22°C (with breathing) for the gelatin phantom, and from 0.68°C to 0.13°C (no breathing) and from 1.06°C to 0.17°C (with breathing) for the pork sample. The accuracy in nonheated regions, assessed as the RMS error deviation from 0°C, improved from 1.70°C to 1.11°C (no breathing) and from 4.73°C to 1.47°C (with breathing) for the gelatin phantom, and from 5.95°C to 0.88°C (no breathing) and from 13.40°C to 1.73°C (with breathing) for the pork sample. The correction did not affect the temperature measurement accuracy in the heated regions.

CONCLUSION

This work demonstrates that phase changes resulting from variations in B0 due to drift and respiration, commonly seen in MR thermometry applications, can be measured directly from 3D Cartesian acquisition methods. The correction of temporal field variations using the presented technique improved temperature accuracy, reduced variability in nonheated regions, and did not reduce accuracy in heated regions.

Cardiovascular Pulsatility Increases in Visual Cortex Before Blood Oxygen Level Dependent Response During Stimulus

The physiological pulsations that drive tissue fluid homeostasis are not well characterized during brain activation. Therefore, we used fast magnetic resonance encephalography (MREG) fMRI to measure full band (0–5 Hz) blood oxygen level-dependent (BOLD_FB) signals during a dynamic visual task in 23 subjects. This revealed brain activity in the very low frequency (BOLD_VLF) as well as in cardiac and respiratory bands. The cardiovascular hemodynamic envelope (CHe) signal correlated significantly with the visual BOLD_VLF response, considered as an independent signal source in the V1-V2 visual cortices. The CHe preceded the canonical BOLD_VLF response by an average of 1.3 (± 2.2) s. Physiologically, the observed CHe signal could mark increased regional cardiovascular pulsatility following vasodilation.

Spectral analysis of physiological brain pulsations affecting the BOLD signal

Physiological pulsations have been shown to affect the global blood oxygen level dependent (BOLD) signal in human brain. While these pulsations have previously been regarded as noise, recent studies show their potential as biomarkers of brain pathology. We used the extended 5 Hz spectral range of magnetic resonance encephalography (MREG) data to investigate spatial and frequency distributions of physiological BOLD signal sources. Amplitude spectra of the global image signals revealed cardiorespiratory envelope modulation (CREM) peaks, in addition to the previously known very low frequency (VLF) and cardiorespiratory pulsations. We then proceeded to extend the amplitude of low frequency fluctuations (ALFF) method to each of these pulsations. The respiratory pulsations were spatially dominating over most brain structures. The VLF pulsations overcame the respiratory pulsations in frontal and parietal gray matter, whereas cardiac and CREM pulsations had this effect in central cerebrospinal fluid (CSF) spaces and major blood vessels. A quasi‐periodic pattern (QPP) analysis showed that the CREM pulsations propagated as waves, with a spatiotemporal pattern differing from that of respiratory pulsations, indicating them to be distinct intracranial physiological phenomenon. In conclusion, the respiration has a dominant effect on the global BOLD signal and directly modulates cardiovascular brain pulsations.

Cardiovascular brain impulses in Alzheimer's disease

Accumulation of amyloid-β is a key neuropathological feature in brain of Alzheimer’s disease patients. Alterations in cerebral haemodynamics, such as arterial impulse propagation driving the (peri)vascular CSF flux, predict future Alzheimer’s disease progression. We now present a non-invasive method to quantify the three-dimensional propagation of cardiovascular impulses in human brain using ultrafast 10 Hz magnetic resonance encephalography. This technique revealed spatio-temporal abnormalities in impulse propagation in Alzheimer’s disease. The arrival latency and propagation speed both differed in patients with Alzheimer’s disease. Our mapping of arterial territories revealed Alzheimer’s disease-specific modifications, including reversed impulse propagation around the hippocampi and in parietal cortical areas. The findings imply that pervasive abnormality in (peri)vascular CSF impulse propagation compromises vascular impulse propagation and subsequently glymphatic brain clearance of amyloid-β in Alzheimer’s disease.

Deconvolution-based distortion correction of EPI using analytic single-voxel point-spread functions

PURPOSE

To develop a postprocessing algorithm that corrects geometric distortions due to spatial variations of the static magnetic field amplitude, B₀ , and effects from relaxation during signal acquisition in EPI.

THEORY AND METHODS

An analytic, complex point-spread function is deduced for k-space trajectories of EPI variants and applied to corresponding acquisitions in a resolution phantom and in human volunteers at 3 T. With the analytic point-spread function and experimental maps of B₀ (and, optionally, the effective transverse relaxation time, T 2 * ) as input, a point-spread function matrix operator is devised for distortion correction by a Thikonov-regularized deconvolution in image space. The point-spread function operator provides additional information for an appropriate correction of the signal intensity distribution. A previous image combination algorithm for acquisitions with opposite phase blip polarities is adapted to the proposed method to recover destructively interfering signal contributions.

RESULTS

Applications of the proposed deconvolution-based distortion correction ("DecoDisCo") algorithm demonstrate excellent distortion corrections and superior performance regarding the recovery of an undistorted intensity distribution in comparison to a multifrequency reconstruction. Examples include full and partial Fourier standard EPI scans as well as double-shot center-out trajectories. Compared with other distortion-correction approaches, DecoDisCo permits additional deblurring to obtain sharper images in cases of significant T 2 * effects.

CONCLUSION

Robust distortion corrections in EPI acquisitions are feasible with high quality by regularized deconvolution with an analytic point-spread function. The general algorithm, which is publicly released on GitHub, can be straightforwardly adapted for specific EPI variants or other acquisition schemes.

Lag Analysis of Fast fMRI Reveals Delayed Information Flow Between the Default Mode and Other Networks in Narcolepsy

Narcolepsy is a chronic neurological disease characterized by dysfunction of the hypocretin system in brain causing disruption in the wake-promoting system. In addition to sleep attacks and cataplexy, patients with narcolepsy commonly report cognitive symptoms while objective deficits in sustained attention and executive function have been observed. Prior resting-state functional magnetic resonance imaging (fMRI) studies in narcolepsy have reported decreased inter/intranetwork connectivity regarding the default mode network (DMN). Recently developed fast fMRI data acquisition allows more precise detection of brain signal propagation with a novel dynamic lag analysis. In this study, we used fast fMRI data to analyze dynamics of inter resting-state network (RSN) information signaling between narcolepsy type 1 patients (NT1, n = 23) and age- and sex-matched healthy controls (HC, n = 23). We investigated dynamic connectivity properties between positive and negative peaks and, furthermore, their anticorrelative (pos-neg) counterparts. The lag distributions were significantly (P < 0.005, familywise error rate corrected) altered in 24 RSN pairs in NT1. The DMN was involved in 83% of the altered RSN pairs. We conclude that narcolepsy type 1 is characterized with delayed and monotonic inter-RSN information flow especially involving anticorrelations, which are known to be characteristic behavior of the DMN regarding neurocognition.

Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder

This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default‐mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large‐scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244–258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc.

Lay Summary

Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra‐fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default‐mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder.

A comparison of static and dynamic ∆B0 mapping methods for correction of CEST MRI in the presence of temporal B0 field variations

PURPOSE

To assess the performance, in the presence of scanner instabilities, of three dynamic correction methods which integrate ∆B₀ mapping into the chemical exchange saturation transfer (CEST) measurement and three established static ∆B₀ -correction approaches.

METHODS

A homogeneous phantom and five healthy volunteers were scanned with a CEST sequence at 7 T. The in vivo measurements were performed twice: first with unaltered system frequency and again applying frequency shifts during the CEST acquisition. In all cases, retrospective voxel-wise ∆B₀ -correction was performed using one intrinsic and two extrinsic [prescans with dual-echo gradient-echo and water saturation shift referencing (WASSR)] static approaches. These were compared with two intrinsic [using phase data directly generated by single-echo or double-echo GRE (gradient-echo) CEST readout (CEST-GRE-2TE)] and one extrinsic [phase from interleaved dual-echo EPI (echo planar imaging) navigator (NAV-EPI-2TE)] dynamic ∆B₀ -correction approaches [allowing correction of each Z-spectral point before magnetization transfer ratio asymmetry (MTR_asym) analysis].

RESULTS

All three dynamic methods successfully mapped the induced drift. The intrinsic approaches were affected by the CEST labeling near water (∆ω < |0.3| ppm). The MTR_asym contrast was distorted by the frequency drift in the brain by up to 0.21%/Hz when static ∆B₀ -corrections were applied, whereas the dynamic ∆B₀ corrections reduced this to <0.01%/Hz without the need of external scans. The CEST-GRE-2TE and NAV-EPI-2TE resulted in highly consistent MTR_asym values with/without drift for all subjects.

CONCLUSION

Reliable correction of scanner instabilities is essential to establish clinical CEST MRI. The three dynamic approaches presented improved the ∆B₀ -correction performance significantly in the presence of frequency drift compared to established static methods. Among them, the self-corrected CEST-GRE-2TE was the most accurate and straightforward to implement.

Sampling Rate Effects on Resting State fMRI Metrics

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling (p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning.

Investigating the accuracy of FatNav-derived estimates of temporal B0 changes and their application to retrospective correction of high-resolution 3D GRE of the human brain at 7T

PURPOSE

To investigate the precision of estimates of temporal variations of magnetic field achievable by double-echo fat image navigators (FatNavs), and their potential application to retrospective correction of 3-dimensional gradient echo-based sequences.

METHODS

Both head motion and temporal changes of B₀ were tracked using double-echo highly accelerated 3-dimensional FatNavs as navigators, allowing estimation of the temporal changes in low spatial-order field coefficients. The accuracy of the method was determined by direct comparison to controlled offsets in the linear imaging gradients. Double-echo FatNavs were also incorporated into a high-resolution, 3-dimensional gradient echo-based sequence to retrospectively correct for both motion and temporal changes in B₀ during natural and deep breathing. The additional scan time was 5 min (a 40% increase). Correction was also investigated using only the first echo of the FatNav to explore the trade-off in accuracy versus scan time.

RESULTS

Excellent accuracy (0.27 Hz, 1.57-2.75 Hz/m) was achieved for tracking field changes, and no significant bias could be observed. Artifacts in the 3-dimensional gradient echo-based images induced by temporal field changes, if present, were effectively reduced using either the field estimates from the double echo or the first echo only from the FatNavs.

CONCLUSION

The FatNavs were shown to be an excellent candidate for accurate, fast, and precise estimation of global field variations for the tested patterns of respiration. Future work will investigate ways to increase the temporal sampling to increase robustness to variations in breathing patterns. Magn Reson Med 80:585-597, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

The clinical relevance of distortion correction in presurgical fMRI at 7T

Presurgical planning with fMRI benefits from increased reliability and the possibility to reduce measurement time introduced by using ultra-high field. Echo-planar imaging suffers, however, from geometric distortions which scale with field strength and potentially give rise to clinically significant displacement of functional activation. We evaluate the effectiveness of a dynamic distortion correction (DDC) method based on unmodified single-echo EPI in the context of simulated presurgical planning fMRI at 7T and compare it with static distortion correction (SDC). The extent of distortion in EPI and activation shifts are investigated in a group of eleven patients with a range of neuropathologies who performed a motor task. The consequences of neglecting to correct images for susceptibility-induced distortions are assessed in a clinical context. It was possible to generate time series of EPI-based field maps which were free of artifacts in the eloquent brain areas relevant to presurgical fMRI, despite the presence of signal dropouts caused by pathologies and post-operative sites. Distortions of up to 5.1mm were observed in the primary motor cortex in raw EPI. These were accurately corrected with DDC and slightly less accurately with SDC. The dynamic nature of distortions in UHF clinical fMRI was demonstrated via investigation of temporal variation in voxel shift maps, confirming the potential inadequacy of SDC based on a single reference field map, particularly in the vicinity of pathologies or in the presence of motion. In two patients, the distortion correction was potentially clinically significant in that it might have affected the localization or interpretation of activation and could thereby have influenced the treatment plan. Distortion correction is shown to be effective and clinically relevant in presurgical planning at 7T.

A method for the dynamic correction of B0-related distortions in single-echo EPI at 7T

We propose a method to calculate field maps from the phase of each EPI in an fMRI time series. These field maps can be used to correct the corresponding magnitude images for distortion caused by inhomogeneity in the static magnetic field. In contrast to conventional static distortion correction, in which one ‘snapshot’ field map is applied to all subsequent fMRI time points, our method also captures dynamic changes to B₀ which arise due to motion and respiration. The approach is based on the assumption that the non-B₀-related contribution to the phase measured by each radio-frequency coil, which is dominated by the coil sensitivity, is stable over time and can therefore be removed to yield a field map from EPI.

Our solution addresses imaging with multi-channel coils at ultra-high field (7 T), where phase offsets vary rapidly in space, phase processing is non-trivial and distortions are comparatively large. We propose using dual-echo gradient echo reference scan for the phase offset calculation, which yields estimates with high signal-to-noise ratio. An extrapolation method is proposed which yields reliable estimates for phase offsets even where motion is large and a tailored phase unwrapping procedure for EPI is suggested which gives robust results in regions with disconnected tissue or strong signal decay.

Phase offsets are shown to be stable during long measurements (40 min) and for large head motions. The dynamic distortion correction proposed here is found to work accurately in the presence of large motion (up to 8.1°), whereas a conventional method based on single field map fails to correct or even introduces distortions (up to 11.2 mm). Finally, we show that dynamic unwarping increases the temporal stability of EPI in the presence of motion.

Our approach can be applied to any EPI measurements without the need for sequence modification.

Correcting dynamic distortions in 7T echo planar imaging using a jittered echo time sequence

Purpose

To develop a distortion correction method for echo planar imaging (EPI) that is able to measure dynamic changes in B₀.

Theory and Methods

The approach we propose is based on single‐echo EPI with a jittering of the echo time between two values for alternate time points. Field maps are calculated between phase images from adjacent volumes and are used to remove distortion from corresponding magnitude images. The performance of our approach was optimized using an analytical model and by comparison with field maps from dual‐echo EPI. The method was tested in functional MRI experiments at 7T with motor tasks and compared with the conventional static approach.

Results

Unwarping using our method was accurate even for head rotations up to 8.2°, where the static approach introduced errors up to 8.2 mm. Jittering the echo time between 19 and 25 ms had no measurable effect on blood oxygenation level–dependent (BOLD) sensitivity. Our approach reduced the distortions in activated regions to <1 mm and repositioned active voxels correctly.

Conclusion

This method yields accurate distortion correction in the presence of motion. No reduction in BOLD sensitivity was observed. As such, it is suitable for application in a wide range of functional MRI experiments. Magn Reson Med 76:1388–1399, 2016. © 2015 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.

Mapping brain glucose uptake with chemical exchange-sensitive spin-lock magnetic resonance imaging

Uptake of administered D-glucose (Glc) or 2-deoxy-D-glucose (2DG) has been indirectly mapped through the chemical exchange (CE) between glucose hydroxyl and water protons using CE-dependent saturation transfer (glucoCEST) magnetic resonance imaging (MRI). We propose an alternative technique-on-resonance CE-sensitive spin-lock (CESL) MRI-to enhance responses to glucose changes. Phantom data and simulations suggest higher sensitivity for this 'glucoCESL' technique (versus glucoCEST) in the intermediate CE regime relevant to glucose. Simulations of CESL signals also show insensitivity to B0-fluctuations. Several findings are apparent from in vivo glucoCESL studies of rat brain at 9.4 Tesla with intravenous injections. First, dose-dependent responses are nearly linearly for 0.25-, 0.5-, and 1-g/kg Glc administration (obtained with 12-second temporal resolution), with changes robustly detected for all doses. Second, responses at a matched dose of 1 g/kg are much larger and persist for a longer duration for 2DG versus Glc administration, and are minimal for mannitol as an osmolality control. And third, with similar increases in steady-state blood glucose levels, glucoCESL responses are ∼2.2 times higher for 2DG versus Glc, consistent with their different metabolic properties. Overall, we show that glucoCESL MRI could be a highly sensitive and quantifiable tool for glucose transport and metabolism studies.