Optimization of 3D dynamic speech MRI: Poisson-disc undersampling and locally higher-rank reconstruction through partial separability model with regional optimized temporal basis.

PURPOSE: To improve the spatiotemporal qualities of images and dynamics of speech MRI through an improved data sampling and image reconstruction approach. METHODS: For data acquisition, we used a Poisson-disc random under sampling scheme that reduced the undersampling coherence. For image reconstruction, we proposed a novel locally higher-rank partial separability model. This reconstruction model represented the oral and static regions using separate low-rank subspaces, therefore, preserving their distinct temporal signal characteristics. Regional optimized temporal basis was determined from the regional-optimized virtual coil approach. Overall, we achieved a better spatiotemporal image reconstruction quality with the potential of reducing total acquisition time by 50%. RESULTS: The proposed method was demonstrated through several 2-mm isotropic, 64 mm total thickness, dynamic acquisitions with 40 frames per second and compared to the previous approach using a global subspace model along with other k-space sampling patterns. Individual timeframe images and temporal profiles of speech samples were shown to illustrate the ability of the Poisson-disc under sampling pattern in reducing total acquisition time. Temporal information of sagittal and coronal directions was also shown to illustrate the effectiveness of the locally higher-rank operator and regional optimized temporal basis. To compare the reconstruction qualities of different regions, voxel-wise temporal SNR analysis were performed. CONCLUSION: Poisson-disc sampling combined with a locally higher-rank model and a regional-optimized temporal basis can drastically improve the spatiotemporal image quality and provide a 50% reduction in overall acquisition time.

Measuring CSF shunt flow with MRI using flow enhancement of signal intensity (FENSI).

PURPOSE: To develop and validate a noninvasive imaging technique for accurately assessing very slow CSF flow within shunt tubes in pediatric patients with hydrocephalus, aiming to identify obstructions that might impede CSF drainage. THEORY AND METHODS: A simulation of shunt flow enhancement of signal intensity (shunt-FENSI) signal is used to establish the relationship between signal change and flow rate. The quantification of flow enhancement of signal intensity data involves normalization, curve fitting, and calibration to match simulated data. Additionally, a phase sweep method is introduced to accommodate the impact of magnetic field inhomogeneity on the flow measurement. The method is tested in flow phantoms, healthy adults, intensive care unit patients with external ventricular drains (EVD), and shunt patients. EVDs enable shunt-flow measurements to be acquired with a ground truth measure of CSF drainage. RESULTS: The flow-rate-to-signal simulation establishes signal-flow relationships and takes into account the T1 of draining fluid. The phase sweep method accurately accounts for phase accumulation due to frequency offsets at the shunt. Results in phantom and healthy human participants reveal reliable quantification of flow rates using controlled flows and agreement with the flow simulation. EVD patients display reliable measures of flow rates. Shunt patient results demonstrate feasibility of the method and consistent flow rates for functional shunts. CONCLUSION: The results demonstrate the technique's applicability, accuracy, and potential for diagnosing and noninvasively monitoring hydrocephalus. Limitations of the current approach include a high sensitivity to motion and strict requirement of imaging slice prescription.

Associations between infant amygdala functional connectivity and social engagement following a stressor: A preliminary investigation.

Functional architecture of the infant brain, especially functional connectivity (FC) within the amygdala network and between the amygdala and other networks (i.e., default-mode [DMN] and salience [SAL] networks), provides a neural basis for infant socioemotional functioning. Yet, little is known about the extent to which early within- and between-network amygdala FC are related to infant stress recovery across the first year of life. In this study, we examined associations between amygdala FC (i.e., within-network amygdala connectivity, and between-network amygdala connectivity with the DMN and SAL) at 3 months and infant recovery from a mild social stressor at 3, 6 and 9 months. At 3 months, thirty-five infants (13 girls) underwent resting-state functional magnetic resonance imaging during natural sleep. Infants and their mothers completed the still-face paradigm at 3, 6, and 9 months, and infant stress recovery was assessed at each time point as the proportion of infant social engagement during the reunion episode. Bivariate correlations indicated that greater positive within-network amygdala FC and greater positive amygdala-SAL FC, but not amygdala-DMN FC, at 3 months predicted lower levels of stress recovery at 3 and 6 months, but were nonsignificant at 9 months. These findings provide preliminary evidence that early functional synchronization within the amygdala network, as well as segregation between the amygdala and the SAL, may contribute to infant stress recovery in the context of infant-mother interaction.

Functional neural network connectivity at 3 months predicts infant-mother dyadic flexibility during play at 6 months.

Early functioning of neural networks likely underlies the flexible switching between internal and external orientation and may be key to the infant's ability to effectively engage in social interactions. To test this hypothesis, we examined the association between infants' neural networks at 3 months and infant-mother dyadic flexibility (denoting the structural variability of their interaction dynamics) at 3, 6, and 9 months. Participants included thirty-five infants (37% girls) and their mothers (87% White). At 3 months, infants participated in a resting-state functional magnetic resonance imaging session, and functional connectivity (FC) within the default mode (DMN) and salience (SN) networks, as well as DMN-SN internetwork FC, were derived using a seed-based approach. When infants were 3, 6, and 9 months, infant-mother dyads completed the Still-Face Paradigm where their individual engagement behaviors were observed and used to quantify dyadic flexibility using state space analysis. Results revealed that greater within-DMN FC, within-SN FC, and DMN-SN anticorrelation at 3 months predicted greater dyadic flexibility at 6 months, but not at 3 and 9 months. Findings suggest that early synchronization and interaction between neural networks underlying introspection and salience detection may support infants' flexible social interactions as they become increasingly active and engaged social partners.

Development and validation of a quality control procedure for automatic segmentation of hippocampal subfields.

Automatic segmentation methods for in vivo magnetic resonance imaging are increasing in popularity because of their high efficiency and reproducibility. However, automatic methods can be perfectly reliable and consistently wrong, and the validity of automatic segmentation methods cannot be taken for granted. Quality control (QC) by trained and reliable human raters is necessary to ensure the validity of automatic measurements. Yet QC practices for applied neuroimaging research are underdeveloped. We report a detailed QC and correction procedure to accompany our validated atlas for hippocampal subfield segmentation. We document a two-step QC procedure for identifying segmentation errors, along with a taxonomy of errors and an error severity rating scale. This detailed procedure has high between-rater reliability for error identification and manual correction. The latter introduces at maximum 3% error variance in volume measurement. All procedures were cross-validated on an independent sample collected at a second site with different imaging parameters. The analysis of error frequency revealed no evidence of bias. An independent rater with a third sample replicated procedures with high within-rater reliability for error identification and correction. We provide recommendations for implementing the described method along with hypothesis testing strategies. In sum, we present a detailed QC procedure that is optimized for efficiency while prioritizing measurement validity and suits any automatic atlas.

Enhancing linguistic research through 2-mm isotropic 3D dynamic speech MRI optimized by sparse temporal sampling and low-rank reconstruction.

PURPOSE: To enable a more comprehensive view of articulations during speech through near-isotropic 3D dynamic MRI with high spatiotemporal resolution and large vocal-tract coverage. METHODS: Using partial separability model-based low-rank reconstruction coupled with a sparse acquisition of both spatial and temporal models, we are able to achieve near-isotropic resolution 3D imaging with a high frame rate. The total acquisition time of the speech acquisition is shortened by introducing a sparse temporal sampling that interleaves one temporal navigator with four randomized phase and slice-encoded imaging samples. Memory and computation time are improved through compressing coils based on the region of interest for low-rank constrained reconstruction with an edge-preserving spatial penalty. RESULTS: The proposed method has been evaluated through experiments on several speech samples, including a standard reading passage. A near-isotropic 1.875 × 1.875 × 2 mm3 spatial resolution, 64-mm through-plane coverage, and a 35.6-fps temporal resolution are achieved. Investigations and analysis on specific speech samples support novel insights into nonsymmetric tongue movement, velum raising, and coarticulation events with adequate visualization of rapid articulatory movements. CONCLUSION: Three-dimensional dynamic images of the vocal tract structures during speech with high spatiotemporal resolution and axial coverage is capable of enhancing linguistic research, enabling visualization of soft tissue motions that are not possible with other modalities.

Preliminary Development of an MRI Atlas for Application to Cleft Care: Findings and Future Recommendations.

OBJECTIVE: To introduce a highly innovative imaging method to study the complex velopharyngeal (VP) system and introduce the potential future clinical applications of a VP atlas in cleft care. DESIGN: Four healthy adults participated in a 20-min dynamic magnetic resonance imaging scan that included a high-resolution T2-weighted turbo-spin-echo 3D structural scan and five custom dynamic speech imaging scans. Subjects repeated a variety of phrases when in the scanner as real-time audio was captured. SETTING: Multisite institution and clinical setting. PARTICIPANTS: Four adult subjects with normal anatomy were recruited for this study. MAIN OUTCOME: Establishment of 4-D atlas constructed from dynamic VP MRI data. RESULTS: Three-dimensional dynamic magnetic resonance imaging was successfully used to obtain high quality dynamic speech scans in an adult population. Scans were able to be re-sliced in various imaging planes. Subject-specific MR data were then reconstructed and time-aligned to create a velopharyngeal atlas representing the averaged physiological movements across the four subjects. CONCLUSIONS: The current preliminary study examined the feasibility of developing a VP atlas for potential clinical applications in cleft care. Our results indicate excellent potential for the development and use of a VP atlas for assessing VP physiology during speech.

DeepSENSE: Learning coil sensitivity functions for SENSE reconstruction using deep learning.

PURPOSE: To improve the estimation of coil sensitivity functions from limited auto-calibration signals (ACS) in SENSE-based reconstruction for brain imaging. METHODS: We propose to use deep learning to estimate coil sensitivity functions by leveraging information from previous scans obtained using the same RF receiver system. Specifically, deep convolutional neural networks were designed to learn an end-to-end mapping from the initial sensitivity to the high-resolution counterpart. Sensitivity alignment was further proposed to reduce the geometric variation caused by different subject positions and imaging FOVs. Cross-validation with a small set of datasets was performed to validate the learned neural network. Iterative SENSE reconstruction was adopted to evaluate the utility of the sensitivity functions from the proposed and conventional methods. RESULTS: The proposed method produced improved sensitivity estimates and SENSE reconstructions compared to the conventional methods in terms of aliasing and noise suppression with very limited ACS data. Cross-validation with a small set of data demonstrated the feasibility of learning coil sensitivity functions for brain imaging. The network learned on the spoiled GRE data can be applied to predict sensitivity functions for spin-echo and MPRAGE datasets. CONCLUSION: A deep learning-based method has been proposed for improving the estimation of coil sensitivity functions. Experimental results have demonstrated the feasibility and potential of the proposed method for improving SENSE-based reconstructions especially when the ACS data are limited.

Establishing a Clinical Protocol for Velopharyngeal MRI and Interpreting Imaging Findings.

Traditional imaging modalities used to assess velopharyngeal insufficiency (VPI) do not allow for direct visualization of underlying velopharyngeal (VP) structures and musculature which could impact surgical planning. This limitation can be overcome via structural magnetic resonance imaging (MRI), the only current imaging tool that provides direct visualization of salient VP structures. MRI has been used extensively in research; however, it has had limited clinical use. Factors that restrict clinical use of VP MRI include limited access to optimized VP MRI protocols and uncertainty regarding how to interpret VP MRI findings. The purpose of this paper is to outline a framework for establishing a novel VP MRI scan protocol and to detail the process of interpreting scans of the velopharynx at rest and during speech tasks. Additionally, this paper includes common scan parameters needed to allow for visualization of velopharynx and techniques for the elicitation of speech during scans.

Proof-of-concept evidence for trimodal simultaneous investigation of human brain function.

The link between spatial (where) and temporal (when) aspects of the neural correlates of most psychological phenomena is not clear. Elucidation of this relation, which is crucial to fully understand human brain function, requires integration across multiple brain imaging modalities and cognitive tasks that reliably modulate the engagement of the brain systems of interest. By overcoming the methodological challenges posed by simultaneous recordings, the present report provides proof-of-concept evidence for a novel approach using three complementary imaging modalities: functional magnetic resonance imaging (fMRI), event-related potentials (ERPs), and event-related optical signals (EROS). Using the emotional oddball task, a paradigm that taps into both cognitive and affective aspects of processing, we show the feasibility of capturing converging and complementary measures of brain function that are not currently attainable using traditional unimodal or other multimodal approaches. This opens up unprecedented possibilities to clarify spatiotemporal integration of brain function.

Quantification of magnetic resonance spectroscopy data using a combined reference: Application in typically developing infants.

Quantification of proton magnetic resonance spectroscopy (1 H-MRS) data is commonly performed by referencing the ratio of the signal from one metabolite, or metabolite group, to that of another, or to the water signal. Both approaches have drawbacks: ratios of two metabolites can be difficult to interpret because study effects may be driven by either metabolite, and water-referenced data must be corrected for partial volume and relaxation effects in the water signal. Here, we introduce combined reference (CRef) analysis, which compensates for both limitations. In this approach, metabolites are referenced to the combined signal of several reference metabolites or metabolite groups. The approach does not require the corrections necessary for water scaling and produces results that are less sensitive to the variation of any single reference signal, thereby aiding the interpretation of results. We demonstrate CRef analysis using 202 1 H-MRS acquisitions from the brains of 140 infants, scanned at approximately 1 and 3 months of age. We show that the combined signal of seven reference metabolites or metabolite groups is highly correlated with the water signal, corrected for partial volume and relaxation effects associated with cerebral spinal fluid. We also show that the combined reference signal is equally or more uniform across subjects than the reference signals from single metabolites or metabolite groups. We use CRef analysis to quantify metabolite concentration changes during the first several months of life in typically developing infants.

Do subcortical gray matter volumes and aerobic capacity account for cognitive-motor coupling in multiple sclerosis?

BACKGROUND: There is evidence of cognitive-motor coupling in multiple sclerosis (MS) such that the slowing of cognitive processing speed correlates with the worsening of walking speed and endurance. OBJECTIVE: The current study first established the presence of cognitive-motor coupling and second examined the possibility that volumes of subcortical gray matter (SGM) structures and aerobic capacity might explain the coupling of cognitive and motor functions in persons with MS. METHODS: We included data from 62 persons with clinically definite MS who underwent assessments of cognitive processing speed, walking performance, and aerobic capacity, and completed magnetic resonance imaging (MRI) within 7 days of the aforementioned assessments. RESULTS: The strong correlations between cognitive processing speed and walking performance were attenuated in magnitude and not statistically significant when controlling for aerobic capacity alone and aerobic capacity and SGM volumes together. The associations between cognitive processing speed and walking performance remained statistically significant when controlling for SGM volumes alone. CONCLUSION: Aerobic capacity may be an important target for neurorehabilitation-based approaches for managing co-occurring cognitive and motor dysfunction in MS.

Brain stiffness following recovery in a patient with an episode of low-pressure hydrocephalus: case report.

The authors describe a follow-up to a case of a 19-year-old female with shunted aqueductal stenosis who presented with low-pressure hydrocephalus during a shunt malfunction. Shortly after management with CSF drainage at negative pressure, a magnetic resonance elastography scan was performed and revealed very low brain stiffness (high compliance). Here we present the case of the same patient seen 2 years later, now 21 years old, who again received a magnetic resonance elastography scan after receiving treatment for another shunt malfunction, this time with high intracranial pressure. This scan revealed recovery of brain stiffness to a near normal value for the patients' age. This observation suggests the low brain stiffness observed during the low-pressure hydrocephalus event is reversible. The authors discuss these findings in relation to biomechanical hypotheses of low-pressure hydrocephalus.

4D magnetic resonance imaging atlas construction using temporally aligned audio waveforms in speech.

Magnetic resonance (MR) imaging is becoming an established tool in capturing articulatory and physiological motion of the structures and muscles throughout the vocal tract and enabling visual and quantitative assessment of real-time speech activities. Although motion capture speed has been regularly improved by the continual developments in high-speed MR technology, quantitative analysis of multi-subject group data remains challenging due to variations in speaking rate and imaging time among different subjects. In this paper, a workflow of post-processing methods that matches different MR image datasets within a study group is proposed. Each subject's recorded audio waveform during speech is used to extract temporal domain information and generate temporal alignment mappings from their matching pattern. The corresponding image data are resampled by deformable registration and interpolation of the deformation fields, achieving inter-subject temporal alignment between image sequences. A four-dimensional dynamic MR speech atlas is constructed using aligned volumes from four human subjects. Similarity tests between subject and target domains using the squared error, cross correlation, and mutual information measures all show an overall score increase after spatiotemporal alignment. The amount of image variability in atlas construction is reduced, indicating a quality increase in the multi-subject data for groupwise quantitative analysis.

A performance-based measure of emotion response control: A preliminary MRI study.

Identifying performance-based assessments of emotion regulation is needed for the study of myriad mood and neurological disorders. Color and form responses on the Rorschach Inkblot Method are valid measures of emotion response control, but have not been studied in relation to known neural correlations of emotion regulation. A discrepancy of color (CF + C) greater than form (FC) responses suggests low cognitive control over emotional responses. This preliminary report explores the discrepancy between form-color responses as a correlate of regional cortical thickness. A sample of community-dwelling adults were administered the Rorschach Inkblot Method and participated in a structural MRI scan. Greater middle frontal cortex thickness was associated with a positive discrepancy score [(CF + C) - FC], indicating less emotion response control (rs  = 0.48, p < 0.05); a moderate, non-significant correlation was also observed with insula cortex (rs  = 0.42, p = 0.07).The results provide evidence in support of the Rorschach Inkblot Method as a valid behavioral measure of emotion response control. More specifically, these results support the use of color-related variables included in contemporary evidence-based Rorschach methods. The results are discussed with implications for the study of emotion regulation in mood disorders and sensitivity analyses based on the observed effect sizes are reported to inform future study planning.

Standard-space atlas of the viscoelastic properties of the human brain.

Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast-based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18-35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, µ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM-152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross-center comparisons.

Intravoxel B0 inhomogeneity corrected reconstruction using a low-rank encoding operator.

PURPOSE: To present a general and efficient method for macroscopic intravoxel B0 inhomogeneity corrected reconstruction from multi-TE acquisitions. THEORY AND METHODS: A signal encoding model for multi-TE gradient echo (GRE) acquisitions that incorporates 3D intravoxel B0 field variations is derived, and a low-rank approximation to the encoding operator is introduced under piecewise linear B0 assumption. The low-rank approximation enables very efficient computation and memory usage, and allows the proposed signal model to be integrated into general inverse problem formulations that are compatible with multi-coil and undersampling acquisitions as well as different regularization functions. RESULTS: Experimental multi-echo GRE data were acquired to evaluate the proposed method. Effective reduction of macroscopic intravoxel B0 inhomogeneity induced artifacts was demonstrated. Improved R2∗ estimation from the corrected reconstruction over standard Fourier reconstruction has also been obtained. CONCLUSIONS: The proposed method can effectively correct the effects of intravoxel B0 inhomogeneity, and can be useful for various imaging applications involving GRE-based acquisitions, including fMRI, quantitative R2∗ and susceptibility mapping, and MR spectroscopic imaging.

Structural and Functional MRI Evidence for Distinct Medial Temporal and Prefrontal Roles in Context-dependent Relational Memory.

Declarative memory is supported by distributed brain networks in which the medial-temporal lobes (MTLs) and pFC serve as important hubs. Identifying the unique and shared contributions of these regions to successful memory performance is an active area of research, and a growing literature suggests that these structures often work together to support declarative memory. Here, we present data from a context-dependent relational memory task in which participants learned that individuals belonged in a single room in each of two buildings. Room assignment was consistent with an underlying contextual rule structure in which male and female participants were assigned to opposite sides of a building and the side assignment switched between buildings. In two experiments, neural correlates of performance on this task were evaluated using multiple neuroimaging tools: diffusion tensor imaging (Experiment 1), magnetic resonance elastography (Experiment 1), and functional MRI (Experiment 2). Structural and functional data from each individual modality provided complementary and consistent evidence that the hippocampus and the adjacent white matter tract (i.e., fornix) supported relational memory, whereas the ventromedial pFC/OFC (vmPFC/OFC) and the white matter tract connecting vmPFC/OFC to MTL (i.e., uncinate fasciculus) supported memory-guided rule use. Together, these data suggest that MTL and pFC structures differentially contribute to and support contextually guided relational memory.

Correction of magnetic field inhomogeneity effects for fast quantitative susceptibility mapping.

PURPOSE: Quantitative susceptibility mapping (QSM) provides information about tissue composition and organization. However, current acquisition methods can be quite time consuming, limiting the use of QSM in studies and in monitoring dynamic events. In this work, time efficient spiral acquisitions are combined with a model-based image reconstruction approach. Magnetic field inhomogeneity artifacts are corrected to obtain full brain susceptibility maps. METHODS: Magnetic field maps, capturing the magnetic field inhomogeneity distribution due to non-tissue sources (background field), were estimated from a calibration scan. Tissue phase information present in the background field maps was identified using variable spherical mean value filtering and removed from the estimated field maps. The resulting background field maps were then used in the image reconstruction to correct the magnetic field inhomogeneity artifacts. Images were acquired on a 3 T system with a 3D spiral-in acquisition based on a rotated stack of spirals. For comparison, standard gradient echo images were also acquired. Susceptibility maps were obtained for both acquisitions using a dipole inversion algorithm based on a compressed sensing compensated formulation with wavelet and total variation penalties. RESULTS: Susceptibility maps obtained with the spiral acquisition and the model-based reconstruction agree with the ones obtained with the spin-warp gradient echo acquisition. Using the 3D spiral acquisition, full brain susceptibility maps at the resolution of 1 mm isotropic are obtained in 23 s CONCLUSIONS: Image distortions and blurring due to magnetic field inhomogeneity are removed while maintaining tissue magnetic susceptibility information, resulting in QSM maps in much shorter acquisition time.

The Intersection of Physical Function, Cognitive Performance, Aging, and Multiple Sclerosis: A Cross-sectional Comparative Study.

OBJECTIVE: To examine the associations between physical function (walking speed and endurance and functional mobility) and cognitive function (information processing speed and verbal memory) in older adults with multiple sclerosis (MS) and healthy controls. BACKGROUND: Older adults with MS have worse physical and cognitive function than older adults without MS and young and middle-aged adults with MS. To date, little is known about the associations between, or coupling of, physical and cognitive function outcomes in older adults with MS. METHODS: We administered physical and cognitive function measures to 40 older adults with MS and 40 demographically matched healthy controls. Pearson product moment correlations were used to examine bivariate linear relationships in the overall sample and in the subsamples of (a) older adults with MS and (b) healthy controls. Linear regression analyses were used to examine the independent associations between demographic characteristics and physical and cognitive function variables in the two subsamples. RESULTS: In the overall sample, all physical function variables were significantly correlated with cognitive function, as measured by information processing speed, and these correlations were mainly due to the subsample of older adults with MS. The linear regression analyses further indicated that information processing speed and years of education consistently explained variance in all physical function variables, beyond the influence of demographic variables, in older adults with MS. CONCLUSIONS: Physical function and information processing speed are strongly correlated in older adults with MS. Future research should examine underlying neurobehavioral mechanisms associated with physical and cognitive function as well as behavioral strategies for jointly improving these functions in older adults with MS.