ECCENTRIC: a fast and unrestrained approach for high-resolution in vivo metabolic imaging at ultra-high field MR.

A novel method for fast and high-resolution metabolic imaging, called ECcentric Circle ENcoding TRajectorIes for Compressed sensing (ECCENTRIC), has been developed and implemented at 7 Tesla MRI. ECCENTRIC is a non-Cartesian spatial-spectral encoding method optimized to accelerate magnetic resonance spectroscopic imaging (MRSI) with high signal-to-noise at ultra-high field. The approach provides flexible and random (k,t) sampling without temporal interleaving to improve spatial response function and spectral quality. ECCENTRIC needs low gradient amplitudes and slew-rates that reduces electrical, mechanical and thermal stress of the scanner hardware, and is robust to timing imperfection and eddy-current delays. Combined with a model-based low-rank reconstruction, this approach enables simultaneous imaging of up to 14 metabolites over the whole-brain at 2-3mm isotropic resolution in 4-10 minutes. In healthy volunteers ECCENTRIC demonstrated unprecedented spatial mapping of fine structural details of human brain neurochemistry. This innovative tool introduces a novel approach to neuroscience, providing new insights into the exploration of brain activity and physiology.

Dynamics of hepatic steatosis resolution and changes in gut microbiome with weight loss in nonalcoholic fatty liver disease.

BACKGROUND: Weight loss is recommended as the primary treatment for nonalcoholic fatty liver disease (NAFLD). However, the magnitude and velocity of hepatic steatosis resolution with weight loss is unclear, making it difficult to counsel patients seeking weight loss for treatment of NAFLD. The aim of this study was to determine the rate of hepatic steatosis improvement and stool microbiome changes associated with rapid diet-induced weight loss in NAFLD. METHODS: Fourteen NAFLD patients (mean ± standard deviation, body mass index [BMI] 36.4 ± 4 kg/m2) enrolled in a 12-week meal replacement program underwent frequent measurement of Fibroscan-controlled attenuation parameter (CAP). Magnetic resonance imaging (MRI-Dixon method) for hepatic fat quantitation and stool microbiome analysis (16S rRNA gene sequencing) were completed in 11 subjects at baseline and Week 12. RESULTS: At Week 12, mean (95% confidence interval) weight loss was -13.4 (-15.2, -11.5)% and CAP score -26.6 (-35.6, -17.6)% (both Ps < 0.001). CAP scores changed at a rate of -4.9 dB/m/kg (-30.1 dB/m per unit BMI) in Weeks 1-4 and -0.6 dB/m/kg (-2.4 dB/m per unit BMI) in Weeks 8-12. MRI-determined hepatic fat fraction decreased by -74.1% (p < 0.001) at a rate of -0.51%/kg (-3.19% per unit BMI), with complete steatosis resolution in 90% patients. BMI change was associated with decreased stool microbial diversity (coefficient = 0.17; Shannon Index), increased abundance of Prevotella_9 (Bacteroidetes; coefficient = 0.96) and decreased abundance of Phascolarctobacterium (Firmicutes; coefficient = -0.42) (both Ps < 0.05). CONCLUSIONS: Diet-induced intensive weight loss is associated with rapid improvement and complete resolution of hepatic steatosis and decreased stool microbial diversity. These findings highlight the dynamic nature of hepatic fat and may help clinicians to develop evidence-based treatment goals for patients with NAFLD and obesity who undertake weight loss interventions. Further research is warranted to understand the effects of intensive weight loss and gut microbiome changes on long-term NAFLD resolution.

Fast, regional three-dimensional hybrid (1D-Hadamard 2D-rosette) proton MR spectroscopic imaging in the human temporal lobes.

1 H-MRSI is commonly performed with gradient phase encoding, due to its simplicity and minimal radio frequency (RF) heating (specific absorption rate). Its two well-known main problems-(i) "voxel bleed" due to the intrinsic point-spread function, and (ii) chemical shift displacement error (CSDE) when slice-selective RF pulses are used, which worsens with increasing volume of interest (VOI) size-have long become accepted as unavoidable. Both problems can be mitigated with Hadamard multislice RF encoding. This is demonstrated and quantified with numerical simulations, in a multislice phantom and in five healthy young adult volunteers at 3 T, targeting a 2-cm thick temporal lobe VOI through the bilateral hippocampus. This frequently targeted region (e.g. in epilepsy and Alzheimer's disease) is subject to strong, 1-2 ppm.cm-1 regional B0, susceptibility gradients that can dramatically reduce the signal-to-noise ratio (SNR) and water suppression effectiveness. The chemical shift imaging (CSI) sequence used a 3-ms Shinnar-Le Roux (SLR) 90° RF pulse, acquiring eight steps in the slice direction. The Hadamard sequence acquired two overlapping slices using the same SLR 90° pulses, under twofold stronger gradients that proportionally halved the CSDE. Both sequences used 2D 20 × 20 rosette spectroscopic imaging (RSI) for in-plane spatial localization and both used RF and gradient performance characteristics that are easily met by all modern MRI instruments. The results show that Hadamard spectroscopic imaging (HSI) suffered dramatically less signal bleed within the VOI compared with CSI (<1% vs. approximately 26% in simulations; and 5%-8% vs. >50%) in a phantom specifically designed to test these effects. The voxels' SNR per unit volume per unit time was also 40% higher for HSI. In a group of five healthy volunteers, we show that HSI with in-plane 2D-RSI facilitates fast, 3D multivoxel encoding at submilliliter spatial resolution, over the bilateral human hippocampus, in under 10 min, with negligible CSDE, spectral and spatial contamination and more than 6% improved SNR per unit time per unit volume.

Decreased functional connectivity in the fronto-parietal network in children with mood disorders compared to children with dyslexia during rest: An fMRI study.

Background: The DSM-5 separates the diagnostic criteria for mood and behavioral disorders. Both types of disorders share neurocognitive deficits of executive function and reading difficulties in childhood. Children with dyslexia also have executive function deficits, revealing a role of executive function circuitry in reading. The aim of the current study is to determine whether there is a significant relationship of functional connectivity within the fronto-parietal and cingulo-opercular cognitive control networks to reading measures for children with mood disorders, behavioral disorders, dyslexia, and healthy controls (HC). Method: Behavioral reading measures of phonological awareness, decoding, and orthography were collected. Resting state fMRI data were collected, preprocessed, and then analyzed for functional connectivity. Differences in the reading measures were tested for significance among the groups. Global efficiency (GE) measures were also tested for correlation with reading measures in 40 children with various disorders and 17 HCs. Results: Significant differences were found between the four groups on all reading measures. Relative to HCs and children with mood disorders or behavior disorders, children with dyslexia as a primary diagnosis scored significantly lower on all three reading measures. Children with mood disorders scored significantly lower than controls on a test of phonological awareness. Phonological awareness deficits correlated with reduced resting state functional connectivity MRI (rsfcMRI) in the cingulo-opercular network for children with dyslexia. A significant difference was also found in fronto-parietal global efficiency in children with mood disorders relative to the other three groups. We also found a significant difference in cingulo-opercular global efficiency in children with mood disorders relative to the Dyslexia and Control groups. However, none of these differences correlate significantly with reading measures. Conclusions/significance: Reading difficulties involve abnormalities in different cognitive control networks in children with dyslexia compared to children with mood disorders. Findings of the current study suggest increased functional connectivity of one cognitive control network may compensate for reduced functional connectivity in the other network in children with mood disorders. These findings provide guidance to clinical professionals for design of interventions tailored for children suffering from reading difficulties originating from different pathologies.

Fast 3D rosette spectroscopic imaging of neocortical abnormalities at 3 T: Assessment of spectral quality.

PURPOSE: To use a fast 3D rosette spectroscopic imaging acquisition to quantitatively evaluate how spectral quality influences detection of the endogenous variation of gray and white matter metabolite differences in controls, and demonstrate how rosette spectroscopic imaging can detect metabolic dysfunction in patients with neocortical abnormalities. METHODS: Data were acquired on a 3T MR scanner and 32-channel head coil, with rosette spectroscopic imaging covering a 4-cm slab of fronto-parietal-temporal lobes. The influence of acquisition parameters and filtering on spectral quality and sensitivity to tissue composition was assessed by LCModel analysis, the Cramer-Rao lower bound, and the standard errors from regression analyses. The optimized protocol was used to generate normative white and gray matter regressions and evaluate three patients with neocortical abnormalities. RESULTS: As a measure of the sensitivity to detect abnormalities, the standard errors of regression for Cr/NAA and Ch/NAA were significantly correlated with the Cramer-Rao lower bound values (R = 0.89 and 0.92, respectively, both with P < 0.001). The rosette acquisition with a duration of 9.6 min, produces a mean Cramer-Rao lower bound (%) over the entire slab of 4.6 ± 2.6 and 5.8 ± 2.3 for NAA and Cr, respectively. This enables a Cr/NAA standard error of 0.08 (i.e., detection sensitivity of 25% for a 50/50 mixed gray and white matter voxel). In healthy controls, the regression of Cr/NAA versus fraction gray matter in the cingulate differs from frontal and parietal regions. CONCLUSIONS: Fast rosette spectroscopic imaging acquisitions with regression analyses are able to identify metabolic differences across 4-cm slabs of the brain centrally and over the cortical periphery with high efficiency, generating results that are consistent with clinical findings. Magn Reson Med 79:2470-2480, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Assessing the Structural Footprint of Minimally Invasive Brain Cannulation on Cerebral White Matter: A Cadaveric Model.

BACKGROUND: All brain surgery requires some degree of iatrogenic trauma to healthy tissue. Minimally invasive approaches to brain tumors offer the potential of decreasing this trauma compared with conventional approaches. However, there are no validated radiologic models to examine axonal damage after minimally invasive entry into the brain. OBJECTIVE: To present a cadaveric model of brain cannulation using fractional anisotropy measurements obtained from diffusion tensor magnetic resonance imaging (MRI). Two different methods of access are compared. METHODS: Freshly harvested unfixed cadaveric brains were cannulated using both direct and indirect (i.e., dilation followed by cannulation) methods. Specimens were subjected to 68-direction diffusion tensor imaging scans and proton-density imaging. Fractional anisotropy (FA) data from a region of interest surrounding the entry zone was extracted from scans using imaging software and analyzed. RESULTS: FA values were significantly higher following indirect cannulation (less invasive method) than they were following direct cannulation. FA values for undisturbed brain were significantly higher than in either of the cannulated groups, suggesting an inverse relationship between FA values and brain injury. CONCLUSION: Axonal damage following brain cannulation can potentially be evaluated by FA analysis in a cadaveric model. These data may lead to an MRI-based model of iatrogenic brain injury following tumor surgery. Future studies will focus on histologic analysis and clinical validation in live tissues.

Brain Regional Blood Flow and Working Memory Performance Predict Change in Blood Pressure Over 2 Years.

Hypertension is a presumptive risk factor for premature cognitive decline. However, lowering blood pressure (BP) does not uniformly reverse cognitive decline, suggesting that high BP per se may not cause cognitive decline. We hypothesized that essential hypertension has initial effects on the brain that, over time, manifest as cognitive dysfunction in conjunction with both brain vascular abnormalities and systemic BP elevation. Accordingly, we tested whether neuropsychological function and brain blood flow responses to cognitive challenges among prehypertensive individuals would predict subsequent progression of BP. Midlife adults (n=154; mean age, 49; 45% men) with prehypertensive BP underwent neuropsychological testing and assessment of regional cerebral blood flow (rCBF) response to cognitive challenges. Neuropsychological performance measures were derived for verbal and logical memory (memory), executive function, working memory, mental efficiency, and attention. A pseudo-continuous arterial spin labeling magnetic resonance imaging sequence compared rCBF responses with control and active phases of cognitive challenges. Brain areas previously associated with BP were grouped into composites for frontoparietal, frontostriatal, and insular-subcortical rCBF areas. Multiple regression models tested whether BP after 2 years was predicted by initial BP, initial neuropsychological scores, and initial rCBF responses to cognitive challenge. The neuropsychological composite of working memory (standardized beta, -0.276; se=0.116; P=0.02) and the frontostriatal rCBF response to cognitive challenge (standardized beta, 0.234; se=0.108; P=0.03) significantly predicted follow-up BP. Initial BP failed to significantly predict subsequent cognitive performance or rCBF. Changes in brain function may precede or co-occur with progression of BP toward hypertensive levels in midlife.

Reading related white matter structures in adolescents are influenced more by dysregulation of emotion than behavior.

Mood disorders and behavioral are broad psychiatric diagnostic categories that have different symptoms and neurobiological mechanisms, but share some neurocognitive similarities, one of which is an elevated risk for reading deficit. Our aim was to determine the influence of mood versus behavioral dysregulation on reading ability and neural correlates supporting these skills in youth, using diffusion tensor imaging in 11- to 17-year-old children and youths with mood disorders or behavioral disorders and age-matched healthy controls. The three groups differed only in phonological processing and passage comprehension. Youth with mood disorders scored higher on the phonological test but had lower comprehension scores than children with behavioral disorders and controls; control participants scored the highest. Correlations between fractional anisotropy and phonological processing in the left Arcuate Fasciculus showed a significant difference between groups and were strongest in behavioral disorders, intermediate in mood disorders, and lowest in controls. Correlations between these measures in the left Inferior Longitudinal Fasciculus were significantly greater than in controls for mood but not for behavioral disorders. Youth with mood disorders share a deficit in the executive-limbic pathway (Arcuate Fasciculus) with behavioral-disordered youth, suggesting reduced capacity for engaging frontal regions for phonological processing or passage comprehension tasks and increased reliance on the ventral tract (e.g., the Inferior Longitudinal Fasciculus). The low passage comprehension scores in mood disorder may result from engaging the left hemisphere. Neural pathways for reading differ mainly in executive-limbic circuitry. This new insight may aid clinicians in providing appropriate intervention for each disorder.

Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth.

Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS) study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5). Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18) from those with lower (n = 34) trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7). Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03) youth with different (higher vs lower) trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This approach has potential to identify patterns of neural markers of future clinical course.

Longitudinal relationships among activity in attention redirection neural circuitry and symptom severity in youth.

BACKGROUND: Changes in neural circuitry function may be associated with longitudinal changes in psychiatric symptom severity. Identification of these relationships may aid in elucidating the neural basis of psychiatric symptom evolution over time. We aimed to distinguish these relationships using data from the Longitudinal Assessment of Manic Symptoms (LAMS) cohort. METHODS: Forty-one youth completed two study visits (mean=21.3 months). Elastic-net regression (Multiple response Gaussian family) identified emotional regulation neural circuitry that changed in association with changes in depression, mania, anxiety, affect lability, and positive mood and energy dysregulation, accounting for clinical and demographic variables. RESULTS: Non-zero coefficients between change in the above symptom measures and change in activity over the inter-scan interval were identified in right amygdala and left ventrolateral prefrontal cortex. Differing patterns of neural activity change were associated with changes in each of the above symptoms over time. Specifically, from Scan1 to Scan2, worsening affective lability and depression severity were associated with increased right amygdala and left ventrolateral prefrontal cortical activity. Worsening anxiety and positive mood and energy dysregulation were associated with decreased right amygdala and increased left ventrolateral prefrontal cortical activity. Worsening mania was associated with increased right amygdala and decreased left ventrolateral prefrontal cortical activity. These changes in neural activity between scans accounted for 13.6% of the variance; that is 25% of the total explained variance (39.6%) in these measures. CONCLUSIONS: Distinct neural mechanisms underlie changes in different mood and anxiety symptoms overtime.

Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study.

Neurodevelopment continues through adolescence, with notable maturation of white matter tracts comprising regional fiber systems progressing at different rates. To identify factors that could contribute to regional differences in white matter microstructure development, large samples of youth spanning adolescence to young adulthood are essential to parse these factors. Recruitment of adequate samples generally relies on multi-site consortia but comes with the challenge of merging data acquired on different platforms. In the current study, diffusion tensor imaging (DTI) data were acquired on GE and Siemens systems through the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a multi-site study designed to track the trajectories of regional brain development during a time of high risk for initiating alcohol consumption. This cross-sectional analysis reports baseline Tract-Based Spatial Statistic (TBSS) of regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1), and radial diffusivity (LT) from the five consortium sites on 671 adolescents who met no/low alcohol or drug consumption criteria and 132 adolescents with a history of exceeding consumption criteria. Harmonization of DTI metrics across manufacturers entailed the use of human-phantom data, acquired multiple times on each of three non-NCANDA participants at each site's MR system, to determine a manufacturer-specific correction factor. Application of the correction factor derived from human phantom data measured on MR systems from different manufacturers reduced the standard deviation of the DTI metrics for FA by almost a half, enabling harmonization of data that would have otherwise carried systematic error. Permutation testing supported the hypothesis of higher FA and lower diffusivity measures in older adolescents and indicated that, overall, the FA, MD, and L1 of the boys were higher than those of the girls, suggesting continued microstructural development notable in the boys. The contribution of demographic and clinical differences to DTI metrics was assessed with General Additive Models (GAM) testing for age, sex, and ethnicity differences in regional skeleton mean values. The results supported the primary study hypothesis that FA skeleton mean values in the no/low-drinking group were highest at different ages. When differences in intracranial volume were covaried, FA skeleton mean reached a maximum at younger ages in girls than boys and varied in magnitude with ethnicity. Our results, however, did not support the hypothesis that youth who exceeded exposure criteria would have lower FA or higher diffusivity measures than the no/low-drinking group; detecting the effects of excessive alcohol consumption during adolescence on DTI metrics may require longitudinal study.

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

INTRODUCTION: High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. METHODS: A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. RESULTS: Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas. CONCLUSIONS: The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

In vivo brain rosette spectroscopic imaging (RSI) with LASER excitation, constant gradient strength readout, and automated LCModel quantification for all voxels.

PURPOSE: To optimize the Rosette trajectories for high-sensitivity in vivo brain spectroscopic imaging and reduced gradient demands. METHODS: Using LASER localization, a rosette based sampling scheme for in vivo brain spectroscopic imaging data on a 3 Tesla (T) system is described. The two-dimensional (2D) and 3D rosette spectroscopic imaging (RSI) data were acquired using 20 × 20 in-plane resolution (8 × 8 mm(2) ), and 1 (2D) -18 mm (1.1 cc) or 12 (3D) -8 mm partitions (0.5 cc voxels). The performance of the RSI acquisition was compared with a conventional spectroscopic imaging (SI) sequence using LASER localization and 2D or 3D elliptical phase encoding (ePE). Quantification of the entire RSI data set was performed using an LCModel based pipeline. RESULTS: The RSI acquisitions took 32 s for the 2D scan, and as short as 5 min for the 3D 20 × 20 × 12 scan, using a maximum gradient strength Gmax=5.8 mT/m and slew-rate Smax=45 mT/m/ms. The Bland-Altman agreement between RSI and ePE CSI, characterized by the 95% confidence interval for their difference (RSI-ePE), is within 13% of the mean (RSI+ePE)/2. Compared with the 3D ePE at the same nominal resolution, the effective RSI voxel size was three times smaller while the measured signal-to-noise ratio sensitivity, after normalization for differences in effective size, was 43% greater. CONCLUSION: 3D LASER-RSI is a fast, high-sensitivity spectroscopic imaging sequence, which can acquire medium-to-high resolution SI data in clinically acceptable scan times (5-10 min), with reduced stress on the gradient system. Magn Reson Med 76:380-390, 2016. © 2015 Wiley Periodicals, Inc.

White matter structure in youth with behavioral and emotional dysregulation disorders: a probabilistic tractographic study.

IMPORTANCE: Psychiatric disorders in youth characterized by behavioral and emotional dysregulation are often comorbid and difficult to distinguish. An alternative approach to conceptualizing these disorders is to move toward a diagnostic system based on underlying pathophysiologic processes that may cut across conventionally defined diagnoses. Neuroimaging techniques have potentials for the identification of these processes. OBJECTIVE: To determine whether diffusion imaging, a neuroimaging technique examining white matter (WM) structure, can identify neural correlates of emotional dysregulation in a sample of youth with different psychiatric disorders characterized by behavioral and emotional dysregulation. DESIGN, SETTING, AND PARTICIPANTS: Using global probabilistic tractography, we examined relationships between WM structure in key tracts in emotional regulation circuitry (ie, cingulum, uncinate fasciculus, and forceps minor) and (1) broader diagnostic categories of behavioral and emotional dysregulation disorders (DDs) and (2) symptom dimensions cutting across conventional diagnoses in 120 youth with behavioral and/or emotional DDs, a referred sample of the Longitudinal Assessment of Manic Symptoms (LAM) study. Thirty age- and sex-matched typically developing youth (control participants) were included. Multivariate multiple regression models were used. The study was conducted from July 1, 2010, to February 28, 2014. MAIN OUTCOMES AND MEASURES: Fractional anisotropy as well as axial and radial diffusivity were estimated and imported into a well-established statistical package. We hypothesized that (1) youth with emotional DDs and those with both behavioral and emotional DDs would show significantly lower fractional anisotropy compared with youth with behavioral DDs in these WM tracts and (2) that there would be significant inverse relationships between dimensional measures of affective symptom severity and fractional anisotropy in these tracts across all participants. RESULTS: Multivariate multiple regression analyses revealed decreased fractional anisotropy and decreased axial diffusivity within the uncinate fasciculus in youth with emotional DDs vs those with behavioral DDs, those with both DDs, and the controls (F6,160 = 2.4; P = .032; all pairwise comparisons, P < .002). In the same model, greater severity of manic symptoms was positively associated with higher fractional anisotropy across all affected youth (F3,85 = 2.8; P = .044). CONCLUSIONS AND RELEVANCE: These findings suggest that abnormal uncinate fasciculus and cingulum WM structure may underlie emotional, but not behavioral, dysregulation in pediatric psychiatric disorders and that a different neural mechanism may exist for comorbid emotional and behavioral DDs.

White matter diffusivity and microarchitecture among schizophrenia subjects and first-degree relatives.

BACKGROUND: Impairments in structural and functional connections are demonstrated in schizophrenia. Certain disconnectional patterns may be biomarkers of elevated risk for schizophrenia. Convergent examination of multiple diffusion parameters and cognitive performance better illustrates pathophysiological significance of such disconnectional patterns. METHODS: Diffusion Tensor Imaging data on 39 early-course schizophrenia subjects, 21 adolescent/young adult first-degree relatives (FDR) of schizophrenia subjects and 29 healthy controls (HC) were examined for threshold-free clusters of fractional anisotropy (FA) and radial diffusivity (RD) differences correcting for multiple comparisons. Regression models examined the variance contributed by anisotropy differences, age and sex. Group-wise differences on sustained attention, verbal memory and executive functions were examined and correlated with diffusivity measures controlling for age and sex. RESULTS: Schizophrenia subjects showed significantly decreased FA and increased RD in the forceps minor and superior longitudinal fasciculus (SLF) compared to HC. FDR showed decreased forceps minor FA compared to HC, and decreased SLF RD compared to HC and schizophrenia subjects. Quantitative RD differences were 2-3 fold higher compared to FA. Besides, forceps minor RD was inversely correlated with sustained attention in schizophrenia. CONCLUSIONS: Schizophrenia and FDR subjects show different patterns of white matter diffusivity compared to HC. While forceps minor changes may be a disease marker, SLF changes may be risk markers. In addition, RD may be a more robust risk marker than FA.

Decreased amygdala-insula resting state connectivity in behaviorally and emotionally dysregulated youth.

The Research Domain Criteria (RDoC) adopts a dimensional approach for examining pathophysiological processes underlying categorically defined psychiatric diagnoses. We used this framework to examine relationships among symptom dimensions, diagnostic categories, and resting state connectivity in behaviorally and emotionally dysregulated youth selected from the Longitudinal Assessment of Manic Symptoms study (n=42) and healthy control youth (n=18). Region of interest analyses examined relationships among resting state connectivity, symptom dimensions (behavioral and emotional dysregulation measured with the Parent General Behavior Inventory-10 Item Mania Scale [PGBI-10M]; dimensional severity measures of mania, depression, anxiety), and diagnostic categories (Bipolar Spectrum Disorders, Attention Deficit Hyperactivity Disorder, Anxiety Disorders, and Disruptive Behavior Disorders). After adjusting for demographic variables, two dimensional measures showed significant inverse relationships with resting state connectivity, regardless of diagnosis: 1) PGBI-10M with amygdala-left posterior insula/bilateral putamen; and 2) depressive symptoms with amygdala-right posterior insula connectivity. Diagnostic categories showed no significant relationships with resting state connectivity. Resting state connectivity between amygdala and posterior insula decreased with increasing severity of behavioral and emotional dysregulation and depression; this suggests an intrinsic functional uncoupling of key neural regions supporting emotion processing and regulation. These findings support the RDoC dimensional approach for characterizing pathophysiologic processes that cut across different psychiatric disorders.

Iterative projection onto convex sets for quantitative susceptibility mapping.

PURPOSE: Quantitative susceptibility map (QSM) reconstruction is ill posed due to the zero values on the "magic angle cone" that make the maps prone to streaking artifacts. We propose projection onto convex sets (POCS) in the method of steepest descent (SD) for QSM reconstruction. METHODS: Two convex projections, an object-support projection in the image domain and a projection in k-space were used. QSM reconstruction using the proposed SD-POCS method was compared with SD and POCS alone as well as with truncated k-space division (TKD) for numerically simulated and 7 Tesla (T) human brain phase data. RESULTS: The QSM reconstruction error from noise-free simulated phase data using SD-POCS is at least two orders of magnitude lower than using SD, POCS, or TKD and has reduced streaking artifacts. Using the l1 -TV reconstructed susceptibility as a gold standard for 7T in vivo imaging, SD-POCS showed better image quality comparing to SD, POCS, or TKD from visual inspection. CONCLUSION: POCS is an alternative method for regularization that can be used in an iterative minimization method such as SD for QSM reconstruction.

Clinical cell therapy imaging using a perfluorocarbon tracer and fluorine-19 MRI.

PURPOSE: Cellular therapeutics are emerging as a treatment option for a host of serious human diseases. To accelerate clinical translation, noninvasive imaging of cell grafts in clinical trials can potentially be used to assess the initial delivery and behavior of cells. METHODS: The use of a perfluorocarbon (PFC) tracer agent for clinical fluorine-19 ((19) F) MRI cell detection is described. This technology was used to detect immunotherapeutic dendritic cells (DCs) delivered to colorectal adenocarcinoma patients. Autologous DC vaccines were labeled with a PFC MRI agent ex vivo. Patients received DCs intradermally, and (19) F spin-density-weighted MRI at 3 Tesla (T) was used to observe cells. RESULTS: Spin-density-weighted (19) F images at the injection site displayed DCs as background-free "hot-spot" images. (19) F images were acquired in clinically relevant scan times (<10 min). Apparent DC numbers could be quantified in two patients from the (19) F hot-spots and were observed to decrease by ∼50% at injection site by 24 h. From 3T phantom studies, the sensitivity limit for DC detection is estimated to be on the order of ∼10(5) cells/voxel in this study. CONCLUSION: These results help to establish a clinically applicable means to track a broad range of cell types used in cell therapy.

Glutamate and GABA contributions to medial prefrontal cortical activity to emotion: implications for mood disorders.

The dorsomedial prefrontal cortex (MdPFC) and anterior cingulate cortices (ACC) play a critical role in implicit emotion regulation; however the understanding of the specific neurotransmitters that mediate such role is lacking. In this study, we examined relationships between MdPFC concentrations of two neurotransmitters, glutamate and γ-amino butyric acid (GABA), and BOLD activity in ACC during performance of an implicit facial emotion-processing task. Twenty healthy volunteers, aged 20-35 years, were scanned while performing an implicit facial emotion-processing task, whereby presented facial expressions changed from neutral to one of the four emotions: happy, anger, fear, or sad. Glutamate concentrations were measured before and after the emotion-processing task in right MdPFC using magnetic resonance spectroscopy (MRS). GABA concentrations were measured in bilateral MdPFC after the emotion-processing task. Multiple regression models were run to determine the relative contribution of glutamate and GABA concentration, age, and gender to BOLD signal in ACC to each of the four emotions. Multiple regression analyses revealed a significant negative correlation between MdPFC GABA concentration and BOLD signal in subgenual ACC (p<0.05, corrected) to sad versus shape contrast. For the anger versus shape contrast, there was a significant negative correlation between age and BOLD signal in pregenual ACC (p<0.05, corrected) and a positive correlation between MdPFC glutamate concentration (pre-task) and BOLD signal in pregenual ACC (p<0.05, corrected). Our findings are the first to provide insight into relationships between MdPFC neurotransmitter concentrations and ACC BOLD signal, and could further understanding of molecular mechanisms underlying emotion processing in healthy and mood-disordered individuals.

Parsing dimensional vs diagnostic category-related patterns of reward circuitry function in behaviorally and emotionally dysregulated youth in the Longitudinal Assessment of Manic Symptoms study.

IMPORTANCE: Pediatric disorders characterized by behavioral and emotional dysregulation pose diagnostic and treatment challenges because of high comorbidity, suggesting that they may be better conceptualized dimensionally rather than categorically. Identifying neuroimaging measures associated with behavioral and emotional dysregulation in youth may inform understanding of underlying dimensional vs disorder-specific pathophysiologic features. OBJECTIVE: To identify, in a large cohort of behaviorally and emotionally dysregulated youth, neuroimaging measures that (1) are associated with behavioral and emotional dysregulation pathologic dimensions (behavioral and emotional dysregulation measured with the Parent General Behavior Inventory 10-Item Mania Scale [PGBI-10M], mania, depression, and anxiety) or (2) differentiate diagnostic categories (bipolar spectrum disorders, attention-deficit/hyperactivity disorder, anxiety, and disruptive behavior disorders). DESIGN, SETTING, AND PARTICIPANTS: A multisite neuroimaging study was conducted from February 1, 2011, to April 15, 2012, at 3 academic medical centers: University Hospitals Case Medical Center, Cincinnati Children's Hospital Medical Center, and University of Pittsburgh Medical Center. Participants included a referred sample of behaviorally and emotionally dysregulated youth from the Longitudinal Assessment of Manic Symptoms (LAMS) study (n = 85) and healthy youth (n = 20). MAIN OUTCOMES AND MEASURES: Region-of-interest analyses examined relationships among prefrontal-ventral striatal reward circuitry during a reward paradigm (win, loss, and control conditions), symptom dimensions, and diagnostic categories. RESULTS: Regardless of diagnosis, higher PGBI-10M scores were associated with greater left middle prefrontal cortical activity (r = 0.28) and anxiety with greater right dorsal anterior cingulate cortical (r = 0.27) activity to win. The 20 highest (t = 2.75) and 20 lowest (t = 2.42) PGBI-10M-scoring youth showed significantly greater left middle prefrontal cortical activity to win compared with 20 healthy youth. Disruptive behavior disorders were associated with lower left ventrolateral prefrontal cortex activity to win (t = 2.68) (all P < .05, corrected). CONCLUSIONS AND RELEVANCE: Greater PGBI-10M-related left middle prefrontal cortical activity and anxiety-related right dorsal anterior cingulate cortical activity to win may reflect heightened reward sensitivity and greater attention to reward in behaviorally and emotionally dysregulated youth regardless of diagnosis. Reduced left ventrolateral prefrontal cortex activity to win may reflect reward insensitivity in youth with disruptive behavior disorders. Despite a distinct reward-related neurophysiologic feature in disruptive behavior disorders, findings generally support a dimensional approach to studying neural mechanisms in behaviorally and emotionally dysregulated youth.