Improving diffusion MRI using simultaneous multi-slice echo planar imaging

Direct and Indirect Associations of Widespread Individual Differences in Brain White Matter Microstructure With Executive Functioning and General and Specific Dimensions of Psychopathology in Children

BACKGROUND

Executive functions (EFs) are important partly because they are associated with risk for psychopathology and substance use problems. Because EFs have been linked to white matter microstructure, we tested the prediction that fractional anisotropy (FA) and mean diffusivity (MD) in white matter tracts are associated with EFs and dimensions of psychopathology in children younger than the age of widespread psychoactive substance use.

METHODS

Parent symptom ratings, EF test scores, and diffusion tensor parameters from 8588 9- to 10-year-olds in the ABCD Study (Adolescent Brain Cognitive Development Study) were used.

RESULTS

A latent factor derived from EF test scores was significantly associated with specific conduct problems and attention-deficit/hyperactivity disorder problems, with dimensions defined in a bifactor model. Furthermore, EFs were associated with FA and MD in 16 of 17 bilateral white matter tracts (range: β = .05; SE = .17; through β = -.31; SE = .06). Neither FA nor MD was directly associated with psychopathology, but there were significant indirect associations via EFs of both FA (range: β = .01; SE = .01; through β = -.09; SE = .02) and MD (range: β = .01; SE = .01; through β = .09; SE = .02) with both specific conduct problems and attention-deficit/hyperactivity disorder in all tracts except the forceps minor.

CONCLUSIONS

EFs in children are inversely associated with diffusion tensor imaging measures in nearly all tracts throughout the brain. Furthermore, variance in diffusion tensor measures that is shared with EFs is indirectly shared with attention-deficit/hyperactivity disorder and conduct problems.

Multi-shell Diffusion MRI Models for White Matter Characterization in Cerebral Small Vessel Disease

OBJECTIVE

To test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change, and reproducibility of diffusion metrics.

METHODS

We included 50 patients with sporadic and 59 patients with genetically defined SVD (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 patients with sporadic SVD with longitudinal high-frequency imaging (in total 459 MRIs). Intersite reproducibility was determined in 10 patients with CADASIL scanned back-to-back on 2 different 3T MRI scanners.

RESULTS

Metrics from DKI showed the strongest associations with processing speed performance (R ² up to 21%) and the largest added benefit on top of conventional SVD imaging markers in patients with sporadic SVD and patients with CADASIL with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient >0.93) for DTI and DKI metrics. NODDI metrics were less reproducible.

CONCLUSION

Multi-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available intersite dataset facilitates future studies.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.

Customizing TMS Applications in Traumatic Brain Injury Using Neuroimaging

Optimizing transcranial magnetic stimulation (TMS) treatments in traumatic brain injury (TBI) and co-occurring conditions may benefit from neuroimaging-based customization.

PARTICIPANTS

Our total sample (N = 97) included 58 individuals with TBI (49 mild, 8 moderate, and 1 severe in a state of disordered consciousness), of which 24 had co-occurring conditions (depression in 14 and alcohol use disorder in 10). Of those without TBI, 6 individuals had alcohol use disorder and 33 were healthy controls. Of our total sample, 54 were veterans and 43 were civilians.

DESIGN

Proof-of-concept study incorporating data from 5 analyses/studies that used multimodal approaches to integrate neuroimaging with TMS.

MAIN MEASURES

Multimodal neuroimaging methods including structural magnetic resonance imaging (MRI), MRI-guided TMS navigation, functional MRI, diffusion MRI, and TMS-induced electric fields. Outcomes included symptom scales, neuropsychological tests, and physiological measures.

RESULTS

It is feasible to use multimodal neuroimaging data to customize TMS targets and understand brain-based changes in targeted networks among people with TBI.

CONCLUSIONS

TBI is an anatomically heterogeneous disorder. Preliminary evidence from the 5 studies suggests that using multimodal neuroimaging approaches to customize TMS treatment is feasible. To test whether this will lead to increased clinical efficacy, studies that integrate neuroimaging and TMS targeting data with outcomes are needed.

Comparison of 2D simultaneous multi-slice and 3D GRASE readout schemes for pseudo-continuous arterial spin labeling of cerebral perfusion at 3 T

OBJECTIVE

In this perfusion magnetic resonance imaging study, the performances of different pseudo-continuous arterial spin labeling (PCASL) sequences were compared: two-dimensional (2D) single-shot readout with simultaneous multislice (SMS), 2D single-shot echo-planar imaging (EPI) and multishot three-dimensional (3D) gradient and spin echo (GRASE) sequences combined with a background-suppression (BS) module.

MATERIALS AND METHODS

Whole-brain PCASL images were acquired from seven healthy volunteers. The performance of each protocol was evaluated by extracting regional cerebral blood flow (rCBF) measures using an inline morphometric segmentation prototype. Image data postprocessing and subsequent statistical analyses enabled comparisons at the regional and sub-regional levels.

RESULTS

The main findings were as follows: (i) Mean global CBF obtained across methods was were highly correlated, and these correlations were significantly higher among the same readout sequences. (ii) Temporal signal-to-noise ratio and gray-matter-to-white-matter CBF ratio were found to be equivalent for all 2D variants but lower than those of 3D-GRASE.

DISCUSSION

Our study demonstrates that the accelerated SMS readout can provide increased acquisition efficiency and/or a higher temporal resolution than conventional 2D and 3D readout sequences. Among all of the methods, 3D-GRASE showed the lowest variability in CBF measurements and thus highest robustness against noise.

Challenges for biophysical modeling of microstructure

The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of bringing a biophysical model from initial design to clinical implementation, identifying both hurdles that have been already overcome and outstanding issues. First, we describe the critical initial task of selecting which features of tissue microstructure can be estimated using a model and which acquisition protocol needs to be implemented to make the estimation possible. The model performance should necessarily be tested in realistic numerical simulations and in experimental data - adapting the fitting strategy accordingly, and parameter estimates should be validated against complementary techniques, when/if available. Secondly, the model performance and validity should be explored in pathological conditions, and, if appropriate, dedicated models for pathology should be developed. We build on examples from tumors, ischemia and demyelinating diseases. We then discuss the challenges associated with clinical translation and added value. Finally, we single out four major unresolved challenges that are related to: the availability of a microstructural ground truth, the validation of model parameters which cannot be accessed with complementary techniques, the development of a generalized standard model for any brain region and pathology, and the seamless communication between different parties involved in the development and application of biophysical models of diffusion.

Evaluation of trigeminal nerve tractography using two-fold-accelerated simultaneous multi-slice readout-segmented echo planar diffusion tensor imaging

OBJECTIVES

Simultaneous multi-slice (SMS) imaging with short repetition time (TR) accelerates diffusion tensor imaging (DTI) acquisitions. However, its impact when combined with readout-segmented echo planar imaging (RESOLVE) on the cranial nerves given the challenging skull base/posterior fossa terrain is unexplored. We evaluated the reliability of trigeminal nerve DTI metrics using SMS with RESOLVE-DTI.

METHODS

Eight healthy controls and six patients with unilateral trigeminal neuralgia (TN) underwent brain MRI scan. Three different RESOLVE-DTI protocols were performed on a 3-T MRI system: non-SMS (TR = 4330 ms), SMS with identical TR (4330 ms), and SMS with short TR (2400 ms). Pontine signal-to-noise ratio (SNR) and DTI metrics of the trigeminal nerve streamlines tracked by two independent raters using deterministic tractography and standardized tracking protocol were obtained. These were statistically analyzed and compared across the three protocols using intra-rater and inter-rater intraclass correlation coefficients (ICCs), one-way analysis of variance (ANOVA), post hoc analysis, and linear regression.

RESULTS

On visual screening, there were no artifacts across the trigeminal nerves. All data also cleared objective image quality assurance analysis. Pontine SNR was similar for the two SMS protocols and higher for the non-SMS RESOLVE-DTI (F_(2,36) = 4.40, p = 0.02). Intra-rater and inter-rater ICCs were very good (> 0.85). Trigeminal nerve DTI metrics were consistently measured by the three protocols, revealing significant linear relationships between non-SMS- and SMS-derived DTI metrics.

CONCLUSION

SMS RESOLVE-DTI enables fast and reliable evaluation of microstructural integrity of the trigeminal nerve, with potential application in the clinical management of TN.

KEY POINTS

• Readout-segmented diffusion-weighted echo planar imaging (RESOLVE-DTI) reduces image distortion artifacts in the posterior fossa but its long acquisition time limits clinical utility. • Simultaneous multi-slice (SMS) imaging combined with RESOLVE-DTI provides reliable trigeminal nerve tractography with potential applications in trigeminal neuralgia. • Two-fold-accelerated RESOLVE-DTI yields comparable trigeminal nerve streamlines and DTI metrics while near-halving acquisition time.

Multishell Diffusion MRI-Based Tractography of the Facial Nerve in Vestibular Schwannoma

BACKGROUND AND PURPOSE

Tractography of the facial nerve based on single-shell diffusion MR imaging is thought to be helpful before surgery for resection of vestibular schwannoma. However, this paradigm can be vitiated by the isotropic diffusion of the CSF, the convoluted path of the facial nerve, and its crossing with other bundles. Here we propose a multishell diffusion MR imaging acquisition scheme combined with probabilistic tractography that has the potential to provide a presurgical facial nerve reconstruction uncontaminated by such effects.

MATERIALS AND METHODS

Five patients scheduled for vestibular schwannoma resection underwent multishell diffusion MR imaging (b-values = 0, 300, 1000, 2000 s/mm²). Facial nerve tractography was performed with a probabilistic algorithm and anatomic seeds located in the brain stem, cerebellopontine cistern, and internal auditory canal. A single-shell diffusion MR imaging (b-value = 0, 1000 s/mm²) subset was extrapolated from the multishell diffusion MR imaging data. The quality of the facial nerve reconstruction based on both multishell diffusion MR imaging and single-shell diffusion MR imaging sequences was assessed against intraoperative videos recorded during the operation.

RESULTS

Single-shell diffusion MR imaging-based tractography was characterized by failures in facial nerve tracking (2/5 cases) and inaccurate facial nerve reconstructions displaying false-positives and partial volume effects. In contrast, multishell diffusion MR imaging-based tractography provided accurate facial nerve reconstructions (4/5 cases), even in the presence of ostensibly complex patterns.

CONCLUSIONS

In comparison with single-shell diffusion MR imaging, the combination of multishell diffusion MR imaging-based tractography and probabilistic algorithms is a more valuable aid for surgeons before vestibular schwannoma resection, providing more accurate facial nerve reconstructions, which may ultimately improve the postsurgical patient's outcome.

Data-Driven Identification of the Regions of Interest for Fiber Tracking in Patients with Brain Tumors

BACKGROUND

We investigated the added value of combining information from direction-encoded color (DEC) maps with high-resolution structural magnetic resonance imaging scans (T1-weighted images [T1WIs]) to improve the identification of regions of interest (ROIs) for fiber tracking during preoperative planning for patients with brain tumors.

METHODS

The dataset included 42 patients with gliomas and 10 healthy subjects from the Human Connectome Project. For identification of the ROIs, we combined the structural information from high-resolution T1WIs and the directional information from DEC maps. To test our hypothesis, we examined the interrater and intrarater agreement.

RESULTS

We identified specific ROIs to extract the main white matter bundles. The directional information from the DEC maps combined with the T1WIs (T1WI-DEC maps) had significantly facilitated ROI identification in patients with brain tumors, especially patients in whom the tracts had been displaced by the mass effect of the tumor. Fiber tracking using the combined T1WI-DEC maps showed significantly greater inter- and intrarater agreement compared with using either T1WI or DEC maps alone.

CONCLUSION

Combining the information from diffusion-derived color-encoded maps with high-resolution anatomical details from structural imaging (T1WI-DEC map), especially in patients with brain tumors, could be useful for accurate identification of the ROIs.

Ultra-high spatial resolution BOLD fMRI in humans using combined segmented-accelerated VFA-FLEET with a recursive RF pulse design

PURPOSE

To alleviate the spatial encoding limitations of single-shot echo-planar imaging (EPI) by developing multi-shot segmented EPI for ultra-high-resolution functional MRI (fMRI) with reduced ghosting artifacts from subject motion and respiration.

THEORY AND METHODS

Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering, where segments are looped over before slices, was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) radiofrequency (RF) pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals.

RESULTS

The temporal stability of VFA-FLEET-SLR was compared against conventional-segmented EPI and VFA-FLEET-Sinc at 3T and 7T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7T, without zoomed imaging or partial Fourier, demonstrating reliable detection of blood oxygenation level-dependent (BOLD) responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing.

CONCLUSIONS

VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "full-brain" field of view.

Rapid Imaging: Recent Advances in Abdominal MRI for Reducing Acquisition Time and Its Clinical Applications

Magnetic resonance imaging (MRI) plays an important role in abdominal imaging. The high contrast resolution offered by MRI provides better lesion detection and its capacity to provide multiparametric images facilitates lesion characterization more effectively than computed tomography. However, the relatively long acquisition time of MRI often detrimentally affects the image quality and limits its accessibility. Recent developments have addressed these drawbacks. Specifically, multiphasic acquisition of contrast-enhanced MRI, free-breathing dynamic MRI using compressed sensing technique, simultaneous multi-slice acquisition for diffusion-weighted imaging, and breath-hold three-dimensional magnetic resonance cholangiopancreatography are recent notable advances in this field. This review explores the aforementioned state-of-the-art techniques by focusing on their clinical applications and potential benefits, as well as their likely future direction.

Diffusion-prepared 3D gradient spin-echo sequence for improved oscillating gradient diffusion MRI

PURPOSE

Oscillating gradient (OG) enables the access of short diffusion times for time-dependent diffusion MRI (dMRI); however, it poses several technical challenges for clinical use. This study proposes a 3D oscillating gradient-prepared gradient spin-echo (OGprep-GRASE) sequence to improve SNR and shorten acquisition time for OG dMRI on clinical scanners.

METHODS

The 3D OGprep-GRASE sequence consisted of global saturation, diffusion encoding, fat saturation, and GRASE readout modules. Multiplexed sensitivity-encoding reconstruction was used to correct the phase errors between multiple shots. We compared the scan time and SNR of the proposed sequence and the conventional 2D-EPI sequence for OG dMRI at 30-90-mm slice coverage. We also examined the time-dependent diffusivity changes with OG dMRI acquired at frequencies of 50 Hz and 25 Hz and pulsed-gradient dMRI at diffusion times of 30 ms and 60 ms.

RESULTS

The OGprep-GRASE sequence reduced the scan time by a factor of 1.38, and increased the SNR by 1.74-2.27 times compared with 2D EPI for relatively thick slice coverage (60-90 mm). The SNR gain led to improved diffusion-tensor reconstruction in the multishot protocols. Image distortion in 2D-EPI images was also reduced in GRASE images. Diffusivity measurements from the pulsed-gradient dMRI and OG dMRI showed clear diffusion-time dependency in the white matter and gray matter of the human brain, using both the GRASE and EPI sequences.

CONCLUSION

The 3D OGprep-GRASE sequence improved scan time and SNR and reduced image distortion compared with the 2D multislice acquisition for OG dMRI on a 3T clinical system, which may facilitate the clinical translation of time-dependent dMRI.

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

Although the non-invasive measurement of visually evoked responses has been extensively studied, the structural basis of variabilities in latency in healthy humans is not well understood. We investigated how tissue properties of optic radiation could predict interindividual variability in the latency of the initial visually evoked component (C1), which may originate from the primary visual cortex (V1). We collected C1 peak latency data using magnetoencephalography (MEG) and checkerboard stimuli, and multiple structural magnetic resonance imaging (MRI) data from 20 healthy subjects. While we varied the contrast and position of the stimuli, the C1 measurement was most reliable when high-contrast stimuli were presented to the lower visual field (LVF). We then attempted to predict interindividual variability in C1 peak latency in this stimulus condition with a multiple regression model using MRI parameters along the optic radiation. We found that this model could predict >20% of variance in C1 latency, when the data were averaged across the hemispheres. The model using the corticospinal tract did not predict variability in C1 latency, suggesting that there is no evidence for generalization to a non-visual tract. In conclusion, our results suggest that the variability in neural latencies in the early visual cortex in healthy subjects can be partly explained by tissue properties along the optic radiation. We discuss the challenges of predicting neural latency using current structural neuroimaging methods and other factors that may explain interindividual variance in neural latency.

Simultaneous multislice diffusion-weighted imaging with short tau inversion recovery fat suppression in bone-metastasizing breast cancer

PURPOSE

To compare image quality and ADC values of simultaneous multislice diffusion-weighted imaging (mb-DWI) with that of conventional DWI (c-DWI) using short tau inversion recovery fat saturation (STIR) in women with bone-metastasizing breast cancer.

METHOD

c-DWI and mb-DWI were acquired at 1.5 T in 23 breast cancer patients from skull base to mid thighs. mb-DWI was compared to c-DWI in terms of subjective image quality, artefacts and bone metastasis lesion conspicuity assessed on a 5-point Likert scale. ADC values of different organs as well as bone metastasis ADC values were compared between c-DWI and mb-DWI.

RESULTS

mb-DWI reduced scan time by 48 % compared with c-DWI (1 min 58 s vs. 3 min 45 s per station). mb-DWI provided similar subjective image quality (3.8 vs. 3.7, p = 0.70), number of artefacts (50 vs. 56), severity of these (4.6 vs. 4.7, p = 0.11), and lesion conspicuity (4.2 vs. 4.4, p = 0.31) compared to c-DWI. mb-DWI showed lower mean ADC values in liver (0.5 × 10^-3 mm²/s vs. 0.7 × 10^-3 mm²/s, p = 0.002) and erector spine muscle (1.3 × 10^-3 mm²/s vs. 1.5 × 10^-3 mm²/s, p < 0.001). Bone metastasis ADC values from mb-DWI were 6.4 % lower than c-DWI (95 % confidence interval: 5.4%-7.4%, p < 0.001).

CONCLUSIONS

mb-DWI provides similar subjective image quality to c-DWI with the same level of artefacts. Although bone metastasis ADC values were lower, mb-DWI can substantially reduce scan times of whole-body DWI in women with bone-metastasizing breast cancer.

Mapping brain-behavior networks using functional and structural connectome fingerprinting in the HCP dataset

INTRODUCTION

Connectome analysis of the human brain's structural and functional architecture provides a unique opportunity to understand the organization of the brain's functional architecture. In previous studies, connectome fingerprinting using brain functional connectivity profiles as an individualized trait was able to predict an individual's neurocognitive performance from the Human Connectome Project (HCP) neurocognitive datasets.

MATERIALS AND METHODS

In the present study, we extend connectome fingerprinting from functional connectivity (FC) to structural connectivity (SC), identifying multiple relationships between behavioral traits and brain connectivity. Higher-order neurocognitive tasks were found to have a weaker association with structural connectivity than its functional connectivity counterparts.

RESULTS

Neurocognitive tasks with a higher sensory footprint were, however, found to have a stronger association with structural connectivity than their functional connectivity counterparts. Language behavioral measurements had a particularly stronger correlation, especially between performance on the picture language test (Pic Vocab) and both FC (r = .28, p < .003) and SC (r = 0.27, p < .00077).

CONCLUSIONS

At the neural level, we found that the pattern of structural brain connectivity related to high-level language performance is consistent with the language white matter regions identified in presurgical mapping. We illustrate how this approach can be used to generalize the connectome fingerprinting framework to structural connectivity and how this can help understand the connections between cognitive behavior and the white matter connectome of the brain.

Inter-individual Differences in Occipital Alpha Oscillations Correlate with White Matter Tissue Properties of the Optic Radiation

Neural oscillations at ∼10 Hz, called alpha oscillations, are one of the most prominent components of neural oscillations in the human brain. In recent years, characteristics (power/frequency/phase) of occipital alpha oscillations have been correlated with various perceptual phenomena. However, the relationship between inter-individual differences in alpha oscillatory characteristics and the properties of the underlying brain structures, such as white matter pathways, is unclear. A possibility is that intrinsic occipital alpha oscillations are mediated by thalamocortical interaction; we hypothesized that the most promising candidate for characterizing the intrinsic alpha oscillation is optic radiation (OR), which is the geniculo-cortical pathway carrying signals between the lateral geniculate nucleus (LGN) and primary visual cortex (V1). We used resting-state magnetoencephalography (MEG) and diffusion-weighted/quantitative magnetic resonance imaging (MRI) (dMRI/qMRI) to correlate the frequency and power of occipital alpha oscillations with the tissue properties of the OR by focusing on the different characteristics across individuals. We found that the peak alpha frequency (PAF) negatively correlated with intracellular volume fraction (ICVF), reflecting diffusion properties in intracellular (axonal) space, whereas the peak alpha power was not correlated with any tissue properties measurements. No significant correlation was found between OR and beta frequency/amplitude or between other white matter tract connecting parietal and inferotemporal cortex and alpha frequency/amplitude. These results support the hypothesis that an interaction between thalamic nuclei and early visual areas is essential for the occipital alpha oscillatory rhythm.

Towards HCP-Style macaque connectomes: 24-Channel 3T multi-array coil, MRI sequences and preprocessing

Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain.

Microstructural Investigations of the Visual Pathways in Pediatric Epilepsy Neurosurgery: Insights From Multi-Shell Diffusion Magnetic Resonance Imaging

Background

Surgery is a key approach for achieving seizure freedom in children with focal onset epilepsy. However, the resection can affect or be in the vicinity of the optic radiations. Multi-shell diffusion MRI and tractography can better characterize tissue structure and provide guidance to help minimize surgical related deficits. Whilst in adults tractography has been used to demonstrate that damage to the optic radiations leads to postoperative visual field deficits, this approach has yet to be properly explored in children.

Objective

To demonstrate the capabilities of multi-shell diffusion MRI and tractography in characterizing microstructural changes in children with epilepsy pre- and post-surgery affecting the occipital, parietal or temporal lobes.

Methods

Diffusion Tensor Imaging and the Spherical Mean Technique were used to investigate the microstructure of the optic radiations. Furthermore, tractography was used to evaluate whether pre-surgical reconstructions of the optic radiations overlap with the resection margin as measured using anatomical post-surgical T1-weighted MRI.

Results

Increased diffusivity in patients compared to controls at baseline was observed with evidence of decreased diffusivity, anisotropy, and neurite orientation distribution in contralateral hemisphere after surgery. Pre-surgical optic radiation tractography overlapped with post-surgical resection margins in 20/43 (46%) children, and where visual data was available before and after surgery, the presence of overlap indicated a visual field deficit.

Conclusion

This is the first report in a pediatric series which highlights the relevance of tractography for future pre-surgical evaluation in children undergoing epilepsy surgery and the usefulness of multi-shell diffusion MRI to characterize brain microstructure in these patients.

Mapping Short Association Fibers in the Early Cortical Visual Processing Stream Using In Vivo Diffusion Tractography

Short association fibers (U-fibers) connect proximal cortical areas and constitute the majority of white matter connections in the human brain. U-fibers play an important role in brain development, function, and pathology but are underrepresented in current descriptions of the human brain connectome, primarily due to methodological challenges in diffusion magnetic resonance imaging (dMRI) of these fibers. High spatial resolution and dedicated fiber and tractography models are required to reliably map the U-fibers. Moreover, limited quantitative knowledge of their geometry and distribution makes validation of U-fiber tractography challenging. Submillimeter resolution diffusion MRI—facilitated by a cutting-edge MRI scanner with 300 mT/m maximum gradient amplitude—was used to map U-fiber connectivity between primary and secondary visual cortical areas (V1 and V2, respectively) in vivo. V1 and V2 retinotopic maps were obtained using functional MRI at 7T. The mapped V1–V2 connectivity was retinotopically organized, demonstrating higher connectivity for retinotopically corresponding areas in V1 and V2 as expected. The results were highly reproducible, as demonstrated by repeated measurements in the same participants and by an independent replication group study. This study demonstrates a robust U-fiber connectivity mapping in vivo and is an important step toward construction of a more complete human brain connectome.

Simultaneous use of individual and joint regularization terms in compressive sensing: Joint reconstruction of multi-channel multi-contrast MRI acquisitions

Multi-contrast images are commonly acquired together to maximize complementary diagnostic information, albeit at the expense of longer scan times. A time-efficient strategy to acquire high-quality multi-contrast images is to accelerate individual sequences and then reconstruct undersampled data with joint regularization terms that leverage common information across contrasts. However, these terms can cause features that are unique to a subset of contrasts to leak into the other contrasts. Such leakage-of-features may appear as artificial tissues, thereby misleading diagnosis. The goal of this study is to develop a compressive sensing method for multi-channel multi-contrast magnetic resonance imaging (MRI) that optimally utilizes shared information while preventing feature leakage. Joint regularization terms group sparsity and colour total variation are used to exploit common features across images while individual sparsity and total variation are also used to prevent leakage of distinct features across contrasts. The multi-channel multi-contrast reconstruction problem is solved via a fast algorithm based on Alternating Direction Method of Multipliers. The proposed method is compared against using only individual and only joint regularization terms in reconstruction. Comparisons were performed on single-channel simulated and multi-channel in-vivo datasets in terms of reconstruction quality and neuroradiologist reader scores. The proposed method demonstrates rapid convergence and improved image quality for both simulated and in-vivo datasets. Furthermore, while reconstructions that solely use joint regularization terms are prone to leakage-of-features, the proposed method reliably avoids leakage via simultaneous use of joint and individual terms, thereby holding great promise for clinical use.

Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain

In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 mm or smaller but degrades at 2 mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques.

Improved compressed sensing and super-resolution of cardiac diffusion MRI with structure-guided total variation

Purpose

Structure‐guided total variation is a recently introduced prior that allows reconstruction of images using knowledge of the location and orientation of edges in a reference image. In this work, we demonstrate the advantages of a variant of structure‐guided total variation known as directional total variation (DTV), over traditional total variation (TV), in the context of compressed‐sensing reconstruction and super‐resolution.

Methods

We compared TV and DTV in retrospectively undersampled ex vivo diffusion tensor imaging and diffusion spectrum imaging data from healthy, sham, and hypertrophic rat hearts.

Results

In compressed sensing at an undersampling factor of 8, the RMS error of mean diffusivity and fractional anisotropy relative to the fully sampled ground truth were 44% and 20% lower in DTV compared with TV. In super‐resolution, these values were 29% and 14%, respectively. Similarly, we observed improvements in helix angle, transverse angle, sheetlet elevation, and sheetlet azimuth. The RMS error of the diffusion kurtosis in the undersampled data relative to the ground truth was uniformly lower (22% on average) with DTV compared to TV.

Conclusion

Acquiring one fully sampled non‐diffusion‐weighted image and 10 diffusion‐weighted images at 8× undersampling would result in an 80% net reduction in data needed. We demonstrate efficacy of the DTV algorithm over TV in reducing data sampling requirements, which can be translated into higher apparent resolution and potentially shorter scan times. This method would be equally applicable in diffusion MRI applications outside the heart.

Correction of respiratory artifacts in MRI head motion estimates

Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison 'single-shot' datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.

MRI profiling of focal cortical dysplasia using multi-compartment diffusion models

Objective

Focal cortical dysplasia (FCD) lesion detection and subtyping remain challenging on conventional MRI. New diffusion models such as the spherical mean technique (SMT) and neurite orientation dispersion and density imaging (NODDI) provide measurements that potentially produce more specific maps of abnormal tissue microstructure. This study aims to assess the SMT and NODDI maps for computational and radiological lesion characterization compared to standard fractional anisotropy (FA) and mean diffusivity (MD).

Methods

SMT, NODDI, FA, and MD maps were calculated for 33 pediatric patients with suspected FCD (18 histologically confirmed). Two neuroradiologists scored lesion visibility on clinical images and diffusion maps. Signal profile changes within lesions and homologous regions were quantified using a surface‐based approach. Diffusion parameter changes at multiple cortical depths were statistically compared between FCD type IIa and type IIb.

Results

Compared to fluid‐attenuated inversion recovery (FLAIR) or T1‐weighted imaging, lesions conspicuity on NODDI intracellular volume fraction (ICVF) maps was better/equal/worse in 5/14/14 patients, respectively, while on SMT intra‐neurite volume fraction (INVF) in 3/3/27. Compared to FA or MD, lesion conspicuity on the ICVF was better/equal/worse in 27/4/2, while on the INVF in 20/7/6. Quantitative signal profiling demonstrated significant ICVF and INVF reductions in the lesions, whereas SMT microscopic mean, radial, and axial diffusivities were significantly increased. FCD type IIb exhibited greater changes than FCD type IIa. No changes were detected on FA or MD profiles.

Significance

FCD lesion‐specific signal changes were found in ICVF and INVF but not in FA and MD maps. ICVF and INVF showed greater contrast than FLAIR in some cases and had consistent signal changes specific to FCD, suggesting that they could improve current presurgical pediatric epilepsy imaging protocols and can provide features useful for automated lesion detection.

MRI Techniques to Decrease Imaging Times in Children

Long acquisition times can limit the use of MRI in pediatric patients, and the use of sedation or general anesthesia is frequently necessary to facilitate diagnostic examinations. The use of sedation or anesthesia has disadvantages including increased cost and imaging time and potential risks to the patient. Reductions in imaging time may decrease or eliminate the need for sedation or general anesthesia. Over the past decade, a number of imaging techniques that can decrease imaging time have become commercially available. These products have been used increasingly in clinical practice and include parallel imaging, simultaneous multisection imaging, radial k-space acquisition, compressed sensing MRI reconstruction, and automated protocol selection software. The underlying concepts, supporting data, current clinical applications, and available products for each of these strategies are reviewed in this article. In addition, emerging techniques that are still under investigation may provide further reductions in imaging time, including artificial intelligence-based reconstruction, gradient-controlled aliasing sampling and reconstruction, three-dimensional MR spectroscopy, and prospective motion correction. The preliminary results for these techniques are also discussed. ^©RSNA, 2020 See discussion on this article by Greer and Vasanawala.

A resource for the detailed 3D mapping of white matter pathways in the marmoset brain

While the fundamental importance of the white matter in supporting neuronal communication is well known, existing publications of primate brains do not feature a detailed description of its complex anatomy. The main barrier to achieving this is that existing primate neuroimaging data have insufficient spatial resolution to resolve white matter pathways fully. Here we present a resource that allows detailed descriptions of white matter structures and trajectories of fiber pathways in the marmoset brain. The resource includes: (1) the highest-resolution diffusion-weighted MRI data available to date, which reveal white matter features not previously described; (2) a comprehensive three-dimensional white matter atlas depicting fiber pathways that were either omitted or misidentified in previous atlases; and (3) comprehensive fiber pathway maps of cortical connections combining diffusion-weighted MRI tractography and neuronal tracing data. The resource, which can be downloaded from marmosetbrainmapping.org, will facilitate studies of brain connectivity and the development of tractography algorithms in the primate brain.

High-fidelity, high-isotropic-resolution diffusion imaging through gSlider acquisition with B1+ and T1 corrections and integrated ΔB0 /Rx shim array

PURPOSE

B 1 + and T1 corrections and dynamic multicoil shimming approaches were proposed to improve the fidelity of high-isotropic-resolution generalized slice-dithered enhanced resolution (gSlider) diffusion imaging.

METHODS

An extended reconstruction incorporating B 1 + inhomogeneity and T1 recovery information was developed to mitigate slab-boundary artifacts in short-repetition time (TR) gSlider acquisitions. Slab-by-slab dynamic B0 shimming using a multicoil integrated ΔB0 /Rx shim array and high in-plane acceleration (Rinplane = 4) achieved with virtual-coil GRAPPA were also incorporated into a 1-mm isotropic resolution gSlider acquisition/reconstruction framework to achieve a significant reduction in geometric distortion compared to single-shot echo planar imaging (EPI).

RESULTS

The slab-boundary artifacts were alleviated by the proposed B 1 + and T1 corrections compared to the standard gSlider reconstruction pipeline for short-TR acquisitions. Dynamic shimming provided >50% reduction in geometric distortion compared to conventional global second-order shimming. One-millimeter isotropic resolution diffusion data show that the typically problematic temporal and frontal lobes of the brain can be imaged with high geometric fidelity using dynamic shimming.

CONCLUSIONS

The proposed B 1 + and T1 corrections and local-field control substantially improved the fidelity of high-isotropic-resolution diffusion imaging, with reduced slab-boundary artifacts and geometric distortion compared to conventional gSlider acquisition and reconstruction. This enabled high-fidelity whole-brain 1-mm isotropic diffusion imaging with 64 diffusion directions in 20 min using a 3T clinical scanner.

Longitudinal structural connectomic and rich-club analysis in adolescent mTBI reveals persistent, distributed brain alterations acutely through to one year post-injury

The diffuse nature of mild traumatic brain injury (mTBI) impacts brain white-matter pathways with potentially long-term consequences, even after initial symptoms have resolved. To understand post-mTBI recovery in adolescents, longitudinal studies are needed to determine the interplay between highly individualised recovery trajectories and ongoing development. To capture the distributed nature of mTBI and recovery, we employ connectomes to probe the brain’s structural organisation. We present a diffusion MRI study on adolescent mTBI subjects scanned one day, two weeks and one year after injury with controls. Longitudinal global network changes over time suggests an altered and more ‘diffuse’ network topology post-injury (specifically lower transitivity and global efficiency). Stratifying the connectome by its back-bone, known as the ‘rich-club’, these network changes were driven by the ‘peripheral’ local subnetwork by way of increased network density, fractional anisotropy and decreased diffusivities. This increased structural integrity of the local subnetwork may be to compensate for an injured network, or it may be robust to mTBI and is exhibiting a normal developmental trend. The rich-club also revealed lower diffusivities over time with controls, potentially indicative of longer-term structural ramifications. Our results show evolving, diffuse alterations in adolescent mTBI connectomes beginning acutely and continuing to one year.

Analysis of errors in diffusion kurtosis imaging caused by slice crosstalk in simultaneous multi-slice imaging

Simultaneous multi-slice (SMS) imaging techniques accelerate diffusion MRI data acquisition. However, slice separation is imperfect and results in residual signal leakage between the simultaneously excited slices. The resulting consistent bias may adversely affect diffusion model parameter estimation. Although this bias is usually small and might not affect the simplified diffusion tensor model significantly, higher order diffusion models such as kurtosis are likely to be more susceptible to such effects. In this work, two SMS reconstruction techniques and an alternative acquisition approach were tested to quantify the effects of slice crosstalk on diffusion kurtosis parameters. In reconstruction, two popular slice separation algorithms, slice GRAPPA and split-slice GRAPPA, are evaluated to determine the effect of slice leakage on diffusion kurtosis metrics. For the alternative acquisition, the slice pairings were varied across diffusion weighted images such that the signal leakage does not come from the same overlapped slice for all diffusion encodings. Simulation results demonstrated the potential benefits of randomizing the slice pairings. However, various experimental factors confounded the advantages of slice pair randomization. In volunteer experiments, region-of-interest analyses found high metric errors with each of the SMS acquisitions and reconstructions in the brain white matter.

Complex diffusion-weighted image estimation via matrix recovery under general noise models

We propose a patch-based singular value shrinkage method for diffusion magnetic resonance image estimation targeted at low signal to noise ratio and accelerated acquisitions. It operates on the complex data resulting from a sensitivity encoding reconstruction, where asymptotically optimal signal recovery guarantees can be attained by modeling the noise propagation in the reconstruction and subsequently simulating or calculating the limit singular value spectrum. Simple strategies are presented to deal with phase inconsistencies and optimize patch construction. The pertinence of our contributions is quantitatively validated on synthetic data, an in vivo adult example, and challenging neonatal and fetal cohorts. Our methodology is compared with related approaches, which generally operate on magnitude-only data and use data-based noise level estimation and singular value truncation. Visual examples are provided to illustrate effectiveness in generating denoised and debiased diffusion estimates with well preserved spatial and diffusion detail.

Multi-shot diffusion-weighted MRI reconstruction with magnitude-based spatial-angular locally low-rank regularization (SPA-LLR)

PURPOSE

To resolve the motion-induced phase variations in multi-shot multi-direction diffusion-weighted imaging (DWI) by applying regularization to magnitude images.

THEORY AND METHODS

A nonlinear model was developed to estimate phase and magnitude images separately. A locally low-rank regularization (LLR) term was applied to the magnitude images from all diffusion-encoding directions to exploit the spatial and angular correlation. In vivo experiments with different resolutions and b-values were performed to validate the proposed method.

RESULTS

The proposed method significantly reduces the noise level compared to the conventional reconstruction method and achieves submillimeter (0.8mm and 0.9mm isotropic resolutions) DWI with a b-value of 1,000  s / mm 2 and 1-mm isotropic DWI with a b-value of 2,000  s / mm 2 without modification of the sequence.

CONCLUSIONS

A joint reconstruction method with spatial-angular LLR regularization on magnitude images substantially improves multi-direction DWI reconstruction, simultaneously removes motion-induced phase artifacts, and denoises images.

Tractography-based parcellation does not provide strong evidence of anatomical organisation within the thalamus

Connectivity-based parcellation of subcortical structures using diffusion tractography is now a common paradigm in neuroscience. These analyses often imply voxel-level specificity of connectivity, and the formation of compact, spatially coherent clusters is often taken as strong imaging-based evidence for anatomically distinct subnuclei in an individual. In this study, we demonstrate that internal structure in diffusion anisotropy is not necessary for a plausible parcellation to be obtained, by spatially permuting diffusion parameters within the thalami and repeating the parcellation. Moreover, we show that, in a winner-takes-all paradigm, most voxels receive the same label before and after this shuffling process-a finding that is stable across image acquisitions and tractography algorithms. We therefore suggest that such parcellations should be interpreted with caution.

Arterial stiffness cut-off value and white matter integrity in the elderly

Objective

Central artery stiffness is a confirmed predictor of cardiovascular health status that has been consistently associated with cognitive dysfunction and dementia. The European Society of Hypertension has established a threshold of arterial stiffness above which a cardiovascular event is likely to occur. However, the threshold at which arterial stiffness alters brain integrity has never been established.

Methods

The aim of this study is to determine the arterial stiffness cut-off value at which there is an impact on the white matter microstructure. This study has been conducted with 53 cognitively elderly without dementia. The integrity of the white matter was assessed using diffusion tensor metrics. Central artery stiffness was evaluated by measuring the carotid-femoral pulse wave velocity (cfPWV). The statistical analyses included 4 regions previously denoted vulnerable to increased central arterial stiffness (the corpus callosum, the internal capsule, the corona radiata and the superior longitudinal fasciculus).

Results

The results of this study call into question the threshold value of 10 m/s cfPWV established by the European Society of Hypertension to classify patients in neuro-cardiovascular risk groups. Our results suggest that the cfPWV threshold value would be approximately 8.5 m/s when the microstructure of the white matter is taken as a basis for comparison.

Conclusions

Adjustment of the cfPWV value may be necessary for a more accurate distinction between lower and higher risk group of patients for white matter microstructural injury related to arterial stiffness. Targeting the highest risk group for prevention methods may, in turn, help preserve brain health and cognitive functions.

•

DTI (FA, RD) analysis of white matter microstructure reveals that the cfPWV cut-off value (10 m/s) may be too high

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This study rather suggests a value of cfPWV cut-off of 8.5 m/s to separate lower and higher neurovascular risk groups

•

Better executive function performance is correlated with higher FA and lower RD in participants with a cfPWV above 8.5 m/s.

Tensor-valued diffusion MRI in under 3 minutes: an initial survey of microscopic anisotropy and tissue heterogeneity in intracranial tumors

PURPOSE

To evaluate the feasibility of a 3-minutes protocol for assessment of the microscopic anisotropy and tissue heterogeneity based on tensor-valued diffusion MRI in a wide range of intracranial tumors.

METHODS

B-tensor encoding was performed in 42 patients with intracranial tumors (gliomas, meningiomas, adenomas, and metastases). Microscopic anisotropy and tissue heterogeneity were evaluated by estimating the anisotropic kurtosis (MK_A ) and isotropic kurtosis (MK_I ), respectively. An extensive imaging protocol was compared with a 3-minutes protocol.

RESULTS

The fast imaging protocol yielded parameters with characteristics in terms of bias and precision similar to the full protocol. Glioblastomas had lower microscopic anisotropy than meningiomas (MK_A = 0.29 ± 0.06 vs. 0.45 ± 0.08, P = 0.003). Metastases had higher tissue heterogeneity (MK_I = 0.57 ± 0.07) than both the glioblastomas (0.44 ± 0.06, P < 0.001) and meningiomas (0.46 ± 0.06, P = 0.03).

CONCLUSION

Evaluation of the microscopic anisotropy and tissue heterogeneity in intracranial tumor patients is feasible in clinically relevant times frames.

Comparative neuroanatomy: Integrating classic and modern methods to understand association fibers connecting dorsal and ventral visual cortex

Comparative neuroanatomy studies improve understanding of brain structure and function and provide insight regarding brain development, evolution, and also what features of the brain are uniquely human. With modern methods such as diffusion MRI (dMRI) and quantitative MRI (qMRI), we are able to measure structural features of the brain with the same methods across human and non-human primates. In this review article, we discuss how recent dMRI measurements of vertical occipital connections in humans and macaques can be compared with previous findings from invasive anatomical studies that examined connectivity, including relatively forgotten classic strychnine neuronography studies. We then review recent progress in understanding the neuroanatomy of vertical connections within the occipitotemporal cortex by combining modern quantitative MRI and classical histological measurements in human and macaque. Finally, we a) discuss current limitations of dMRI and tractography and b) consider potential paths for future investigations using dMRI and tractography for comparative neuroanatomical studies of white matter tracts between species. While we focus on vertical association connections in visual cortex in the present paper, this same approach can be applied to other white matter tracts. Similar efforts are likely to continue to advance our understanding of the neuroanatomical features of the brain that are shared across species, as well as to distinguish the features that are uniquely human.

Accelerated whole-brain perfusion imaging using a simultaneous multislice spin-echo and gradient-echo sequence with joint virtual coil reconstruction

PURPOSE

Dynamic susceptibility contrast imaging requires high temporal sampling, which poses limits on achievable spatial coverage and resolution. Additionally, more encoding-intensive multi-echo acquisitions for quantitative imaging are desired to mitigate contrast leakage effects, which further limits spatial encoding. We present an accelerated sequence that provides whole-brain coverage at an improved spatio-temporal resolution, to allow for dynamic quantitative R2 and R2 * mapping during contrast-enhanced imaging.

METHODS

A multi-echo spin and gradient-echo sequence was implemented with simultaneous multislice acquisition. Complementary k-space sampling between repetitions and joint virtual coil reconstruction were used along with a dynamic phase-matching technique to achieve high-quality reconstruction at 9-fold acceleration, which enabled 2 × 2 × 5 mm whole-brain imaging at TR of 1.5 to 1.7 seconds. The multi-echo images from this sequence were fit to achieve quantitative R2 and R2 * maps for each repetition, and subsequently used to find perfusion measures including cerebral blood flow and cerebral blood volume.

RESULTS

Images reconstructed using joint virtual coil show improved image quality and g-factor compared with conventional reconstruction methods, resulting in improved quantitative maps with a 9-fold acceleration factor and whole-brain coverage during the dynamic perfusion acquisition.

CONCLUSION

The method presented shows the advantage of using a joint virtual coil-GRAPPA reconstruction to allow for high acceleration factors while maintaining reliable image quality for quantitative perfusion mapping, with the potential to improve tumor diagnostics and monitoring.

Language beyond the language system: Dorsal visuospatial pathways support processing of demonstratives and spatial language during naturalistic fast fMRI

Spatial demonstratives are powerful linguistic tools used to establish joint attention. Identifying the meaning of semantically underspecified expressions like "this one" hinges on the integration of linguistic and visual cues, attentional orienting and pragmatic inference. This synergy between language and extralinguistic cognition is pivotal to language comprehension in general, but especially prominent in demonstratives. In this study, we aimed to elucidate which neural architectures enable this intertwining between language and extralinguistic cognition using a naturalistic fMRI paradigm. In our experiment, 28 participants listened to a specially crafted dialogical narrative with a controlled number of spatial demonstratives. A fast multiband-EPI acquisition sequence (TR = 388 m s) combined with finite impulse response (FIR) modelling of the hemodynamic response was used to capture signal changes at word-level resolution. We found that spatial demonstratives bilaterally engage a network of parietal areas, including the supramarginal gyrus, the angular gyrus, and precuneus, implicated in information integration and visuospatial processing. Moreover, demonstratives recruit frontal regions, including the right FEF, implicated in attentional orienting and reference frames shifts. Finally, using multivariate similarity analyses, we provide evidence for a general involvement of the dorsal ("where") stream in the processing of spatial expressions, as opposed to ventral pathways encoding object semantics. Overall, our results suggest that language processing relies on a distributed architecture, recruiting neural resources for perception, attention, and extra-linguistic aspects of cognition in a dynamic and context-dependent fashion.

Investigating Gains in Neurocognition in an Intervention Trial of Exercise (IGNITE): Protocol

Despite the ubiquity of normal age-related cognitive decline there is an absence of effective approaches for improving neurocognitive health. Fortunately, moderate intensity exercise is a promising method for improving brain and cognitive health in late life, but its effectiveness remains a matter of skepticism and debate because of the absence of large, comprehensive, Phase III clinical trials. Here we describe the protocol for such a randomized clinical trial called IGNITE (Investigating Gains in Neurocognition in an Intervention Trial of Exercise), a study capable of more definitively addressing whether exercise influences cognitive and brain health in cognitively normal older adults. We are conducting a 12-month, multi-site, randomized dose-response exercise trial in 639 cognitively normal adults between 65 and 80 years of age. Participants are randomized to (1) a moderate intensity aerobic exercise condition of 150 min/week (N = 213), (2) a moderate intensity aerobic exercise condition at 225 min/week (N = 213), or (3) a light intensity stretching-and-toning control condition for 150 min/week (N = 213). Participants are engaging in 3 days/week of supervised exercise and two more days per week of unsupervised exercise for 12 months. A comprehensive cognitive battery, blood biomarkers and battery of psychosocial questionnaires is assessed at baseline, 6 and 12-months. In addition, brain magnetic resonance imaging, physiological biomarkers, cardiorespiratory fitness, physical function, and positron emission tomography of amyloid deposition are assessed at baseline and at the 12-month follow-up. The results from this trial could transform scientific-based policy and health care recommendations for approaches to improve cognitive function in cognitively normal older adults.

Tensor network factorizations: Relationships between brain structural connectomes and traits

Advanced brain imaging techniques make it possible to measure individuals' structural connectomes in large cohort studies non-invasively. Given the availability of large scale data sets, it is extremely interesting and important to build a set of advanced tools for structural connectome extraction and statistical analysis that emphasize both interpretability and predictive power. In this paper, we developed and integrated a set of toolboxes, including an advanced structural connectome extraction pipeline and a novel tensor network principal components analysis (TN-PCA) method, to study relationships between structural connectomes and various human traits such as alcohol and drug use, cognition and motion abilities. The structural connectome extraction pipeline produces a set of connectome features for each subject that can be organized as a tensor network, and TN-PCA maps the high-dimensional tensor network data to a lower-dimensional Euclidean space. Combined with classical hypothesis testing, canonical correlation analysis and linear discriminant analysis techniques, we analyzed over 1100 scans of 1076 subjects from the Human Connectome Project (HCP) and the Sherbrooke test-retest data set, as well as 175 human traits measuring different domains including cognition, substance use, motor, sensory and emotion. The test-retest data validated the developed algorithms. With the HCP data, we found that structural connectomes are associated with a wide range of traits, e.g., fluid intelligence, language comprehension, and motor skills are associated with increased cortical-cortical brain structural connectivity, while the use of alcohol, tobacco, and marijuana are associated with decreased cortical-cortical connectivity. We also demonstrated that our extracted structural connectomes and analysis method can give superior prediction accuracies compared with alternative connectome constructions and other tensor and network regression methods.

Diffusion Acceleration with Gaussian process Estimated Reconstruction (DAGER)

PURPOSE

Image acceleration provides multiple benefits to diffusion MRI, with in-plane acceleration reducing distortion and slice-wise acceleration increasing the number of directions that can be acquired in a given scan time. However, as acceleration factors increase, the reconstruction problem becomes ill-conditioned, particularly when using both in-plane acceleration and simultaneous multislice imaging. In this work, we develop a novel reconstruction method for in vivo MRI acquisition that provides acceleration beyond what conventional techniques can achieve.

THEORY AND METHODS

We propose to constrain the reconstruction in the spatial (k) domain by incorporating information from the angular (q) domain. This approach exploits smoothness of the signal in q-space using Gaussian processes, as has previously been exploited in post-reconstruction analysis. We demonstrate in-plane undersampling exceeding the theoretical parallel imaging limits, and simultaneous multislice combined with in-plane undersampling at a total factor of 12. This reconstruction is cast within a Bayesian framework that incorporates estimation of smoothness hyper-parameters, with no need for manual tuning.

RESULTS

Simulations and in vivo results demonstrate superior performance of the proposed method compared with conventional parallel imaging methods. These improvements are achieved without loss of spatial or angular resolution and require only a minor modification to standard pulse sequences.

CONCLUSION

The proposed method provides improvements over existing methods for diffusion acceleration, particularly for high simultaneous multislice acceleration with in-plane undersampling.

Are global and specific interindividual differences in cortical thickness associated with facets of cognitive abilities, including face cognition?

Face cognition (FC) is a specific ability that cannot be fully explained by general cognitive functions. Cortical thickness (CT) is a neural correlate of performance and learning. In this registered report, we used data from the Human Connectome Project (HCP) to investigate the relationship between CT in the core brain network of FC and performance on a psychometric task battery, including tasks with facial content. Using structural equation modelling (SEM), we tested the existence of face-specific interindividual differences at behavioural and neural levels. The measurement models include general and face-specific factors of performance and CT. There was no face-specificity in CT in functionally localized areas. In post hoc analyses, we compared the preregistered, small regions of interest (ROIs) to larger, non-individualized ROIs and identified a face-specific CT factor when large ROIs were considered. We show that this was probably due to low reliability of CT in the functional localization (intra-class correlation coefficients (ICC) between 0.72 and 0.85). Furthermore, general cognitive ability, but not face-specific performance, could be predicted by latent factors of CT with a small effect size. In conclusion, for the core brain network of FC, we provide exploratory evidence (in need of cross-validation) that areas of the cortex sharing a functional purpose did also share morphological properties as measured by CT.

Phase-matched virtual coil reconstruction for highly accelerated diffusion echo-planar imaging

PURPOSE

To propose a virtual coil (VC) acquisition/reconstruction framework to improve highly accelerated single-shot EPI (SS-EPI) and generalized slice dithered enhanced resolution (gSlider) acquisition in high-resolution diffusion imaging (DI).

METHODS

For robust VC-GRAPPA reconstruction, a background phase correction scheme was developed to match the image phase of the reference data with the corrupted phase of the accelerated diffusion-weighted data, where the corrupted phase of the diffusion data varies from shot to shot. A Gy prewinding-blip was also added to the EPI acquisition, to create a shifted-ky sampling strategy that allows for better exploitation of VC concept in the reconstruction. To evaluate the performance of the proposed methods, 1.5 mm isotropic whole-brain SS-EPI and 860 μm isotropic whole-brain gSlider-EPI diffusion data were acquired at an acceleration of 8-9 fold. Conventional and VC-GRAPPA reconstructions were performed and compared, and corresponding g-factors were calculated.

RESULTS

The proposed VC reconstruction substantially improves the image quality of both SS-EPI and gSlider-EPI, with reduced g-factor noise and reconstruction artifacts when compared to the conventional method. This has enabled high-quality low-noise diffusion imaging to be performed at 8-9 fold acceleration.

CONCLUSIONS

The proposed VC acquisition/reconstruction framework improves the reconstruction of DI at high accelerations. The ability to now employ such high accelerations will allow DI with EPI at reduced distortion and faster scan time, which should be beneficial for many clinical and neuroscience applications.

Comparison of magnetization transfer contrast of conventional and simultaneous multislice turbo spin echo acquisitions focusing on excitation time interval

PURPOSE

Image contrast differs between conventional multislice turbo spin echo (conventional TSE) and multiband turbo spin echo (SMS-TSE). Difference in time interval between excitations for adjacent slices (SETI) might cause this difference. This study aimed to evaluate the influence of SETI on MT effect for conventional TSE and compare conventional TSE with SMS-TSE in this respect.

MATERIALS AND METHODS

Three different agar concentration phantoms were scanned with conventional TSE by adjusting SETI and TR. Signal change for different SETI was evaluated using Pearson's correlation analysis. SMS-TSE was acquired by changing TR similarly. Three human volunteers were scanned with similar settings to evaluate reproducibility of the phantom results in human brain.

RESULTS

In conventional TSE, shorter SETI induced larger signal reduction. Longer TR and higher agar concentration emphasized this characteristic. Significant linear correlation (P < 0.05) was found in the major cases. The SMS-TSE signal intensity in each TR and phantom was smaller than the assumable levels in conventional TSE when the slices were simultaneously excited. Similar characteristic was observed in human brain.

CONCLUSION

Shorter SETI results in larger MT effect in conventional TSE. The contrast change in SMS-TSE was larger than the supposable level from simultaneous excitation, which needs consideration in clinics.

Common Information Enhanced Reconstruction for Accelerated High-resolution Multi-shot Diffusion Imaging

PURPOSE

Multi-shot technique can effectively achieve high-resolution diffusion weighted images, but the acquisition time of multi-shot technique is prolonged, especially for multiple direction diffusion encoding. Thus, increasing acquisition efficiency is highly desirable for high-resolution diffusion tensor imaging (DTI). In this study, based on the assumption that different diffusion directions share the common information, image ratio constrained reconstruction (IRCR) combined with iterative self-consistent parallel imaging reconstruction (SPIRiT) is proposed to improve data sampling efficiency and image reconstruction fidelity for high-resolution DTI.

THEORY AND METHODS

The proposed reconstruction framework is named Common Information Enhanced Reconstruction (CIER). Inter-image correlation among different direction diffusion-weighted images is used through common information, which is an isotropic component and structure, for improving the performance of reconstruction. The framework consists of three steps. (i) Pre-processing: three intermediate multi-shot images, low-resolution composite image, high-resolution composite image and low-resolution diffusion weighted image, are generated based on the SPIRiT method. (ii) IRCR: the initial high-resolution diffusion weighted image is calculated from the images in step (i) based on that the ratio map between high-resolution images is approximated by the ratio map between the corresponding low-resolution images. (iii) Final SPIRiT reconstruction: the final image is generated with the image from IRCR as initialization by considering data consistency only in the SPIRiT calculation. A specific implementation based on multishot variable density spiral (VDS) DTI is used to demonstrate the method.

RESULTS

The proposed CIER method was compared with the traditional reconstruction methods, conjugate gradient SENSE (CG-SENSE), L1-regularized SPIRiT (L1-SPIRiT), and anisotropic-sparsity SPIRiT (AS-SPIRiT) in brain DTI at acceleration factors of 3 to 7. CIER provided better diffusion image quality than other methods shown by both qualitative and quantitative results, especially at higher undersampling acceleration factors.

CONCLUSION

CIER offers better diffusion image quality at higher undersampling acceleration factors for high-resolution DTI. Both qualitative and quantitative results prove that common information can be used to improve sampling efficiency and maintain the image quality of diffusion-weighted images.

Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network

PURPOSE

In diffusion-weighted magnetic resonance imaging (DW-MRI), the fiber orientation distribution function (fODF) is of great importance for solving complex fiber configurations to achieve reliable tractography throughout the brain, which ultimately facilitates the understanding of brain connectivity and exploration of neurological dysfunction. Recently, multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) method has been explored for reconstructing full fODFs. To achieve a reliable fitting, similar to other model-based approaches, a large number of diffusion measurements is typically required for MSMT-CSD method. The prolonged acquisition is, however, not feasible in practical clinical routine and is prone to motion artifacts. To accelerate the acquisition, we proposed a method to reconstruct the fODF from downsampled diffusion-weighted images (DWIs) by leveraging the strong inference ability of the deep convolutional neural network (CNN).

METHODS

The method treats spherical harmonics (SH)-represented DWI signals and fODF coefficients as inputs and outputs, respectively. To compensate for the reduced gradient directions with reduced number of DWIs in acquisition in each voxel, its surrounding voxels are incorporated by the network for exploiting their spatial continuity. The resulting fODF coefficients are fitted with applying the CNN in a multi-target regression model. The network is composed of two convolutional layers and three fully connected layers. To obtain an initial evaluation of the method, we quantitatively measured its performance on a simulated dataset. Then, for in vivo tests, we employed data from 24 subjects from the Human Connectome Project (HCP) as training set and six subjects as test set. The performance of the proposed method was primarily compared to the super-resolved MSMT-CSD with the decreasing number of DWIs. The fODFs reconstructed by MSMT-CSD from all available 288 DWIs were used as training labels and the reference standard. The performance was quantitatively measured by the angular correlation coefficient (ACC) and the mean angular error (MAE).

RESULTS

For the simulated dataset, the proposed method exhibited the potential advantage over the model reconstruction. For the in vivo dataset, it achieved superior results over the MSMT-CSD in all the investigated cases, with its advantage more obvious when a limited number of DWIs were used. As the number of DWIs was reduced from 95 to 25, the median ACC ranged from 0.96 to 0.91 for the CNN, but 0.93 to 0.77 for the MSMT-CSD (with perfect score of 1). The angular error in the typical regions of interest (ROIs) was also much lower, especially in multi-fiber regions. The average MAE for the CNN method in regions containing one, two, three fibers was, respectively, 1.09°, 2.75°, and 8.35° smaller than the MSMT-CSD method. The visual inception of the fODF further confirmed this superiority. Moreover, the tractography results validated the effectiveness of the learned fODF, in preserving known major branching fibers with only 25 DWIs.

CONCLUSION

Experiments on HCP datasets demonstrated the feasibility of the proposed method in recovering fODFs from up to 11-fold reduced number of DWIs. The proposed method offers a new streamlined reconstruction procedure and exhibits promising potential in acquisition acceleration for the reconstruction of fODFs with good accuracy.