Diffusion MRI of the human brain at ultra-high field (UHF): A review

B 1 + inhomogeneity mitigation for diffusion weighted MRI at 7T using TR-FOCI pulses

PURPOSE

The purpose of this study is to improve the image quality of diffusion-weighted images obtained with a single RF transmit channel 7 T MRI setup using time-resampled frequency-offset corrected inversion (TR-FOCI) pulses to refocus the spins in a twice-refocused spin-echo readout scheme.

METHODS

We replaced the conventional Shinnar-Le Roux-pulses in the twice refocused diffusion sequence with TR-FOCI pulses. The slice profiles were evaluated in simulation and experimentally in phantoms. The image quality was evaluated in vivo comparing the Shinnar-Le Roux and TR-FOCI implementation using a b value of 0 and of 1000 s/mm2.

RESULTS

The b0 and diffusion-weighted images acquired using the modified sequence improved the image quality across the whole brain. A region of interest-based analysis showed an SNR increase of 113% and 66% for the nondiffusion-weighted (b0) and the diffusion-weighted (b = 1000 s/mm2) images in the temporal lobes, respectively. Investigation of all slices showed that the adiabatic pulses mitigatedB 1 + $$ {B}_1^{+} $$ inhomogeneity globally using a conventional single-channel transmission setup.

CONCLUSION

The TR-FOCI pulse can be used in a twice-refocused spin-echo diffusion pulse sequence to mitigate the impact ofB 1 + $$ {B}_1^{+} $$ inhomogeneity on the signal intensity across the brain at 7 T. However, further work is needed to address SAR limitations.

FD-Net: An unsupervised deep forward-distortion model for susceptibility artifact correction in EPI

PURPOSE

To introduce an unsupervised deep-learning method for fast and effective correction of susceptibility artifacts in reversed phase-encode (PE) image pairs acquired with echo planar imaging (EPI).

METHODS

Recent learning-based correction approaches in EPI estimate a displacement field, unwarp the reversed-PE image pair with the estimated field, and average the unwarped pair to yield a corrected image. Unsupervised learning in these unwarping-based methods is commonly attained via a similarity constraint between the unwarped images in reversed-PE directions, neglecting consistency to the acquired EPI images. This work introduces a novel unsupervised deep Forward-Distortion Network (FD-Net) that predicts both the susceptibility-induced displacement field and the underlying anatomically correct image. Unlike previous methods, FD-Net enforces the forward-distortions of the correct image in both PE directions to be consistent with the acquired reversed-PE image pair. FD-Net further leverages a multiresolution architecture to maintain high local and global performance.

RESULTS

FD-Net performs competitively with a gold-standard reference method (TOPUP) in image quality, while enabling a leap in computational efficiency. Furthermore, FD-Net outperforms recent unwarping-based methods for unsupervised correction in terms of both image and field quality.

CONCLUSION

The unsupervised FD-Net method introduces a deep forward-distortion approach to enable fast, high-fidelity correction of susceptibility artifacts in EPI by maintaining consistency to measured data. Therefore, it holds great promise for improving the anatomical accuracy of EPI imaging.

High-resolution diffusion-weighted imaging at 7 Tesla: single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy

Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various multi-shot acquisition strategies have been developed to achieve sub-millimeter resolution, but they require long scan times which can be restricting for patient scans. Alternatively, the SNR of single-shot acquisitions can be increased by using a spiral readout trajectory to minimize the sequence echo time. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* of brain tissue and the greater field non-uniformities at UHFs will degrade image quality, causing image blurring, distortions, and signal loss. In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral trajectories, over a range of dMRI resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6-1.8 mm. In-vivo partial brain scans at a nominal resolution of 1.5 mm isotropic were acquired using the three readout trajectories to validate the simulation results. Field probes were used to measure dynamic magnetic fields offline up to the 3^rd order of spherical harmonics. Image reconstruction was performed using static ΔB₀ field maps and the measured trajectories to correct image distortions and artifacts, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps calculated from a multi-shell dataset with b-values of 300, 1000, and 2000 s/mm² in 5, 16, and 48 directions, respectively. In-vivo scans at nominal resolutions of 1, 1.2, and 1.5 mm were acquired and the SNR of the different trajectories calculated using the multiple replica method to investigate the SNR. Finally, in-vivo whole brain scans with an effective resolution of 1.5 mm isotropic were acquired to explore the SNR and efficiency of different trajectories at a matching effective resolution. FA and intra-cellular volume fraction (ICVF) maps calculated using neurite orientation dispersion and density imaging (NODDI) were used for the comparison. The simulations and in vivo imaging results showed that for matching nominal resolutions, EPI trajectories had the highest specificity and effective resolution with maximum image sharpening effect. However, spirals have a significantly higher SNR, in particular at higher resolutions and even when the effective image resolutions are matched. Overall, this work shows that the higher SNR of single-shot spiral trajectories at 7T allows us to achieve higher effective resolutions compared to EPI and PF-EPI to map the microstructure and connectivity of small brain structures.

Rapid Geometry-Corrected Echo-Planar Diffusion Imaging at Ultrahigh Field: Fusing View Angle Tilting and Point-Spread Function Mapping

PURPOSE

Severe geometric distortions induced by tissue susceptibility, water-fat chemical shift, and eddy currents pose a substantial obstacle in single-shot EPI, especially for high-resolution imaging at ultrahigh field. View angle tilting (VAT)-EPI can mitigate in-plane distortion. However, the accompanied strong image blurring prevented its widespread applications. On the other hand, point-spread function mapping (PSF)-EPI can correct distortion and blurring accurately but requires prolonged scan time. We present fused VAT-PSF-EPI and possibilities for acceleration.

METHODS

MR signal equations were explicitly derived to quantify image blurring in VAT-EPI and the maximum acceleration capacity in VAT-PSF-EPI. To validate the theoretical prediction, phantom measurements with varying in-plane parallel imaging factors, slice thicknesses, and RF pulses were conducted at 7 Tesla. In addition, in vivo human brain scans were acquired with T₂ and diffusion weighting to assess distortion and blurring correction.

RESULTS

VAT can effectively suppress distortion, and the introduced image blurring is corrected through PSF encoding. Up to fourfold acceleration (only 5 shots) in VAT-PSF-EPI was achieved compared with standard PSF-EPI without VAT. VAT-induced signal loss was mitigated by adjusting the sequence parameters and EPI resolution. In vivo T₂ -weighted EPI data with 1.4 mm³ resolution demonstrate immunity to water-fat chemical shift-induced distortion. Very high-spatial resolution diffusion-weighted EPI (0.7 × 0.7 × 2.8 mm³ and 1.2 mm³ ) demonstrates the immunity to eddy current-induced distortion.

CONCLUSION

VAT-PSF-EPI is a novel spin-echo EPI-based sequence for fast high-resolution diffusion imaging at ultrahigh field.

Transient global amnesia: 7 Tesla MRI reveals more hippocampal lesions with diffusion restriction compared to 1.5 and 3 Tesla MRI

PURPOSE

To assess the ability of 7 T MRI to detect hippocampal DWI lesions in the acute phase of TGA compared to 1.5 T/3 T MRI.

METHODS

Patients with a clinical diagnosis consistent with TGA and a 1.5/3 T MRI underwent an additional 7 T MRI when the 7 T system was available for clinical use, thus serving as their own controls.

RESULTS

Thirteen TGA patients with a median age of 68.5 years (range 46-77 years) were included and imaged at 1.5/3 T (median 17 h after onset of symptoms, range 3-23 h) and 7 T (median 23 h after onset, range 15-46 h). The 7 T MRIs were performed a median of 15 h after the 1.5/3 T MRIs (range 1-28 h). At 1.5/3 T, six patients (46%) were found to have at least one hippocampal DWI-lesions supporting the TGA diagnosis, which increased to 11 patients (85%) when examined at 7 T (p = 0.03). At 1.5/3 T, nine hippocampal DWI lesions were detected, which increased to 19 at 7 T, giving an increased detection rate of 111% (p = 0.002). Both neuroradiologists found the hippocampal DWI lesions at 7 T to have higher conspicuity and be easier to categorize as true findings compared to 1.5/3 T.

CONCLUSION

Seven-Tesla MRI showed both a statistically significant increase in the total number of detected hippocampal DWI lesions and the proportion of patients with at least one hippocampal DWI lesion supporting the TGA diagnosis compared to 1.5/3 T. Clinical use of 7 T will increase the number of patients having their TGA diagnosis supported by MRI, which can be especially useful in patients with negative 1.5/3 T MRI and low clinical certainty.

EPI phase error correction with deep learning (PEC-DL) at 7 T

PURPOSE

The phase mismatch between odd and even echoes in EPI causes Nyquist ghost artifacts. Existing ghost correction methods often suffer from severe residual artifacts and are ineffective with k-space undersampling data. This study proposed a deep learning-based method (PEC-DL) to correct phase errors for DWI at 7 Tesla.

METHODS

The acquired k-space data were divided into 2 independent undersampled datasets according to their readout polarities. Then the proposed PEC-DL network reconstructed 2 ghost-free images using the undersampled data without calibration and navigator data. The network was trained with fully sampled images and applied to two- and fourfold accelerated data. Healthy volunteers and patients with Moyamoya disease were recruited to validate the efficacy of the PEC-DL method.

RESULTS

The PEC-DL method was capable to mitigate the ghost artifacts in DWI in healthy volunteers as well as patients with Moyamoya disease. The fourfold accelerated results showed much less distortion in the lesions of the Moyamoya patient using high b-value DWI and the corresponding ADC maps. The ghost-to-signal ratios were significantly lower in PEC-DL images compared to conventional linear phase corrections, mini-entropy, and PEC-GRAPPA algorithms.

CONCLUSION

The proposed method can effectively eliminate ghost artifacts for full sampled and up to fourfold accelerated EPI data without calibration and navigator data.

Sensitivity of Diffusion MRI to White Matter Pathology: Influence of Diffusion Protocol, Magnetic Field Strength, and Processing Pipeline in Systemic Lupus Erythematosus

There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.

Post-Concussive Vestibular Dysfunction Is Related to Injury to the Inferior Vestibular Nerve

Symptoms of vestibular dysfunction such as dizziness and vertigo are common after sports-related concussions (SRC) and associated with a worse outcome and a prolonged recovery. Vestibular dysfunction after SRC can be because of an impairment of the peripheral or central neural parts of the vestibular system. The aim of the present study was to establish the cause of vestibular impairment in athletes with SRC who have persisting post-concussive symptoms (PPCS). We recruited 42 participants-21 athletes with previous SRCs and PPCS ≥6 months and 21 healthy athletic age- and sex-matched controls-who underwent symptom rating, a detailed test battery of vestibular function and 7T magnetic resonance imaging with diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) of cerebellar white matter tracts, and T1-weighted imaging for cerebellar volumetrics. Vestibular dysfunction was observed in 13 SRC athletes and three controls (p = 0.001). Athletes with vestibular dysfunction reported more pronounced symptoms on the Dizziness Handicap Inventory (DHI; p < 0.001) and the Hospital Anxiety and Depression Scale (HADS; p < 0.001). No significant differences in DTI metrics were found, while in DKI two metrics were observed in the superior and/or inferior cerebellar tracts. Cerebellar gray and white matter volumes were similar in athletes with SRC and controls. Compared with controls, pathological video head impulse test results (vHIT; p < 0.001) and cervical vestibular evoked myogenic potentials (cVEMP; p = 0.002) were observed in athletes with SRC, indicating peripheral vestibular dysfunction and specifically suggesting injury to the inferior vestibular nerve. In athletes with persisting symptoms after SRC, vestibular dysfunction is associated with injury to the inferior vestibular nerve.

Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies

Diffusion magnetic resonance imaging (dMRI) provides indirect measures of white matter microstructure that can be used to make inferences about structural connectivity within the brain. Over the last decade, a growing literature of cross-sectional and longitudinal studies have documented relationships between dMRI indices and cognitive development. In this review, we provide a brief overview of dMRI methods and how they can be used to study white matter and connectivity and review the extant literature examining the links between dMRI indices and executive functions during development. We explore the links between white matter microstructure and specific executive functions: inhibition, working memory and cognitive shifting, as well as performance on complex executive function tasks. Concordance in findings across studies are highlighted, and potential explanations for discrepancies between results, together with challenges with using dMRI in child and adolescent populations, are discussed. Finally, we explore future directions that are necessary to better understand the links between child and adolescent development of structural connectivity of the brain and executive functions.

A simulation study investigating potential diffusion-based MRI signatures of microstrokes

Recent studies suggested that cerebrovascular micro-occlusions, i.e. microstokes, could lead to ischemic tissue infarctions and cognitive deficits. Due to their small size, identifying measurable biomarkers of these microvascular lesions remains a major challenge. This work aims to simulate potential MRI signatures combining arterial spin labeling (ASL) and multi-directional diffusion-weighted imaging (DWI). Driving our hypothesis are recent observations demonstrating a radial reorientation of microvasculature around the micro-infarction locus during recovery in mice. Synthetic capillary beds, randomly- and radially-oriented, and optical coherence tomography (OCT) angiograms, acquired in the barrel cortex of mice (n = 5) before and after inducing targeted photothrombosis, were analyzed. Computational vascular graphs combined with a 3D Monte-Carlo simulator were used to characterize the magnetic resonance (MR) response, encompassing the effects of magnetic field perturbations caused by deoxyhemoglobin, and the advection and diffusion of the nuclear spins. We quantified the minimal intravoxel signal loss ratio when applying multiple gradient directions, at varying sequence parameters with and without ASL. With ASL, our results demonstrate a significant difference (p < 0.05) between the signal-ratios computed at baseline and 3 weeks after photothrombosis. The statistical power further increased (p < 0.005) using angiograms measured at week 4. Without ASL, no reliable signal change was found. We found that higher ratios, and accordingly improved significance, were achieved at lower magnetic field strengths (e.g., B0 = 3T) and shorter echo time TE (< 16 ms). Our simulations suggest that microstrokes might be characterized through ASL-DWI sequence, providing necessary insights for posterior experimental validations, and ultimately, future translational trials.

SNR-enhanced diffusion MRI with structure-preserving low-rank denoising in reproducing kernel Hilbert spaces

PURPOSE

To introduce, develop, and evaluate a novel denoising technique for diffusion MRI that leverages nonlinear redundancy in the data to boost the SNR while preserving signal information.

METHODS

We exploit nonlinear redundancy of the dMRI data by means of kernel principal component analysis (KPCA), a nonlinear generalization of PCA to reproducing kernel Hilbert spaces. By mapping the signal to a high-dimensional space, a higher level of redundant information is exploited, thereby enabling better denoising than linear PCA. We implement KPCA with a Gaussian kernel, with parameters automatically selected from knowledge of the noise statistics, and validate it on realistic Monte Carlo simulations as well as with in vivo human brain submillimeter and low-resolution dMRI data. We also demonstrate KPCA denoising on multi-coil dMRI data.

RESULTS

SNR improvements up to 2.7 × were obtained in real in vivo datasets denoised with KPCA, in comparison to SNR gains of up to 1.8 × using a linear PCA denoising technique called Marchenko-Pastur PCA (MPPCA). Compared to gold-standard dataset references created from averaged data, we showed that lower normalized root mean squared error was achieved with KPCA compared to MPPCA. Statistical analysis of residuals shows that anatomical information is preserved and only noise is removed. Improvements in the estimation of diffusion model parameters such as fractional anisotropy, mean diffusivity, and fiber orientation distribution functions were also demonstrated.

CONCLUSION

Nonlinear redundancy of the dMRI signal can be exploited with KPCA, which allows superior noise reduction/SNR improvements than the MPPCA method, without loss of signal information.

A self-decoupled 32-channel receive array for human-brain MRI at 10.5 T

PURPOSE

Receive array layout, noise mitigation, and B₀ field strength are crucial contributors to SNR and parallel-imaging performance. Here, we investigate SNR and parallel-imaging gains at 10.5 T compared with 7 T using 32-channel receive arrays at both fields.

METHODS

A self-decoupled 32-channel receive array for human brain imaging at 10.5 T (10.5T-32Rx), consisting of 31 loops and one cloverleaf element, was co-designed and built in tandem with a 16-channel dual-row loop transmitter. Novel receive array design and self-decoupling techniques were implemented. Parallel imaging performance, in terms of SNR and noise amplification (g-factor), of the 10.5T-32Rx was compared with the performance of an industry-standard 32-channel receiver at 7 T (7T-32Rx) through experimental phantom measurements.

RESULTS

Compared with the 7T-32Rx, the 10.5T-32Rx provided 1.46 times the central SNR and 2.08 times the peripheral SNR. Minimum inverse g-factor value of the 10.5T-32Rx (min[1/g] = 0.56) was 51% higher than that of the 7T-32Rx (min[1/g] = 0.37) with R = 4 × 4 2D acceleration, resulting in significantly enhanced parallel-imaging performance at 10.5 T compared with 7 T. The g-factor values of 10.5 T-32 Rx were on par with those of a 64-channel receiver at 7 T (eg, 1.8 vs 1.9, respectively, with R = 4 × 4 axial acceleration).

CONCLUSION

Experimental measurements demonstrated effective self-decoupling of the receive array as well as substantial gains in SNR and parallel-imaging performance at 10.5 T compared with 7 T.

Simultaneous multi-banding and multi-echo phase encoding for the accelerated acquisition of high-resolution volumetric diffusivity maps by spatiotemporally encoded MRI

PURPOSE

Spatiotemporal Encoding (SPEN) is an ultrafast imaging technique where the low-bandwidth axis is rasterized in a joint spatial/k-domain. SPEN benefits from increased robustness to field inhomogeneities, folding-free reconstruction of subsampled data, and an ability to combine multiple interleaved or signal averaged scans -yet its relatively high SAR complicates volumetric uses. Here we show how this can be alleviated by merging simultaneous multi-band excitation, with intra-slab multi-echo (ME) phase encoding, for the acquisition of high definition volumetric DWI/DTI data.

METHODS

A protocol involving phase-cycling of simultaneous multi-banded z-slab excitations in independently k_y-interleaved scans, together with ME trains that k_z-encoded positions within these slabs, was implemented. A reconstruction incorporating a CAIPIRINHA-like encoding of the multiple bands and exploiting SPEN's ability to deliver self-referenced, per-shot phase maps, then led to high-definition diffusivity acquisitions, with reduced SAR and acquisition times vis-à-vis non-optimized 3D counterparts.

RESULTS

The new protocol was used to collect full brain 3 T DTI experiments at a variety of nominal voxel sizes, ranging from 1.95 to 2.54 mm³. In general, the new protocol yielded superior sensitivity and fewer distortions than what could be observed in comparably timed phase-encoded 3D SPEN, multi-slice 2D SPEN, or optimized EPI counterparts.

CONCLUSIONS

A robust procedure for acquiring volumetric DWI/DTI data was developed and demonstrated.

Probing in vivo cortical myeloarchitecture in humans via line-scan diffusion acquisitions at 7 T with 250-500 micron radial resolution

PURPOSE

The goal of this study was to measure diffusion signals within the cerebral cortex using the line-scan technique to achieve extremely high resolution in the radial direction (ie, perpendicular to the cortical surface) and to demonstrate the utility of these measurements for investigating laminar architecture in the living human brain.

METHODS

Line-scan diffusion data with 250-500 micron radial resolution were acquired at 7 T on 8 healthy volunteers, with each line prescribed perpendicularly to primary somatosensory cortex (S1) and primary motor cortex (M1). Apparent diffusion coefficients, fractional anisotropy values, and radiality indices were measured as a function of cortical depth.

RESULTS

In the deep layers of S1, we found evidence for high anisotropy and predominantly tangential diffusion, with low anisotropy observed in superficial S1. In M1, moderate anisotropy and predominantly radial diffusion was seen at almost all cortical depths. These patterns were consistent across subjects and were conspicuous without averaging data across different locations on the cortical sheet.

CONCLUSION

Our results are in accord with the myeloarchitecture of S1 and M1, known from prior histology studies: in S1, dense bands of tangential myelinated fibers run through the deep layers but not the superficial ones, and in M1, radial myelinated fibers are prominent at most cortical depths. This work therefore provides support for the idea that high-resolution diffusion signals, measured with the line-scan technique and receiving a boost in SNR at 7 T, may serve as a sensitive probe of in vivo laminar architecture.

Spatial versus angular resolution for tractography-assisted planning of deep brain stimulation

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Deep brain stimulation (DBS) benefits from precise targeting of white matter tracts.

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Better to increase spatial vs. angular resolution for separating parallel tracts.

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Scanning time trade-off between angular & spatial resolution depends on local anatomy.

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We recommend increased spatial resolution dMRI for tract-guided internal capsule DBS.

Given the restricted total scanning time for clinical neuroimaging, it is unclear whether clinical diffusion MRI protocols would benefit more from higher spatial resolution or higher angular resolution. In this work, we investigated the relative benefit of improving spatial or angular resolution in diffusion MRI to separate two parallel running white matter tracts that are targets for deep brain stimulation: the anterior thalamic radiation and the supero-lateral branch of the medial forebrain bundle. Both these tracts are situated in the ventral anterior limb of the internal capsule, and recent studies suggest that targeting a specific tract could improve treatment efficacy. Therefore, we scanned 19 healthy volunteers at 3T and 7T according to three diffusion MRI protocols with respectively standard clinical settings, increased spatial resolution of 1.4 mm, and increased angular resolution (64 additional gradient directions at b = 2200s/mm²). We performed probabilistic tractography for all protocols and quantified the separability of both tracts. The higher spatial resolution protocol improved separability by 41% with respect to the clinical standard, presumably due to decreased partial voluming. The higher angular resolution protocol resulted in increased apparent tract volumes and overlap, which is disadvantageous for application in precise treatment planning. We thus recommend to increase the spatial resolution for deep brain stimulation planning to 1.4 mm while maintaining angular resolution. This recommendation complements the general advice to aim for high angular resolution to resolve crossing fibers, confirming that the specific application and anatomical considerations are leading in clinical diffusion MRI protocol optimization.

Structure tensor informed fibre tractography at 3T

Structure tensor informed fibre tractography (STIFT) based on informing tractography for diffusion-weighted images at 3T and by utilising the structure tensor obtained from gradient-recalled echo (GRE) images at 7T is able to delineate fibres when seed voxels are placed close to the fibre boundaries. However, incorporating data from two different field strengths limits the applicability of STIFT. In this study, STIFT was implemented with both diffusion-weighted images and GRE images acquired at 3T. Instead of using the magnitude GRE data directly for STIFT as in the previous work, the utility of T₂ * maps and quantitative susceptibility maps derived from complex-valued GRE data to improve fibre delineation was explored. Single-seed tractography was performed and the results show that the optic radiation reconstructed with STIFT is more distinguishable from the inferior longitudinal fasciculus/inferior fronto-occipital fasciculus complex when compared to standard diffusion-weighted imaging tractography. We further investigated the quantitative effects of STIFT in a group of five healthy volunteers and evaluated its impact on measures of structural connectivity. The framework was extended to evaluate implementations of STIFT based on T₂ *-weighted and quantitative susceptibility-weighted images in a whole-brain connectivity study. In terms of connectivity, no systematic differences were found between STIFT and diffusion-weighted imaging tractography, suggesting that local improvements in tractography are not translated to the atlas-based structural connectivity analysis. Nevertheless, the reduction in the number of statistically significant connections in the STIFT connectivity matrix suggests that STIFT can potentially reduce the false-positive connections in fibre tractography.

Visualizing the Human Subcortex Using Ultra-high Field Magnetic Resonance Imaging

With the recent increased availability of ultra-high field (UHF) magnetic resonance imaging (MRI), substantial progress has been made in visualizing the human brain, which can now be done in extraordinary detail. This review provides an extensive overview of the use of UHF MRI in visualizing the human subcortex for both healthy and patient populations. The high inter-subject variability in size and location of subcortical structures limits the usability of atlases in the midbrain. Fortunately, the combined results of this review indicate that a large number of subcortical areas can be visualized in individual space using UHF MRI. Current limitations and potential solutions of UHF MRI for visualizing the subcortex are also discussed.