Analysis of the effects of noise, DWI sampling, and value of assumed parameters in diffusion MRI models.

PURPOSE: This study was a systematic evaluation across different and prominent diffusion MRI models to better understand the ways in which scalar metrics are influenced by experimental factors, including experimental design (diffusion-weighted imaging [DWI] sampling) and noise. METHODS: Four diffusion MRI models-diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator MRI (MAP-MRI), and neurite orientation dispersion and density imaging (NODDI)-were evaluated by comparing maps and histogram values of the scalar metrics generated using DWI datasets obtained in fixed mouse brain with different noise levels and DWI sampling complexity. Additionally, models were fit with different input parameters or constraints to examine the consequences of model fitting procedures. RESULTS: Experimental factors affected all models and metrics to varying degrees. Model complexity influenced sensitivity to DWI sampling and noise, especially for metrics reporting non-Gaussian information. DKI metrics were highly susceptible to noise and experimental design. The influence of fixed parameter selection for the NODDI model was found to be considerable, as was the impact of initial tensor fitting in the MAP-MRI model. CONCLUSION: Across DTI, DKI, MAP-MRI, and NODDI, a wide range of dependence on experimental factors was observed that elucidate principles and practical implications for advanced diffusion MRI. Magn Reson Med 78:1767-1780, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Prefrontal GABA Levels Measured With Magnetic Resonance Spectroscopy in Patients With Psychosis and Unaffected Siblings.

OBJECTIVE: The authors sought to compare GABA levels in treated and untreated patients with psychosis with levels in their unaffected siblings and healthy control subjects, and to assess the effects of antipsychotic medications on GABA levels. METHOD: GABA+ levels (i.e., including signal from unrelated proteins or macromolecules) referenced to creatine or water were studied with J-edited proton spectroscopy in the dorsal anterior cingulate cortex of 289 individuals: 184 healthy control subjects, 83 treated patients with psychosis, 25 untreated patients, 31 unaffected siblings, and 17 patients studied both while off all medications and while on a single antipsychotic. RESULTS: GABA+ levels in the dorsal anterior cingulate did not differ between untreated patients and healthy controls. For treated patients, levels were modestly lower for GABA+/creatine but did not differ for GABA+/water compared with healthy controls. For both GABA+ measures, unaffected siblings had significantly lower levels compared with controls. GABA+/creatine showed a modest degree of familiality (intraclass correlation=0.36). Antipsychotic dosage was negatively correlated with GABA+ levels, but the on-off medication studies indicated no difference in GABA+ levels on antipsychotics compared with off antipsychotics. CONCLUSIONS: GABA+/creatine in the dorsal anterior cingulate may constitute an intermediate phenotype with low effect size for psychosis, but GABA+/water measures do not fully support this conclusion. Low GABA+ levels in unaffected siblings could suggest a genetic association, but the failure to find consistent evidence of this phenotype in the patients themselves weakens genetic inference on risk for psychosis. Replication in independent samples of siblings is warranted to confirm the potential genetic risk association.

Clinical feasibility of using mean apparent propagator (MAP) MRI to characterize brain tissue microstructure.

Diffusion tensor imaging (DTI) is the most widely used method for characterizing noninvasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its ability to describe intricate tissue microanatomy. Consequently, the biological interpretation of microstructural parameters, such as fractional anisotropy or mean diffusivity, is often equivocal. We evaluate the clinical feasibility of assessing brain tissue microstructure with mean apparent propagator (MAP) MRI, a powerful analytical framework that efficiently measures the probability density function (PDF) of spin displacements and quantifies useful metrics of this PDF indicative of diffusion in complex microstructure (e.g., restrictions, multiple compartments). Rotation invariant and scalar parameters computed from the MAP show consistent variation across neuroanatomical brain regions and increased ability to differentiate tissues with distinct structural and architectural features compared with DTI-derived parameters. The return-to-origin probability (RTOP) appears to reflect cellularity and restrictions better than MD, while the non-Gaussianity (NG) measures diffusion heterogeneity by comprehensively quantifying the deviation between the spin displacement PDF and its Gaussian approximation. Both RTOP and NG can be decomposed in the local anatomical frame for reference determined by the orientation of the diffusion tensor and reveal additional information complementary to DTI. The propagator anisotropy (PA) shows high tissue contrast even in deep brain nuclei and cortical gray matter and is more uniform in white matter than the FA, which drops significantly in regions containing crossing fibers. Orientational profiles of the propagator computed analytically from the MAP MRI series coefficients allow separation of different fiber populations in regions of crossing white matter pathways, which in turn improves our ability to perform whole-brain fiber tractography. Reconstructions from subsampled data sets suggest that MAP MRI parameters can be computed from a relatively small number of DWIs acquired with high b-value and good signal-to-noise ratio in clinically achievable scan durations of less than 10min. The neuroanatomical consistency across healthy subjects and reproducibility in test-retest experiments of MAP MRI microstructural parameters further substantiate the robustness and clinical feasibility of this technique. The MAP MRI metrics could potentially provide more sensitive clinical biomarkers with increased pathophysiological specificity compared to microstructural measures derived using conventional diffusion MRI techniques.

Effects of the BDNF Val66Met polymorphism on white matter microstructure in healthy adults.

The BDNF Val(66)Met polymorphism, a possible risk variant for mental disorders, is a potent modulator of neural plasticity in humans and has been linked to deficits in gray matter structure, function, and cognition. The impact of the variant on brain white matter structure, however, is controversial and remains poorly understood. Here, we used diffusion tensor imaging to examine the effects of BDNF Val(66)Met genotype on white matter microstructure in a sample of 85 healthy Caucasian adults. We demonstrate decreases of fractional anisotropy and widespread increases in radial diffusivity in Val/Val homozygotes compared with Met-allele carriers, particularly in prefrontal and occipital pathways. These data provide an independent confirmation of prior imaging genetics work, are consistent with complex effects of the BDNF Val(66)Met polymorphism on human brain structure, and may serve to generate hypotheses about variation in white matter microstructure in mental disorders associated with this variant.

Investigation of anatomical thalamo-cortical connectivity and FMRI activation in schizophrenia.

The purpose of this study was to examine measures of anatomical connectivity between the thalamus and lateral prefrontal cortex (LPFC) in schizophrenia and to assess their functional implications. We measured thalamocortical connectivity with diffusion tensor imaging (DTI) and probabilistic tractography in 15 patients with schizophrenia and 22 age- and sex-matched controls. The relationship between thalamocortical connectivity and prefrontal cortical blood-oxygenation-level-dependent (BOLD) functional activity as well as behavioral performance during working memory was examined in a subsample of 9 patients and 18 controls. Compared with controls, schizophrenia patients showed reduced total connectivity of the thalamus to only one of six cortical regions, the LPFC. The size of the thalamic region with at least 25% of model fibers reaching the LPFC was also reduced in patients compared with controls. The total thalamocortical connectivity to the LPFC predicted working memory task performance and also correlated with LPFC BOLD activation. Notably, the correlation with BOLD activation was accentuated in patients as compared with controls in the ventral LPFC. These results suggest that thalamocortical connectivity to the LPFC is altered in schizophrenia with functional consequences on working memory processing in LPFC.

Genetic association of ErbB4 and human cortical GABA levels in vivo.

NRG1-ErbB4 signaling controls inhibitory circuit development in the mammalian cortex through ErbB4-dependent regulation of GABAergic interneuron connectivity. Common genetic variation in ErbB4 (rs7598440) has been associated with ErbB4 messenger RNA levels in the human cortex and risk for schizophrenia. Recent work demonstrates that Erbb4 is expressed exclusively on inhibitory interneurons, where its presence on parvalbumin-positive cells mediates the effects of NRG1 on inhibitory circuit formation in the cortex. We therefore hypothesized that genetic variation in ErbB4 at rs7598440 would impact indices of GABA concentration in the human cortex. We tested this hypothesis in 116 healthy volunteers by measuring GABA and GLX (glutamate + glutamine) with proton magnetic resonance spectroscopy in the dorsal anterior cingulate gyrus. ErbB4 rs7598440 genotype significantly predicted cortical GABA concentration (p = 0.014), but not GLX (p = 0.51), with A allele carriers having higher GABA as predicted by the allelic impact on ErbB4 expression. These data establish an association of ErbB4 and GABA in human brain and have implications for understanding the pathogenesis of schizophrenia and other psychiatric disorders.

Reproducibility of prefrontal γ-aminobutyric acid measurements with J-edited spectroscopy.

γ-Aminobutyric acid (GABA) is the chief inhibitory neurotransmitter of the human brain, and GABA-ergic dysfunction has been implicated in a variety of neuropsychiatric disorders. Recent MRS techniques have allowed the quantification of GABA concentrations in vivo, and could therefore provide biologically relevant information. Few reports have formally characterized the reproducibility of these techniques, and differences in field strength, acquisition and processing parameters may result in large differences in measured GABA values. Here, we used a J-edited, single-voxel spectroscopy method of measurement of GABA + macromolecules (GABA + ) in the anterior cingulate cortex (ACC) and right frontal white matter (rFWM) at 3 T. We measured the coefficient of variation within subjects (CVw) and intra-class correlation coefficients on two repeated scans obtained from 10 healthy volunteers with processing procedures developed in-house for the quantification of GABA + and other major metabolites. In addition, by segmenting the spectroscopic voxel into cerebrospinal fluid, gray matter and white matter, and employing a linear regression technique to extrapolate metabolite values to pure gray and white matter, we determined metabolite differences between gray and white matter in ACC and rFWM. CVw values for GABA + /creatine, GABA + /H(2) O, GABA + , creatine, partially co-edited glutamate + glutamine (Glx)/creatine, partially co-edited Glx and N-acetylaspartic acid (NAA)/creatine were all below 12% in both ACC and rFWM. After extrapolation to pure gray and pure white matter, CVw values for all metabolites were below 16%. We found metabolite ratios between gray and white matter for GABA + /creatine, GABA + , creatine, partially co-edited Glx and NAA/creatine to be 0.88 ± 0.21 (standard deviation), 1.52 ± 0.32, 1.77 ± 0.4, 2.69 ± 0.74 and 0.70 ± 0.05, respectively. This study validates a reproducible method for the quantification of brain metabolites, and provides information on gray/white matter differences that may be important in the interpretation of results in clinical populations.

Genetic modulation of GABA levels in the anterior cingulate cortex by GAD1 and COMT.

Gamma-aminobutyric acid (GABA)-ergic transmission is critical for normal cortical function and is likely abnormal in a variety of neuropsychiatric disorders. We tested the in vivo effects of variations in two genes implicated in GABA function on GABA concentrations in prefrontal cortex of living subjects: glutamic acid decarboxylase 1 (GAD1), which encodes GAD67, and catechol-o-methyltransferase (COMT), which regulates synaptic dopamine in the cortex. We studied six single nucleotide polymorphisms (SNPs) in GAD1 previously associated with risk for schizophrenia or cognitive dysfunction and the val158met polymorphism in COMT in 116 healthy volunteers using proton magnetic resonance spectroscopy. Two of the GAD1 SNPs (rs1978340 (p=0.005) and rs769390 (p=0.004)) showed effects on GABA levels as did COMT val158met (p=0.04). We then tested three SNPs in GAD1 (rs1978340, rs11542313, and rs769390) for interaction with COMT val158met based on previous clinical results. In this model, rs11542313 and COMT val158met showed significant main effects (p=0.001 and 0.003, respectively) and a trend toward a significant interaction (p=0.05). Interestingly, GAD1 risk alleles for schizophrenia were associated with higher GABA/Cre, and Val-Val homozygotes had high GABA/Cre levels when on a GAD1 risk genotype background (N=6). These results support the importance of genetic variation in GAD1 and COMT in regulating prefrontal cortical GABA function. The directionality of the effects, however, is inconsistent with earlier evidence of decreased GABA activity in schizophrenia.

Impact of the brain-derived neurotrophic factor Val66Met polymorphism on levels of hippocampal N-acetyl-aspartate assessed by magnetic resonance spectroscopic imaging at 3 Tesla.

BACKGROUND: This study was conducted to corroborate prior evidence of an effect of the brain-derived neurotrophic factor (BDNF) valine (val) to methionine (met) amino acid substitution at codon 66 (val66met) polymorphism on measures of N-acetyl-aspartate (NAA) containing compounds in healthy subjects. METHODS: The NAA to creatine (Cre) ratio (NAA/Cre), NAA to choline (Cho) ratio (NAA/Cho), and Cho to Cre ratio (Cho/Cre) were measured in the left and right hippocampi, left and right dorsolateral prefrontal cortices, occipital lobe, anterior cingulate, and white matter of the centrum semiovale of 69 carefully screened healthy volunteers utilizing proton magnetic resonance spectroscopic imaging (MRSI) at 3 Tesla (T). RESULTS: Val/met subjects exhibited significantly reduced levels of left hippocampal NAA/Cre and NAA/Cho compared with val/val subjects. This effect was independent of age, IQ, number of voxels, hippocampal volume, or gray matter content in the voxels of interest. Analysis of other brain regions showed no effect of BDNF genotype on NAA measures. CONCLUSIONS: We confirmed the association between the met-BDNF variant and reduced levels of hippocampal NAA found with a similar technique at 1.5T. The consonance of our results with prior findings adds to the evidence that the BDNF val/met genotype affects hippocampal biology with implications for a variety of neuropsychiatric disorders.

Detection and characterization of neurotoxicity in cancer patients using proton MR spectroscopy.

OBJECTIVE: The study objective was to detect abnormalities and identify relationships between brain metabolic ratios determined by proton magnetic resonance spectroscopic imaging ((1)H-MRSI) and neuropsychological (NP) function in cancer patients at risk for neurotoxicity. METHODS: Thirty-two patients received (1)H-MRSI using a multi-slice, multi-voxel technique on a 1.5T magnet. Cho/NAA, NAA/Cr, and Cho/Cr ratios were identified in seven pre-determined sites without tumor involvement. A battery of age-appropriate NP tests was administered within 7 days of imaging. Relationships were examined between test scores and metabolite ratios. CONCLUSIONS: This study identifies relationships between brain metabolite ratios and cognitive functioning in cancer patients. (1)H-MRSI may be useful in early detection of neurotoxic effects, but prospective longitudinal studies in a homogeneous population are recommended to determine the prognostic value.

Three-dimensional mapping of lingual myoarchitecture by diffusion tensor MRI.

This study was performed to assess the feasibility of investigating the complex lingual myoarchitecture through segmentation of muscles from diffusion tensor imaging (DTI) data. The primary eigenvectors were found to be adequate for delineating the superior and inferior longitudinalis, genioglossus, and hyoglossus. The tertiary eigenvector orientations effectively revealed the homogeneous and systematic change of muscle orientation in the tongue core. In the longitudinalis near the tongue tip, the secondary eigenvectors were oriented in the radial direction. Lingual muscles were segmented using two methods: modified directional correlation (DC) and tensor coherence (TC) methods. The DC method, based on one eigenvector, was found to be inadequate for lingual muscle segmentation, whereas the TC method, based on the tensor shape and orientation, was used successfully to segment most lingual muscles. The segmentation result was used to report the diffusion tensor properties of individual lingual muscles. Also found was a continuous change in skewness of the intrinsic tongue core from negative in the anterior region to positive in the posterior region. DTI and the proposed segmentation method provide an adequate means of imaging and visualizing the complex, compartmentalized musculature of the tongue. The potential for in vivo research and clinical applications is demonstrated.

Regional distribution of measurement error in diffusion tensor imaging.

The characterization of measurement error is critical in assessing the significance of diffusion tensor imaging (DTI) findings in longitudinal and cohort studies of psychiatric disorders. We studied 20 healthy volunteers, each one scanned twice (average interval between scans of 51 +/- 46.8 days) with a single shot echo planar DTI technique. Intersession variability for fractional anisotropy (FA) and Trace (D) was represented as absolute variation (standard deviation within subjects: SDw), percent coefficient of variation (CV) and intra-class correlation coefficient (ICC). The values from the two sessions were compared for statistical significance with repeated measures analysis of variance or a non-parametric equivalent of a paired t-test. The results showed good reproducibility for both FA and Trace (CVs below 10% and ICCs at or above 0.70 in most regions of interest) and evidence of systematic global changes in Trace between scans. The regional distribution of reproducibility described here has implications for the interpretation of regional findings and for rigorous pre-processing. The regional distribution of reproducibility measures was different for SDw, CV and ICC. Each one of these measures reveals complementary information that needs to be taken into consideration when performing statistical operations on groups of DT images.

Dependence on diffusion time of apparent diffusion tensor of ex vivo calf tongue and heart.

The time dependence of the apparent diffusion tensor of ex vivo calf heart and tongue was measured for diffusion times (tau(d)) between 32 and 810 ms. The results showed evidence of restricted diffusion in the muscle tissues of both organs. In regions where the myofibers are parallel, the largest eigenvalue (lambda(1)) of the diffusion tensor remained the same for all diffusion times measured, while the other eigenvalues (lambda(2), lambda(3)) decreased by 29-36% between tau(d) = 32 ms and tau(d) = 400 ms. In regions where the fibers cross, the lambda(1) also changed, decreasing by 17% between tau(d) = 32 ms and tau(d) = 400 ms. The restricting compartment size and volume fraction were effectively estimated by fitting the time courses of the eigenvalues to a model consisting of a nonrestricted compartment and a cylindrically restricted compartment. To our knowledge, this study is the first demonstrating diffusion time dependence of measured water diffusion tensor in muscular tissue. With improvement in scanning technology, future studies may permit noninvasive, in vivo detection of changes in muscle myoarchitecture due to disease, treatment, and exercise.

Estimating intensity variance due to noise in registered images: applications to diffusion tensor MRI.

Image registration techniques which require image interpolation are widely used in neuroimaging research. We show that signal variance in interpolated images differs significantly from the signal variance of the original images in native space. We describe a simple approach to compute the signal variance in registered images based on the signal variance and covariance of the original images, the spatial transformations computed by the registration procedure, and the interpolation or approximation kernel chosen. The method is general and could handle various sources of signal variability, such as thermal noise and physiological noise, provided that their effects can be assessed in the original images. Our approach is applied to diffusion tensor (DT) MRI data, assuming only thermal noise as the source of variability in the data. We show that incorrect noise variance estimates in registered diffusion-weighted images can affect DT parameters, as well as indices of goodness of fit such as chi-square maps. In addition to DT-MRI, we believe that this methodology would be useful any time parameter extraction methods are applied to registered or interpolated data, such as in relaxometry and functional MRI studies.