Functional and representational differences between bilateral inferior temporal numeral areas

The processing of numerals as visual objects is supported by an "Inferior Temporal Numeral Area" (ITNA) in the bilateral inferior temporal gyri (ITG). Extant findings suggest some degree of hemispheric asymmetry in how the bilateral ITNAs process numerals. Pollack and Price (2019) reported such a hemispheric asymmetry by which a region in the left ITG was sensitive to digits during a visual search for a digit among letters, and a homologous region in the right ITG that showed greater digit sensitivity in individuals with higher calculation skills. However, the ITG regions were localized with separate analyses without directly contrasting their digit sensitivities and relation to calculation skills. So, the extent of and reasons for these functional asymmetries remain unclear. Here we probe whether the functional and representational properties of the ITNAs are asymmetric by applying both univariate and multivariate region-of-interest analyses to Pollack and Price's (2019) data. Contrary to the implications of the original findings, digit sensitivity did not differ between ITNAs, and digit sensitivity in both left and right ITNAs was associated with calculation skills. Representational similarity analyses revealed that the overall representational geometries of digits in the ITNAs were also correlated, albeit weakly, but the representational contents of the ITNAs were largely inconclusive. Nonetheless, we found a right lateralization in engagement in alphanumeric categorization, and that the right ITNA showed greater discriminability between digits and letters. Greater right lateralization of digit sensitivity and digit discriminability in the left ITNA were also related to higher calculation skills. Our findings thus suggest that the ITNAs may not be functionally identical and should be directly contrasted in future work. Our study also highlights the importance of within-individual comparisons for understanding hemispheric asymmetries, and analyses of individual differences and multivariate features to uncover effects that would otherwise be obscured by averages.

Structural and functional connectivity of the inferior temporal numeral area

A growing body of evidence suggests that in adults, there is a spatially consistent "inferior temporal numeral area" (ITNA) in the occipitotemporal cortex that appears to preferentially process Arabic digits relative to non-numerical symbols and objects. However, very little is known about why the ITNA is spatially segregated from regions that process other orthographic stimuli such as letters, and why it is spatially consistent across individuals. In the present study, we used diffusion-weighted imaging and functional magnetic resonance imaging to contrast structural and functional connectivity between left and right hemisphere ITNAs and a left hemisphere letter-preferring region. We found that the left ITNA had stronger structural and functional connectivity than the letter region to inferior parietal regions involved in numerical magnitude representation and arithmetic. Between hemispheres, the left ITNA showed stronger structural connectivity with the left inferior frontal gyrus (Broca's area), while the right ITNA showed stronger structural connectivity to the ipsilateral inferior parietal cortex and stronger functional coupling with the bilateral IPS. Based on their relative connectivity, our results suggest that the left ITNA may be more readily involved in mapping digits to verbal number representations, while the right ITNA may support the mapping of digits to quantity representations.

MASiVar: Multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI

PURPOSE

Diffusion-weighted imaging allows investigators to identify structural, microstructural, and connectivity-based differences between subjects, but variability due to session and scanner biases is a challenge.

METHODS

To investigate DWI variability, we present MASiVar, a multisite data set consisting of 319 diffusion scans acquired at 3 T from b = 1000 to 3000 s/mm2 across 14 healthy adults, 83 healthy children (5 to 8 years), three sites, and four scanners as a publicly available, preprocessed, and de-identified data set. With the adult data, we demonstrate the capacity of MASiVar to simultaneously quantify the intrasession, intersession, interscanner, and intersubject variability of four common DWI processing approaches: (1) a tensor signal representation, (2) a multi-compartment neurite orientation dispersion and density model, (3) white-matter bundle segmentation, and (4) structural connectomics. Respectively, we evaluate region-wise fractional anisotropy, mean diffusivity, and principal eigenvector; region-wise CSF volume fraction, intracellular volume fraction, and orientation dispersion index; bundle-wise shape, volume, fractional anisotropy, and length; and whole connectome correlation and maximized modularity, global efficiency, and characteristic path length.

RESULTS

We plot the variability in these measures at each level and find that it consistently increases with intrasession to intersession to interscanner to intersubject effects across all processing approaches and that sometimes interscanner variability can approach intersubject variability.

CONCLUSIONS

This study demonstrates the potential of MASiVar to more globally investigate DWI variability across multiple levels and processing approaches simultaneously and suggests harmonization between scanners for multisite analyses should be considered before inference of group differences on subjects.

PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images

PURPOSE

Diffusion weighted MRI imaging (DWI) is often subject to low signal-to-noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document.

METHODS

The proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter-scan intensity normalization; susceptibility-, eddy current-, and motion-induced artifact correction; and slice-wise signal drop-out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness-of-fit and fractional anisotropy analyses.

RESULTS

Raw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility-, eddy current-, and motion-induced artifacts; imputed signal-lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file-type conversion errors and was shown to be effective on externally available datasets.

CONCLUSIONS

The proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI-focused software packages with intuitive QA.

Multi-shot acquisitions for stimulus-evoked spinal cord BOLD fMRI

PURPOSE

To demonstrate the feasibility of 3D multi-shot magnetic resonance imaging acquisitions for stimulus-evoked blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) in the human spinal cord in vivo.

METHODS

Two fMRI studies were performed at 3T. The first study was a hypercapnic gas challenge where data were acquired from healthy volunteers using a multi-shot 3D fast field echo (FFE) sequence as well as single-shot multi-slice echo-planar imaging (EPI). In the second study, another cohort of healthy volunteers performed an upper extremity motor task while fMRI data were acquired using a 3D multi-shot acquisition.

RESULTS

Both 2D-EPI and 3D-FFE were shown to be sensitive to BOLD signal changes in the cervical spinal cord, and had comparable contrast-to-noise ratios in gray matter. FFE exhibited much less signal drop-out and weaker geometric distortions compared to EPI. In the motor paradigm study, the mean number of active voxels was highest in the ventral gray matter horns ipsilateral to the side of the task and at the spinal level associated with innervation of finger extensors.

CONCLUSIONS

Highly multi-shot acquisition sequences such as 3D-FFE are well suited for stimulus-evoked spinal cord BOLD fMRI.

Network topology of symbolic and nonsymbolic number comparison

Studies of brain activity during number processing suggest symbolic and nonsymbolic numerical stimuli (e.g., Arabic digits and dot arrays) engage both shared and distinct neural mechanisms. However, the extent to which number format influences large-scale functional network organization is unknown. In this study, using 7 Tesla MRI, we adopted a network neuroscience approach to characterize the whole-brain functional architecture supporting symbolic and nonsymbolic number comparison in 33 adults. Results showed the degree of global modularity was similar for both formats. The symbolic format, however, elicited stronger community membership among auditory regions, whereas for nonsymbolic, stronger membership was observed within and between cingulo-opercular/salience network and basal ganglia communities. The right posterior inferior temporal gyrus, left intraparietal sulcus, and two regions in the right ventromedial occipital cortex demonstrated robust differences between formats in terms of their community membership, supporting prior findings that these areas are differentially engaged based on number format. Furthermore, a unified fronto-parietal/dorsal attention community in the nonsymbolic condition was fractionated into two components in the symbolic condition. Taken together, these results reveal a pattern of overlapping and distinct network architectures for symbolic and nonsymbolic number processing.

Shared Numerosity Representations Across Formats and Tasks Revealed with 7 Tesla fMRI: Decoding, Generalization, and Individual Differences in Behavior

Debate continues on whether encoding of symbolic number is grounded in nonsymbolic numerical magnitudes. Nevertheless, fluency of perceiving both number formats, and translating between them, predicts math skills across the life span. Therefore, this study asked if numbers share cortical activation patterns across formats and tasks, and whether neural response to number predicts math-related behaviors. We analyzed patterns of neural activation using 7 Tesla functional magnetic resonance imaging in a sample of 39 healthy adults. Discrimination was successful between numerosities 2, 4, 6, and 8 dots and generalized to activation patterns of the same numerosities represented as Arabic digits in the bilateral parietal lobes and left inferior frontal gyrus (IFG) (and vice versa). This indicates that numerosity-specific neural resources are shared between formats. Generalization was also successful across tasks where participants either identified or compared numerosities in bilateral parietal lobes and IFG. Individual differences in decoding did not relate to performance on a number comparison task completed outside of the scanner, but generalization between formats and across tasks negatively related to math achievement in the parietal lobes. Together, these findings suggest that individual differences in representational specificity within format and task contexts relate to mathematical expertise.

Multiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord

Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.

Glutamate-sensitive imaging and evaluation of cognitive impairment in multiple sclerosis

BACKGROUND

Cognitive impairment (CI) profoundly impacts quality of life for patients with multiple sclerosis (MS). Dysfunctional regulation of glutamate in gray matter (GM) has been implicated in the pathogenesis of MS by post-mortem pathological studies and in CI by in vivo magnetic resonance spectroscopy, yet GM pathology is subtle and difficult to detect using conventional T₁- and T₂-weighted magnetic resonance imaging (MRI). There is a need for high-resolution, clinically accessible imaging techniques that probe molecular changes in GM.

OBJECTIVE

To study cortical GM pathology related to CI in MS using glutamate-sensitive chemical exchange saturation transfer (GluCEST) MRI at 7.0 Tesla (7T).

METHODS

A total of 20 patients with relapsing-remitting MS and 20 healthy controls underwent cognitive testing, anatomical imaging, and GluCEST imaging. Glutamate-sensitive image contrast was quantified for cortical GM, compared between cohorts, and correlated with clinical measures of CI.

RESULTS AND CONCLUSION

Glutamate-sensitive contrast was significantly increased in the prefrontal cortex of MS patients with accumulated disability (p < 0.05). In addition, glutamate-sensitive contrast in the prefrontal cortex was significantly correlated with symbol digit modality test (r_S = -0.814) and choice reaction time (r_S = 0.772) scores in patients (p < 0.05), suggesting that GluCEST MRI may have utility as a marker for GM pathology and CI.

Spinal cord grey matter segmentation challenge

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.

Chemical exchange saturation transfer of the cervical spinal cord at 7 T

High-magnetic-field (7 T) chemical exchange saturation transfer (CEST) MRI provides information on the tissue biochemical environment. Multiple sclerosis (MS) affects the entire central nervous system, including the spinal cord. Optimal CEST saturation parameters found via simulation were implemented for CEST MRI in 10 healthy controls and 10 patients with MS, and the results were examined using traditional asymmetry analysis and a Lorentzian fitting method. In addition, T1 - and T2 *-weighted images were acquired for lesion localization and the transmitted B1 (+) field was evaluated to guide imaging parameters. Distinct spectral features for all tissue types studied were found both up- and downfield from the water resonance. The z spectra in healthy subjects had the expected z spectral shape with CEST effects apparent from 2.0 to 4.5 ppm. The z spectra from patients with MS demonstrated deviations from this expected normal shape, indicating this method's sensitivity to known pathology as well as to tissues appearing normal on conventional MRI. Examination of the calculated CESTasym revealed increased asymmetry around the amide proton resonance (Δω = 3.5 ppm), but it was apparent that this measure is complicated by detail in the CEST spectrum upfield from water, which is expected to result from the nuclear Overhauser effect. The z spectra upfield (negative ppm range) were also distinct between healthy and diseased tissue, and could not be ignored, particularly when considering the conventional asymmetry analysis used to quantify the CEST effect. For all frequencies greater than +1 ppm, the Lorentzian differences (and z spectra) for lesions and normal-appearing white matter were distinct from those for healthy white matter. The increased frequency separation and signal-to-noise ratio, in concert with prolonged T1 at 7 T, resulted in signal enhancements necessary to detect subtle tissue changes not possible at lower field strengths. This study presents CEST imaging metrics that may be sensitive to the extensive and temporally varying biochemical neuropathology of MS in the spinal cord. Copyright © 2016 John Wiley & Sons, Ltd.

Abdomen and spinal cord segmentation with augmented active shape models

Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC.

Increased MRI volumetric correlation contralateral to seizure focus in temporal lobe epilepsy

Quantification of volumetric correlation may be sensitive to disease alterations undetected by standard voxel based morphometry (VBM) such as subtle, synchronous alterations in regional volumes, and may provide complementary evidence of the structural impact of temporal lobe epilepsy (TLE) on the brain. The purpose of this study was to quantify differences of regional volumetric correlation in right (RTLE) and left (LTLE) TLE patients compared to healthy controls. A T1 weighted 3T MRI was acquired (1mm(3)) in 44 drug resistant unilateral TLE patients (n=26 RTLE, n=18 LTLE) and 44 individually age and gender matched healthy controls. Images were processed using a standard VBM framework and volumetric correlation was calculated across subjects in 90 regions and compared between patients and controls. Results were summarized across hemispheres and region groups. There was increased correlation involving the contralateral homologues of the seizure foci/network in the limbic, subcortical and temporal regions in both RTLE and LTLE. Outside these regions, results implied widespread correlated alterations across several contralateral lobes in LTLE, with more focal changes in RTLE. These findings complement previous volumetric studies in TLE describing more ipsilateral atrophy, by revealing subtle coordinated volumetric changes to identify a more widespread effect of TLE across the brain.

Thalamic Functional Connectivity in Mild Traumatic Brain Injury: Longitudinal Associations With Patient-Reported Outcomes and Neuropsychological Tests

OBJECTIVES

(1) To examine differences in patient-reported outcomes, neuropsychological tests, and thalamic functional connectivity (FC) between patients with mild traumatic brain injury (mTBI) and individuals without mTBI and (2) to determine longitudinal associations between changes in these measures.

DESIGN

Prospective observational case-control study.

SETTING

Academic medical center.

PARTICIPANTS

A sample (N=24) of 13 patients with mTBI (mean age, 39.3±14.0y; 4 women [31%]) and 11 age- and sex-matched controls without mTBI (mean age, 37.6±13.3y; 4 women [36%]).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Resting state FC (3T magnetic resonance imaging scanner) was examined between the thalamus and the default mode network, dorsal attention network, and frontoparietal control network. Patient-reported outcomes included pain (Brief Pain Inventory), depressive symptoms (Patient Health Questionnaire-9), posttraumatic stress disorder ([PTSD] Checklist - Civilian Version), and postconcussive symptoms (Rivermead Post-Concussion Symptoms Questionnaire). Neuropsychological tests included the Delis-Kaplan Executive Function System Tower test, Trails B, and Hotel Task. Assessments occurred at 6 weeks and 4 months after hospitalization in patients with mTBI and at a single visit for controls.

RESULTS

Student t tests found increased pain, depressive symptoms, PTSD symptoms, and postconcussive symptoms; decreased performance on Trails B; increased FC between the thalamus and the default mode network; and decreased FC between the thalamus and the dorsal attention network and between the thalamus and the frontoparietal control network in patients with mTBI as compared with controls. The Spearman correlation coefficient indicated that increased FC between the thalamus and the dorsal attention network from baseline to 4 months was associated with decreased pain and postconcussive symptoms (corrected P<.05).

CONCLUSIONS

Findings suggest that alterations in thalamic FC occur after mTBI, and improvements in pain and postconcussive symptoms are correlated with normalization of thalamic FC over time.

Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment

The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has developed a database built on XNAT housing over a quarter of a million scans. The database provides framework for (1) rapid prototyping, (2) large scale batch processing of images and (3) scalable project management. The system uses the web-based interfaces of XNAT and REDCap to allow for graphical interaction. A python middleware layer, the Distributed Automation for XNAT (DAX) package, distributes computation across the Vanderbilt Advanced Computing Center for Research and Education high performance computing center. All software are made available in open source for use in combining portable batch scripting (PBS) grids and XNAT servers.

Increasing structural atrophy and functional isolation of the temporal lobe with duration of disease in temporal lobe epilepsy

BACKGROUND

Due to pharmacoresistant seizures and the underutilization of surgical treatments, a large number of temporal lobe epilepsy (TLE) patients experience seizures for years or decades. The goal of this study was to generate a predictive model of duration of disease with the least number of parameters possible in order to identify and quantify the significant volumetric and functional indicators of TLE progression.

METHODS

Two cohorts of subjects including 12 left TLE, 21 right TLE and 20 healthy controls (duration = 0) were imaged on a 3T MRI scanner using high resolution T1-weighted structural MRI and 20 min of resting functional MRI scanning. Multivariate linear regression methods were used to compute a predictive model of duration of disease using 49 predictors including functional connectivity and gray matter volumes computed from these images.

RESULTS

No model developed from the full set of data accurately predicted the duration of disease across the entire range from 3 to 50 years. We then performed the regression on 35 subjects with durations of disease in the range 10 to 35 years. The resulting predictive model showed that longer durations were associated with reductions in functional connectivity from the ipsilateral temporal lobe to the contralateral temporal lobe, precuneus and mid cingulate, and with decreases in volume of the ipsilateral hippocampus and pallidum.

CONCLUSIONS

Functional and volumetric parameters accurately predicted duration of disease in TLE. The findings suggest that TLE is associated with a gradual functional isolation and significant progressive structural atrophy of the ipsilateral temporal lobe over years of duration in the range of 10-35 years. Furthermore, these changes can also be detected in the contralateral hemisphere in these patients, but to a lesser degree.