Dependence of brain DTI maps of fractional anisotropy and mean diffusivity on the number of diffusion weighting directions

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

Associations between maternal pre-pregnancy BMI and infant striatal mean diffusivity

BACKGROUND

It is well-established that parental obesity is a strong risk factor for offspring obesity. Further, a converging body of evidence now suggests that maternal weight profiles may affect the developing offspring's brain in a manner that confers future obesity risk. Here, we investigated how pre-pregnancy maternal weight status influences the reward-related striatal areas of the offspring's brain during in utero development.

METHODS

We used diffusion tensor imaging to quantify the microstructure of the striatal brain regions of interest in neonates (N = 116 [66 males, 50 females], mean gestational weeks at birth [39.88], SD = 1.14; at scan [43.56], SD = 1.05). Linear regression was used to test the associations between maternal pre-pregnancy body mass index (BMI) and infant striatal mean diffusivity.

RESULTS

High maternal pre-pregnancy BMI was associated with higher mean MD values in the infant's left caudate nucleus. Results remained unchanged after the adjustment for covariates.

CONCLUSIONS

In utero exposure to maternal adiposity might have a growth-impairing impact on the mean diffusivity of the infant's left caudate nucleus. Considering the involvement of the caudate nucleus in regulating eating behavior and food-related reward processing later in life, this finding calls for further investigations to define the prognostic relevance of early-life caudate nucleus development and weight trajectories of the offspring.

Effect of number of diffusion encoding directions in neonatal diffusion tensor imaging using Tract-Based Spatial Statistical analysis

Diffusion tensor imaging (DTI) has been used to study the developing brain in early childhood, infants and in utero studies. In infants, number of used diffusion encoding directions has traditionally been smaller in earlier studies down to the minimum of 6 orthogonal directions. Whereas the more recent studies often involve more directions, number of used directions remain an issue when acquisition time is optimized without compromising on data quality and in retrospective studies. Variability in the number of used directions may introduce bias and uncertainties to the DTI scalar estimates that affect cross-sectional and longitudinal study of the brain. We analysed DTI images of 133 neonates, each data having 54 directions after quality control, to evaluate the effect of number of diffusion weighting directions from 6 to 54 with interval of 6 to the DTI scalars with Tract-Based Spatial Statistics (TBSS) analysis. The TBSS analysis was applied to DTI scalar maps, and the mean region of interest (ROI) values were extracted using JHU atlas. We found significant bias in ROI mean values when only 6 directions were used (positive in fractional anisotropy [FA] and negative in fractional anisotropy [MD], axial diffusivity [AD] and fractional anisotropy [RD]), while when using 24 directions and above, the difference to scalar values calculated from 54 direction DTI was negligible. In repeated measures voxel-wise analysis, notable differences to 54 direction DTI were observed with 6, 12 and 18 directions. DTI measurements from data with at least 24 directions may be used in comparisons with DTI measurements from data with higher numbers of directions.

The impact of loneliness and social adaptation on depressive symptoms: Behavioral and brain measures evidence from a brain health perspective

Introduction

Early detection of depression is a cost-effective way to prevent adverse outcomes on brain physiology, cognition, and health. Here we propose that loneliness and social adaptation are key factors that can anticipate depressive symptoms.

Methods

We analyzed data from two separate samples to evaluate the associations between loneliness, social adaptation, depressive symptoms, and their neural correlates.

Results

For both samples, hierarchical regression models on self-reported data showed that loneliness and social adaptation have negative and positive effects on depressive symptoms. Moreover, social adaptation reduces the impact of loneliness on depressive symptoms. Structural connectivity analysis showed that depressive symptoms, loneliness, and social adaptation share a common neural substrate. Furthermore, functional connectivity analysis demonstrated that only social adaptation was associated with connectivity in parietal areas.

Discussion

Altogether, our results suggest that loneliness is a strong risk factor for depressive symptoms while social adaptation acts as a buffer against the ill effects of loneliness. At the neuroanatomical level, loneliness and depression may affect the integrity of white matter structures known to be associated to emotion dysregulation and cognitive impairment. On the other hand, socio-adaptive processes may protect against the harmful effects of loneliness and depression. Structural and functional correlates of social adaptation could indicate a protective role through long and short-term effects, respectively. These findings may aid approaches to preserve brain health via social participation and adaptive social behavior.

A generalized deep learning network for fractional anisotropy reconstruction: Application to epilepsy and multiple sclerosis

Fractional anisotropy (FA) is a quantitative map sensitive to microstructural properties of tissues in vivo and it is extensively used to study the healthy and pathological brain. This map is classically calculated by model fitting (standard method) and requires many diffusion weighted (DW) images for data quality and unbiased readings, hence needing the acquisition time of several minutes. Here, we adapted the U-net architecture to be generalized and to obtain good quality FA from DW volumes acquired in 1 minute. Our network requires 10 input DW volumes (hence fast acquisition), is robust to the direction of application of the diffusion gradients (hence generalized), and preserves/improves map quality (hence good quality maps). We trained the network on the human connectome project (HCP) data using the standard model-fitting method on the entire set of DW directions to extract FA (ground truth). We addressed the generalization problem, i.e., we trained the network to be applicable, without retraining, to clinical datasets acquired on different scanners with different DW imaging protocols. The network was applied to two different clinical datasets to assess FA quality and sensitivity to pathology in temporal lobe epilepsy and multiple sclerosis, respectively. For HCP data, when compared to the ground truth FA, the FA obtained from 10 DW volumes using the network was significantly better (p <10-4) than the FA obtained using the standard pipeline. For the clinical datasets, the network FA retained the same microstructural characteristics as the FA calculated with all DW volumes using the standard method. At the subject level, the comparison between white matter (WM) ground truth FA values and network FA showed the same distribution; at the group level, statistical differences of WM values detected in the clinical datasets with the ground truth FA were reproduced when using values from the network FA, i.e., the network retained sensitivity to pathology. In conclusion, the proposed network provides a clinically available method to obtain FA from a generic set of 10 DW volumes acquirable in 1 minute, augmenting data quality compared to direct model fitting, reducing the possibility of bias from sub-sampled data, and retaining FA pathological sensitivity, which is very attractive for clinical applications.

Diffusion Tensor Imaging of the Dentate Nucleus After Repeated Administration of Gadobutrol in Children

This study aimed to investigate possible signal changes in the dentate nucleus (DN) on diffusion tensor imaging (DTI) after administration of gadobutrol in a pediatric cohort. Total of 50 pediatric patients (mean age: 6.2 ± 4.3 years) with normal renal function exposed exclusively to the macrocyclic GBCA (mcGBCA) gadobutrol and 50 age- and sex-matched control patients with nonpathological neuroimaging findings (and no GBCA administration). Mean diffusivity (MD) and fractional anisotropy (FA) values were determined in the DN. A paired t test was performed to compare FA, MD values, and DN-to-middle cerebral peduncle (MCP) T1WI SI ratios between children exposed to gadobutrol and controls. Pearson correlation analysis was conducted to determine any correlation between FA and MD values as well as T1WI SI ratios and confounding parameters. The mean FA values of DN was significantly lower in children with mcGBCA than in the control group (p < 0.001; non-GBCA group, 0.299 ± 0.03; mcGBCA group, 0.254 ± 0.05), but no significant difference of the T1WI SI ratio was noted between the mcGBCA group (0.946 ± 0.06) and the control group (0.963 ± 0.05; p = 0.336). There was also a significant MD value difference between mcGBCA group and control group (p < 0.001; non-GBCA group, 0.152 ± 0.02 × 10^-3 mm²/s; mcGBCA group, 0.173 ± 0.03 × 10^-3 mm²/s). A significant correlation was identified between FA/MD values and the number of mcGBCA administration (FA; correlation coefficient =  - 0.355, p = 0.011 and MD; correlation coefficient = 0.334, p = 0.018). The administration of the gadobutrol was associated with higher MD and lower FA values in DN suggesting a difference in cerebellar tissue integrity between children exposed to mcGBCAs and control group.

Effect of number of diffusion encoding directions in Diffusion Metrics of 5-year-olds using Tract-Based Spatial Statistical analysis

Methodological aspects and effects of different imaging parameters on DTI (diffusion tensor imaging) results and their reproducibility have been recently studied comprehensively in adult populations. Although MR imaging of children's brains has become common, less interest has been focussed on researching whether adult‐based optimised parameters and pre‐processing protocols can be reliably applied to paediatric populations. Furthermore, DTI scalar values of preschool aged children are rarely reported. We gathered a DTI dataset from 5‐year‐old children (N = 49) to study the effect of the number of diffusion‐encoding directions on the reliability of resultant scalar values with TBSS (tract‐based spatial statistics) method. Additionally, the potential effect of within‐scan head motion on DTI scalars was evaluated. Reducing the number of diffusion‐encoding directions deteriorated both the accuracy and the precision of all DTI scalar values. To obtain reliable scalar values, a minimum of 18 directions for TBSS was required. For TBSS fractional anisotropy values, the intraclass correlation coefficient with two‐way random‐effects model (ICC[2,1]) for the subsets of 6 to 66 directions ranged between 0.136 [95%CI 0.0767;0.227] and 0.639 [0.542;0.740], whereas the corresponding values for subsets of 18 to 66 directions were 0.868 [0.815;0.913] and 0.995 [0.993;0.997]. Following the exclusion of motion‐corrupted volumes, minor residual motion did not associate with the scalar values. A minimum of 18 diffusion directions is recommended to result in reliable DTI scalar results with TBSS. We suggest gathering extra directions in paediatric DTI to enable exclusion of volumes with motion artefacts and simultaneously preserve the overall data quality.

Sensitivity of Diffusion MRI to White Matter Pathology: Influence of Diffusion Protocol, Magnetic Field Strength, and Processing Pipeline in Systemic Lupus Erythematosus

There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.

Same Brain, Different Look?-The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters

In clinical diagnostics and longitudinal studies, the reproducibility of MRI assessments is of high importance in order to detect pathological changes, but developments in MRI hard- and software often outrun extended periods of data acquisition and analysis. This could potentially introduce artefactual changes or mask pathological alterations. However, if and how changes of MRI hardware, scanning protocols or preprocessing software affect complex neuroimaging outcomes from, e.g., diffusion weighted imaging (DWI) remains largely understudied. We therefore compared DWI outcomes and artefact severity of 121 healthy participants (age range 19–54 years) who underwent two matched DWI protocols (Siemens product and Center for Magnetic Resonance Research sequence) at two sites (Siemens 3T Magnetom Verio and Skyra^fit). After different preprocessing steps, fractional anisotropy (FA) and mean diffusivity (MD) maps, obtained by tensor fitting, were processed with tract-based spatial statistics (TBSS). Inter-scanner and inter-sequence variability of skeletonised FA values reached up to 5% and differed largely in magnitude and direction across the brain. Skeletonised MD values differed up to 14% between scanners. We here demonstrate that DTI outcome measures strongly depend on imaging site and software, and that these biases vary between brain regions. These regionally inhomogeneous biases may exceed and considerably confound physiological effects such as ageing, highlighting the need to harmonise data acquisition and analysis. Future studies thus need to implement novel strategies to augment neuroimaging data reliability and replicability.

Meta-analysis of the normal diffusion tensor imaging values of the median nerve and how they change in carpal tunnel syndrome

Carpal tunnel syndrome (CTS) leads to distortion of axonal architecture, demyelination and fibrosis within the median nerve. Diffusion tensor imaging (DTI) characterises tissue microstructure and generates reproducible proxy measures of nerve 'health' which are sensitive to myelination, axon diameter, fiber density and organisation. This meta-analysis summarises the normal DTI values of the median nerve, and how they change in CTS. This systematic review included studies reporting DTI of the median nerve at the level of the wrist in adults. The primary outcome was to determine the normal fractional anisotropy (FA) and mean diffusivity (MD) of the median nerve. Secondarily, we show how the FA and MD differ between asymptomatic adults and patients with CTS, and how these differences are independent of the acquisition methods. We included 32 studies of 2643 wrists, belonging to 1575 asymptomatic adults and 1068 patients with CTS. The normal FA was 0.58 (95% CI 0.56, 0.59) and the normal MD was 1.138 × 10^-3 mm²/s (95% CI 1.101, 1.174). Patients with CTS had a significantly lower FA than controls (mean difference 0.12 [95% CI 0.09, 0.16]). Similarly, the median nerve of patients with CTS had a significantly higher mean diffusivity (mean difference 0.16 × 10^-3 mm²/s [95% CI 0.05, 0.27]). The differences were independent of experimental factors. We provide summary estimates of the normal FA and MD of the median nerve in asymptomatic adults. Furthermore, we show that diffusion throughout the length of the median nerve becomes more isotropic in patients with CTS.

Diffusion tensor imaging in cubital tunnel syndrome

Cubital tunnel syndrome (CuTS) is the 2nd most common compressive neuropathy. To improve both diagnosis and the selection of patients for surgery, there is a pressing need to develop a reliable and objective test of ulnar nerve 'health'. Diffusion tensor imaging (DTI) characterises tissue microstructure and may identify differences in the normal ulnar from those affected by CuTS. The aim of this study was to compare the DTI metrics from the ulnar nerves of healthy (asymptomatic) adults and patients with CuTS awaiting surgery. DTI was acquired at 3.0 T using single-shot echo-planar imaging (55 axial slices, 3 mm thick, 1.5 mm2 in-plane) with 30 diffusion sensitising gradient directions, a b-value of 800 s/mm2 and 4 signal averages. The sequence was repeated with the phase-encoding direction reversed. Data were combined and corrected using the FMRIB Software Library (FSL) and reconstructed using generalized q-sampling imaging in DSI Studio. Throughout the length of the ulnar nerve, the fractional anisotropy (FA), quantitative anisotropy (QA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted, then compared using mixed-effects linear regression. Thirteen healthy controls (8 males, 5 females) and 8 patients with CuTS (6 males, 2 females) completed the study. Throughout the length of the ulnar nerve, diffusion was more isotropic in patients with CuTS. Overall, patients with CuTS had a 6% lower FA than controls, with the largest difference observed proximal to the cubital tunnel (mean difference 0.087 [95% CI 0.035, 0.141]). Patients with CuTS also had a higher RD than controls, with the largest disparity observed within the forearm (mean difference 0.252 × 10-4 mm2/s [95% CI 0.085 × 10-4, 0.419 × 10-4]). There were no significant differences between patients and controls in QA, MD or AD. Throughout the length of the ulnar nerve, the fractional anisotropy and radial diffusivity in patients with CuTS are different to healthy controls. These findings suggest that DTI may provide an objective assessment of the ulnar nerve and potentially, improve the management of CuTS.

Newborn white matter microstructure moderates the association between maternal postpartum depressive symptoms and infant negative reactivity

Maternal postpartum depression is a prominent risk factor for aberrant child socioemotional development, but there is little understanding about the neural phenotypes that underlie infant sensitivity to maternal depression. We examined whether newborn white matter fractional anisotropy (FA), a measure of white matter maturity, moderates the association between maternal postpartum depressive symptoms and infant negative reactivity at 6 months. Participants were 80 mother–infant dyads participating in a prospective population-based cohort, and included families whose newborns underwent a magnetic resonance/diffusion tensor imaging scan at 2–5 weeks of age and whose mothers reported their own depressive symptoms at 3 and 6 months postpartum and infant negative emotional reactivity at 6 months. The whole-brain FA moderated the association between maternal depressive symptoms and mother-reported infant negative reactivity at 6 months after adjusting for the covariates. Maternal depressive symptoms were positively related to infant negative reactivity among infants with high or average FA in the whole brain and in corpus callosum and cingulum, but not among those with low FA. The link between maternal depressive symptoms and infant negative reactivity was moderated by newborn FA. The variation in white matter microstructure might play a role in child susceptibility to parental distress.

Multiband diffusion tensor imaging for presurgical mapping of motor and language pathways in patients with brain tumors

BACKGROUND AND PURPOSE

Assessment of the essential white matter fibers of arcuate fasciculus and corticospinal tract (CST), required for preoperative planning in brain tumor patients, relies on the reliability of diffusion tensor imaging (DTI). The recent development of multiband DTI (mb-DTI) based on simultaneous multislice excitation could maintain the overall quality of tractography while not exceeding standard clinical care time. To address this potential, we performed quantitative analyses to evaluate tractography results of arcuate fasciculus and CST acquired by mb-DTI in brain tumor patients.

METHODS

We retrospectively analyzed 44 patients with brain lesions who underwent presurgical single-shot DTI (s-DTI) and mb-DTI. We measured DTI parameters: fractional anisotropy (FA) and mean diffusivity (MD [mm² s^-1 ]) in whole brain and tumor regions; and the tractography parameters: fiber FA, MD (mm² s^-1 ), volume (mm³ ), and length (mm) in the whole brain, arcuate fasciculus, and CST. Additionally, three neuroradiologists performed a blinded visual assessment comparing s-DTI with mb-DTI.

RESULTS

The mb-DTI showed higher mean FA and lower MD (r > .95, p < .002) in whole brain and tumor regions of interest; slightly higher fiber FA, volume, and length; and slightly lower fiber MD in whole brain, arcuate fasciculus, and CST than in s-DTI. These differences were significant for fiber FA in all tracts; length (mm) in arcuate fasciculus; and fiber MD (mm² s^-1 ) and volume (mm³ ) in all patients with tumor involved in the arcuate fasciculus, CST, and whole brain tracts (p = .001). Visual assessment demonstrated that both techniques produced visually similar tracts.

CONCLUSIONS

This study demonstrated the clinical potential and significant advantages of preoperative mb-DTI in brain tumor patients.

Learning Invariant Representations using Inverse Contrastive Loss

Learning invariant representations is a critical first step in a number of machine learning tasks. A common approach corresponds to the so-called information bottleneck principle in which an application dependent function of mutual information is carefully chosen and optimized. Unfortunately, in practice, these functions are not suitable for optimization purposes since these losses are agnostic of the metric structure of the parameters of the model. We introduce a class of losses for learning representations that are invariant to some extraneous variable of interest by inverting the class of contrastive losses, i.e., inverse contrastive loss (ICL). We show that if the extraneous variable is binary, then optimizing ICL is equivalent to optimizing a regularized MMD divergence. More generally, we also show that if we are provided a metric on the sample space, our formulation of ICL can be decomposed into a sum of convex functions of the given distance metric. Our experimental results indicate that models obtained by optimizing ICL achieve significantly better invariance to the extraneous variable for a fixed desired level of accuracy. In a variety of experimental settings, we show applicability of ICL for learning invariant representations for both continuous and discrete extraneous variables. The project page with code is available at https://github.com/adityakumarakash/ICL.

Fractional anisotropy thresholding for deterministic tractography of the roots of the brachial plexus

Diffusion tensor imaging (DTI) metrics, such as the fractional anisotropy (FA) and estimates of diffusivity are sensitive to the microstructure of peripheral nerves and may be displayed as tractograms. However, the ideal conditions for tractography of the roots of the brachial plexus are unclear, which represents the rationale for this study. Ten healthy adults were scanned using a Siemens Prisma (3T) and single-shot echo-planar imaging (b-value 0/1000 s/mm², 64 directions, 2.5 mm³ with 4 averages; repeated in opposing phase encoding directions). Susceptibility correction and tractography were performed in DSI Studio by two independent raters. The effect of FA thresholding at increments of 0.01 (from 0.04 to 0.10) were tested. The mean FA varied between subjects by 2% (95% CI 1%, 3%). FA thresholds of 0.04, 0.05 and 0.06 all propagated 96% of tracts representing the roots; thresholding at 0.07 yielded 4% fewer tracts (p = 0.2), 0.08 yielded 11% fewer tracts (p = 0.008), 0.09 yielded 15% fewer tracts (p = 0.001) and 0.1 yielded 20% fewer tracts (p < 0.001). There was < 0.1% inter-rater variability in the measured FA and 99% agreement for tractography (κ = 0.92, p < 0.001). The fractional anisotropy thresholds required to generate tractograms of the roots of the brachial plexus appears to be lower than those used in the brain. We provide estimates of the probability of generating true tracts for each spinal nerve root of the brachial plexus, at different fractional anisotropy thresholds.

Altered Dentate Gyrus Microstructure in Individuals at High Familial Risk for Depression Predicts Future Symptoms

BACKGROUND

Offspring of individuals with major depressive disorder (MDD) are at increased risk for developing MDD themselves. Altered hippocampal, and specifically dentate gyrus (DG), structure and function may be involved in depression development. However, hippocampal abnormalities could also be a consequence of the disease. For the first time, we tested whether abnormal DG micro- and macrostructure were present in offspring of individuals with MDD and whether these abnormalities predicted future symptomatology.

METHODS

We measured the mean diffusivity of gray matter, a measure of microstructure, via diffusion tensor imaging and volume of the DG via structural magnetic resonance imaging in 102 generation 2 and generation 3 offspring at high and low risk for depression, defined by the presence or absence, respectively, of moderate to severe MDD in generation 1. Prior, current, and future depressive symptoms were tested for association with hippocampal structure.

RESULTS

DG mean diffusivity was higher in individuals at high risk for depression, regardless of a lifetime history of MDD. While DG mean diffusivity was not associated with past or current depressive symptoms, higher mean diffusivity predicted higher symptom scores 8 years later. DG microstructure partially mediated the association between risk and future symptoms. DG volume was smaller in high-risk generation 2 but not in high-risk generation 3.

CONCLUSIONS

Together, these findings suggest that the DG has a role in the development of depression. Furthermore, DG microstructure, more than macrostructure, is a sensitive risk marker for depression and partially mediates future depressive symptoms.

Association of Cumulative Paternal Early Life Stress With White Matter Maturation in Newborns

IMPORTANCE

Early life stress (ELS) has been shown to affect brain development and health outcomes. Recent animal studies have linked paternal early stress exposures with next-generation outcomes. Epigenetic inheritance through the male germline has been suggested to be one of the mechanisms.

OBJECTIVES

To test whether paternal ELS, as measured using the Trauma and Distress Scale, is associated with neonate brain development.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included data from participants from the prospective 2-generation FinnBrain Birth Cohort, which was collected from 2011 to 2015. Pregnant women and the fathers were consecutively recruited at gestational week 12 from maternity clinics in Finland. Magnetic resonance imaging data were analyzed in 2019. Participants in this study were 72 families (infant, father, mother).

EXPOSURE

Paternal exposure to ELS.

MAIN OUTCOMES AND MEASURES

Fractional anisotropy (FA) values in the major white-matter tracts of the newborn brain.

RESULTS

A total of 72 trios (infant, mother, and father) were analyzed. At the time of delivery, the mean (SD) age was 31.0 (4.4) years for fathers and 30.3 (4.5) years for mothers. Forty-one infants (57%) were boys; mean (SD) child age at inclusion was 26.9 (7.2) days from birth and 205 (8) days from estimated conception. Increasing levels of paternal ELS were associated with higher FA values in the newborn brain in the body of the corpus callosum, right superior corona radiata, and retrolenticular parts of the internal capsule. This association persisted after controlling for maternal ELS, maternal socioeconomic status (SES), maternal body mass index, maternal depressive symptoms during pregnancy, child sex, and child age from birth and gestation corrected age when imaged. In additional region-of-interest analyses, the association between FA values and paternal Trauma and Distress Scale sum scores remained statistically significant in the earliest maturing regions of the brain, eg, the genu of the corpus callosum (in the regression models, β = 0.00096; 95% CI, 0.00034-0.00158; P = .003) and the splenium (β = 0.00090; 95% CI, 0.00000-0.00180; P = .049).

CONCLUSIONS AND RELEVANCE

This cohort study found a statistically significant association between paternal ELS and offspring brain development. This finding may have far-reaching implications in pediatrics, as it suggests the possibility of a novel route of intergenerational inheritance of ELS on next-generation brain development.

Diffusion tensor imaging of the roots of the brachial plexus: a systematic review and meta-analysis of normative values

Purpose

Diffusion tensor magnetic resonance imaging (DTI) characterises tissue microstructure and provides proxy measures of myelination, axon diameter, fibre density and organisation. This may be valuable in the assessment of the roots of the brachial plexus in health and disease. Therefore, there is a need to define the normal DTI values.

Methods

The literature was systematically searched for studies of asymptomatic adults who underwent DTI of the brachial plexus. Participant characteristics, scanning protocols, and measurements of the fractional anisotropy (FA) and mean diffusivity (MD) of each spinal root were extracted by two independent review authors. Generalised linear modelling was used to estimate the effect of experimental conditions on the FA and MD. Meta-analysis of root-level estimates was performed using Cohen's method with random effects.

Results

Nine articles, describing 316 adults (1:1 male:female) of mean age 35 years (SD 6) were included. Increments of ten diffusion sensitising gradient directions reduced the mean FA by 0.01 (95% CI 0.01, 0.03). Each year of life reduced the mean MD by 0.03 × 10^-3 mm²/s (95% CI 0.01, 0.04). At 3-T, the pooled mean FA of the roots was 0.36 (95% CI 0.34, 0.38; I ² 98%). The pooled mean MD of the roots was 1.51 × 10^-3 mm²/s (95% CI 1.45, 1.56; I ² 99%).

Conclusions

The FA and MD of the roots of the brachial plexus vary according to experimental conditions and participant factors. We provide summary estimates of the normative values in different conditions which may be valuable to researchers and clinicians alike.

Cerebral diffusion kurtosis imaging to assess the pathophysiology of postpartum depression

Postpartum depression (PPD), a main cause of maternal suicide, is an important issue in perinatal mental health. Recently, cerebral diffusion tensor imaging (DTI) studies have shown reduced fractional anisotropy (FA) in major depressive disorder (MDD) patients. There are, however, no reports using diffusion kurtosis imaging (DKI) for evaluation of PPD. This was a Japanese single-institutional prospective study from 2016 to 2019 to examine the pathophysiological changes in the brain of PPD patients using DKI. The DKI data from 3.0 T MRI of patients one month after delivery were analyzed; the patients were examined for PPD by a psychiatrist. The mean kurtosis (MK), FA and mean diffusivity (MD) were calculated from the DKI data and compared between PPD and non-PPD groups using tract-based spatial statistics analysis. Of the 75 patients analyzed, eight patients (10.7%) were diagnosed as having PPD. In the PPD group, FA values in the white matter and thalamus were significantly lower and MD values in the white matter and putamen were significantly higher. The area with significant differences in MD value was more extensive (40.8%) than the area with significant differences in FA value (6.5%). These findings may reflect pathophysiological differences of PPD compared with MDD.

Scanner invariant representations for diffusion MRI harmonization

Purpose

In the present work, we describe the correction of diffusion‐weighted MRI for site and scanner biases using a novel method based on invariant representation.

Theory and Methods

Pooled imaging data from multiple sources are subject to variation between the sources. Correcting for these biases has become very important as imaging studies increase in size and multi‐site cases become more common. We propose learning an intermediate representation invariant to site/protocol variables, a technique adapted from information theory‐based algorithmic fairness; by leveraging the data processing inequality, such a representation can then be used to create an image reconstruction that is uninformative of its original source, yet still faithful to underlying structures. To implement this, we use a deep learning method based on variational auto‐encoders (VAE) to construct scanner invariant encodings of the imaging data.

Results

To evaluate our method, we use training data from the 2018 MICCAI Computational Diffusion MRI (CDMRI) Challenge Harmonization dataset. Our proposed method shows improvements on independent test data relative to a recently published baseline method on each subtask, mapping data from three different scanning contexts to and from one separate target scanning context.

Conclusions

As imaging studies continue to grow, the use of pooled multi‐site imaging will similarly increase. Invariant representation presents a strong candidate for the harmonization of these data.

Structural and functional MRI of altered brain development in a novel adolescent rat model of quinpirole-induced compulsive checking behavior

Obsessive-compulsive disorder (OCD) is increasingly considered to be a neurodevelopmental disorder. However, despite insights in neural substrates of OCD in adults, less is known about mechanisms underlying compulsivity during brain development in children and adolescents. Therefore, we developed an adolescent rat model of compulsive checking behavior and investigated developmental changes in structural and functional measures in the frontostriatal circuitry. Five-weeks old Sprague Dawley rats were subcutaneously injected with quinpirole (n = 21) or saline (n = 20) twice a week for five weeks. Each injection was followed by placement in the middle of an open field table, and compulsive behavior was quantified as repeated checking behavior. Anatomical, resting-state functional and diffusion MRI at 4.7T were conducted before the first and after the last quinpirole/saline injection to measure regional volumes, functional connectivity and structural integrity in the brain, respectively. After consecutive quinpirole injections, adolescent rats demonstrated clear checking behavior and repeated travelling between two open-field zones. MRI measurements revealed an increase of regional volumes within the frontostriatal circuits and an increase in fractional anisotropy (FA) in white matter areas during maturation in both experimental groups. Quinpirole-injected rats showed a larger developmental increase in FA values in the internal capsule and forceps minor compared to control rats. Our study points toward a link between development of compulsive behavior and altered white matter maturation in quinpirole-injected adolescent rats, in line with observations in pediatric patients with compulsive phenotypes. This novel animal model provides opportunities to investigate novel treatments and underlying mechanisms for patients with early-onset OCD specifically.

Widespread Disrupted White Matter Microstructure in Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) are characterised by impaired social communication and restricted repetitive behaviours. Researchers posit that these core features may be underpinned by disrupted structural connectivity. A tract based spatial statistical analysis of diffusion MRI data was performed to investigate white matter organisation (an indication of structural connectivity) in a well-defined cohort of 45 ASD and 45 age and IQ matched control participants. Aberrant structural connectivity characterised by reduced fractional anisotropy was observed in several fiber pathways in ASD relative to controls. Disrupted white matter organisation was associated with social deficits and restricted repetitive behaviours in ASD. Abnormal structural connectivity is apparent in ASD and may be linked to the core behavioural features of the disorder.

Genomic deletion of TLR2 induces aggravated white matter damage and deteriorated neurobehavioral functions in mouse models of Alzheimer's disease

Toll-like receptor-2 (TLR2), a member of the TLR family, plays an important role in the initiation and regulation of immune/inflammation response, which is a critical mechanism underlying Alzheimer’s disease (AD). To clarify the role of TLR2 in the pathological process of AD, in the present study, TLR2 knockout plus APPswe/PSEN1dE9 transgenic mice (AD-TLR2KO) were generated. Neurobehavioral tests and brain MRI scan were conducted on mice at the age of 12 months. Additionally, neuron loss was evaluated using NeuN staining. Amyloid β protein (Aβ), glial fibrillary acidic protein (GFAP), endogenous ligands for TLR2, and the activation of downstream signaling of TLR2 in mouse brains were detected by immunohistochemistry and Western blots. The results demonstrated that TLR2 deficit induced learning disabilities, decreased spontaneous activity, increased anxiety and depression, and led to white matter damage (WMD), brain atrophy, loss of neurons, and glial activation. Moreover, TLR2 deficit aggravated impaired neurobehavioral functions and WMD in AD mice, but did not affect the Aβ deposition in mouse brains. Our data indicate that the genomic deletion of TLR2 impairs neurobehavioral functions, induces WMD and brain atrophy, and increases the activation of astrocytes, which in turn aggravate the symptoms of AD through a non-Aβ mechanism.

Structural correlates of the orbitofrontal cortex and amygdala and personality in female adolescents

The five-factor model consists of cognitive-affective-behavioral trait dimensions (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) that are central to models of psychopathology. In adults, individual differences in three of the Big Five traits, neuroticism, extraversion, and conscientiousness, have been linked to structural morphology and connectivity of the orbitofrontal cortex (OFC) and the amygdala, two brain regions critically involved in affective and regulatory processing. It is unclear whether these associations manifest in adolescence, a critical neurodevelopmental period during which many forms of psychiatric illness emerge. A total of 223 adolescent girls (ages 14-16 years) completed a multimodal neuroimaging study that utilized T1-weighted structural MRI (e.g., cortical thickness and volume) and tractography-based diffusion tensor imaging (64-direction). Cortical thickness and volume were extracted from the medial orbitofrontal cortex (mOFC) and amygdala and tractography-based fractional anisotropy was computed in the uncinate fasciculus (UF; the white matter tract connecting the OFC to the temporal lobe). We found that high neuroticism was associated with less mOFC volume (bilateral), and low conscientiousness was associated with higher white matter integrity in the UF, more amygdala volume, and less mOFC thickness (right hemisphere). Extraversion was not observed to share associations with OFC markers. These OFC-amygdala structural correlations to personality do not match those reported in adult samples. Multimodal neuroimaging techniques can help to clarify the underpinnings of personality development between adolescence and adulthood.

Investigation of anisotropic fishing line-based phantom as tool in quality control of diffusion tensor imaging

This work proposes a low-cost, fishing line-based phantom for quality control of diffusion tensor imaging (DTI). The device was applied to investigate the relationship between DTI indexes (DTIi) and imaging acquisition parameters. A Dyneema^® fishing line phantom was built with fiber bundles of different thicknesses. DTI acquisitions were performed in a 3T magnetic resonance imaging scanner using an 8-channel and a 32-channel head coil. For each coil, the following acquisition parameters were changed, one at a time: diffusion sensitivity factor (b value), echo time, sensitivity encoding, voxel size, number of signal averages, and number of diffusion gradient directions (NDGD). DTIi including fractional anisotropy, relative anisotropy (RA), linear anisotropy (CL), and planar anisotropy (CP) were calculated for each image; the data were analyzed using the coefficient of variation (CV) and distributions of DTIi values. The 32-channel head coil presented higher CV values for the DTIi RA, CL, and CP when voxel size was changed. Using the phantom, dependences between diffusion-related parameters (b value and NDGD) and DTIi were also observed; the majority of these were for the smaller thickness fiber bundles. The device proved to be useful for the verification of the DTI performance over time.

Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3

Brain imaging with diffusion-weighted MRI (dMRI) is sensitive to microstructural white matter (WM) changes associated with brain aging and neurodegeneration. In its third phase, the Alzheimer's Disease Neuroimaging Initiative (ADNI3) is collecting data across multiple sites and scanners using different dMRI acquisition protocols, to better understand disease effects. It is vital to understand when data can be pooled across scanners, and how the choice of dMRI protocol affects the sensitivity of extracted measures to differences in clinical impairment. Here, we analyzed ADNI3 data from 317 participants (mean age: 75.4 ± 7.9 years; 143 men/174 women), who were each scanned at one of 47 sites with one of six dMRI protocols using scanners from three different manufacturers. We computed four standard diffusion tensor imaging (DTI) indices including fractional anisotropy (FA^DTI) and mean, radial, and axial diffusivity, and one FA index based on the tensor distribution function (FA^TDF), in 24 bilaterally averaged WM regions of interest. We found that protocol differences significantly affected dMRI indices, in particular FA^DTI. We ranked the diffusion indices for their strength of association with four clinical assessments. In addition to diagnosis, we evaluated cognitive impairment as indexed by three commonly used screening tools for detecting dementia and AD: the AD Assessment Scale (ADAS-cog), the Mini-Mental State Examination (MMSE), and the Clinical Dementia Rating scale sum-of-boxes (CDR-sob). Using a nested random-effects regression model to account for protocol and site, we found that across all dMRI indices and clinical measures, the hippocampal-cingulum and fornix (crus)/stria terminalis regions most consistently showed strong associations with clinical impairment. Overall, the greatest effect sizes were detected in the hippocampal-cingulum (CGH) and uncinate fasciculus (UNC) for associations between axial or mean diffusivity and CDR-sob. FA^TDF detected robust widespread associations with clinical measures, while FA^DTI was the weakest of the five indices for detecting associations. Ultimately, we were able to successfully pool dMRI data from multiple acquisition protocols from ADNI3 and detect consistent and robust associations with clinical impairment and age.

Analysis of variability of fractional anisotropy values at 3T using a novel diffusion tensor imaging phantom

We employed a novel diffusion tensor imaging phantom to study intra- and interscanner reproducibility on two 3T magnetic resonance (MR) scanners. Using a phantom containing thousands of hollow micron-size tubes in complex arrays, we performed two experiments using a b value of 1000 s/ms² on two Siemens 3T Trio scanners. First, we performed 12-direction scans. Second, on one scanner, we performed two 64-direction protocols with different repetition times (TRs). We used a one-way analysis of variance to calculate differences between scanners and the Mann-Whitney U test to assess differences between 12-direction and 64-direction data. We calculated the coefficient of variation (CoV) for intrascanner and interscanner data. For 12-direction protocols, mean fractional anisotropy (FA) was 0.3003 for Scanner 1 (four scans) and 0.3094 for Scanner 2 (three scans). Lowest FA value on Scanner 1 was 2.56 standard deviations below the mean of Scanner 2. For 64-direction scans, mean FA was 0.2640 for 4000 ms TR and 0.2582 for 13,200 ms TR scans. For 12-direction scans, within-scanner CoV was 0.0326 for Scanner 1 and 0.0240 for Scanner 2; between-scanner CoV was 0.032. For 64-direction scans, CoV was 0.056 for TR 4000 ms and 0.0533 for TR 13,200 ms. The difference between median FA values of 12-direction and 64-direction scans was statistically significant ( p < 0.001). We found relatively good reproducibility on any single MR scanner. FA values from one scanner were sometimes significantly below the mean FA of another scanner, which has important implications for clinical use of DTI.

Failure to Replicate the Association Between Fractional Anisotropy and the Serotonin Transporter Gene (5-HTTLPR, rs25531)

Recent work underlines the importance of alterations in white matter (e.g., measured by fractional anisotropy (FA)) as a neural vulnerability marker for psychiatric disorders. In this context, the uncinate fasciculus (UF), which connects the limbic system with prefrontal areas, has repeatedly been linked to psychiatric disorders, fear processing, and anxiety-related traits. Individual differences in FA may partly be genetically determined. Variation in the promoter region of the serotonin transporter gene (serotonin transporter-linked polymorphic region [5-HTTLPR]) is a particularly promising candidate in this context, which has been linked to psychiatric disorders as well as to limbic and prefrontal reactivity. However, findings on the association between the 5-HTTLPR and FA within the UF-tract have been heterogeneous. The present study investigated this relationship and extended previous work by considering different genetic classification approaches as well as sex effects in a human sample (n = 114). All participants were genotyped for the 5-HTTLPR and the rs25531 polymorphism. As a main result, we did not find any significant relationship between the 5-HTTLPR and FA in the UF-tract although power analyses showed an adequate power. In addition, genotype effects were neither found when different classification approaches were used nor when analyses were carried out in males or females only. The present findings suggest that the association of the 5-HTTLPR and FA seems to be a more labile phenomenon than previously assumed. Possible explanations and limitations are discussed.

Harmonization of multi-site diffusion tensor imaging data

Diffusion tensor imaging (DTI) is a well-established magnetic resonance imaging (MRI) technique used for studying microstructural changes in the white matter. As with many other imaging modalities, DTI images suffer from technical between-scanner variation that hinders comparisons of images across imaging sites, scanners and over time. Using fractional anisotropy (FA) and mean diffusivity (MD) maps of 205 healthy participants acquired on two different scanners, we show that the DTI measurements are highly site-specific, highlighting the need of correcting for site effects before performing downstream statistical analyses. We first show evidence that combining DTI data from multiple sites, without harmonization, may be counter-productive and negatively impacts the inference. Then, we propose and compare several harmonization approaches for DTI data, and show that ComBat, a popular batch-effect correction tool used in genomics, performs best at modeling and removing the unwanted inter-site variability in FA and MD maps. Using age as a biological phenotype of interest, we show that ComBat both preserves biological variability and removes the unwanted variation introduced by site. Finally, we assess the different harmonization methods in the presence of different levels of confounding between site and age, in addition to test robustness to small sample size studies.

A comparison of structural connectivity in anxious depression versus non-anxious depression

BACKGROUND

Major depressive disorder (MDD) and anxiety disorders are highly co-morbid. Research has shown conflicting evidence for white matter alteration and amygdala volume reduction in mood and anxiety disorders. To date, no studies have examined differences in structural connectivity between anxious depressed and non-anxious depressed individuals. This study compared fractional anisotropy (FA) and density of selected white matter tracts and amygdala volume between anxious depressed and non-anxious depressed individuals.

METHODS

64- direction DTI and T1 scans were collected from 110 unmedicated subjects with MDD, 39 of whom had a co-morbid anxiety disorder diagnosis. Region of interest (ROI) and tractography methods were performed to calculate amygdala volume and FA in the uncinate fasciculus, respectively. Diffusion connectometry was performed to identify whole brain group differences in white matter health. Correlations were computed between biological and clinical measures.

RESULTS

Tractography and ROI analyses showed no significant differences between bilateral FA values or bilateral amygdala volumes when comparing the anxious depressed and non-anxious depressed groups. The diffusion connectometry analysis showed no significant differences in anisotropy between the groups. Furthermore, there were no significant relationships between MRI-based and clinical measures.

CONCLUSION

The lack of group differences could indicate that structural connectivity and amygdalae volumes of those with anxious-depression are not significantly altered by a co-morbid anxiety disorder. Improving understanding of anxiety co-morbid with MDD would facilitate development of treatments that more accurately target the underlying networks.

Comparison of Diffusion MRI Acquisition Protocols for the In Vivo Characterization of the Mouse Spinal Cord: Variability Analysis and Application to an Amyotrophic Lateral Sclerosis Model

Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios and the mean value and variability of Diffusion Tensor metrics were evaluated in healthy controls. For the estimation of fractional anisotropy less variability was provided by protocols with more diffusion directions, for the estimation of mean, axial and radial diffusivity by protocols with fewer diffusion directions and higher diffusion weighting. Intermediate features (12 directions, b = 1200 s/mm²) provided the overall minimum inter- and intra-subject variability in most cases. In order to test the diagnostic sensitivity of the protocols, 7 G93A-SOD1 mice (model of amyotrophic lateral sclerosis) at 10 and 17 weeks of age were scanned and the derived diffusion parameters compared with those estimated in age-matched healthy animals. The protocols with an intermediate or high number of diffusion directions provided the best differentiation between the two groups at week 17, whereas only few local significant differences were highlighted at week 10. According to our results, a dMRI protocol with an intermediate number of diffusion gradient directions and a relatively high diffusion weighting is optimal for spinal cord imaging. Further work is needed to confirm these results and for a finer tuning of acquisition parameters. Nevertheless, our findings could be important for the optimization of acquisition protocols for preclinical and clinical dMRI studies on the spinal cord.

Robust diffusion tensor imaging by spatiotemporal encoding: Principles and in vivo demonstrations

PURPOSE

Evaluate the usefulness of single-shot and of interleaved spatiotemporally encoded (SPEN) methods to perform diffusion tensor imaging (DTI) under various preclinical and clinical settings.

METHODS

A formalism for analyzing SPEN DTI data is presented, tailored to account for the spatially dependent b-matrix weightings introduced by the sequence's use of swept pulses acting while in the presence of field gradients. Using these b-matrix calculations, SPEN's ability to deliver DTI measurements was tested on phantoms as well as ex vivo and in vivo. In the latter case, DTI involved scans on mice brains and on human lactating breasts.

RESULTS

For both ex vivo and in vivo investigations, SPEN data proved less sensitive to distortions arising from B_o field inhomogeneities and from eddy currents, than conventional single-shot alternatives. Further resolution enhancement could be achieved using referenceless methods for interleaved SPEN data acquisitions.

CONCLUSION

The robustness of SPEN-based sequences vis-à-vis field instabilities and heterogeneities, enables the implementation of DTI experiments with good sensitivity and resolution even in challenging environments in both preclinical and clinical settings. Magn Reson Med 77:1124-1133, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

A COMPREHENSIVE EXAMINATION OF WHITE MATTER TRACTS AND CONNECTOMETRY IN MAJOR DEPRESSIVE DISORDER

BACKGROUND

Major depressive disorder (MDD) is a debilitating disorder characterized by widespread brain abnormalities. The literature is mixed as to whether or not white matter abnormalities are associated with MDD. This study sought to examine fractional anisotropy (FA) in white matter tracts in individuals with MDD using diffusion tensor imaging (DTI).

METHODS

139 participants with MDD and 39 healthy controls (HC) in a multisite study were included. DTI scans were acquired in 64 directions and FA was determined in the brain using four methods: region of interest (ROI), tract-based spatial statistics (TBSS), and diffusion tractography. Diffusion connectometry was used to identify white matter pathways associated with MDD.

RESULTS

There were no significant differences when comparing FA in MDD and HC groups using any method. In the MDD group, there was a significant relationship between depression severity and FA in the right medial orbitofrontal cortex, and between age of onset of MDD and FA in the right caudal anterior cingulate cortex using the ROI method. There was a significant relationship between age of onset and connectivity in the thalamocortical radiation, inferior longitudinal fasciculus, and cerebellar tracts using diffusion connectometry.

CONCLUSIONS

The lack of group differences in FA and connectometry analysis may result from the clinically heterogenous nature of MDD. However, the relationship between FA and depression severity may suggest a state biomarker of depression that should be investigated as a potential indicator of response. Age of onset may also be a significant clinical feature to pursue when studying white matter tracts.

Diffusion-MRI in neurodegenerative disorders

The ability to image the whole brain through ever more subtle and specific methods/contrasts has come to play a key role in understanding the basis of brain abnormalities in several diseases. In magnetic resonance imaging (MRI), "diffusion" (i.e. the random, thermally-induced displacements of water molecules over time) represents an extraordinarily sensitive contrast mechanism, and the exquisite structural detail it affords has proven useful in a vast number of clinical as well as research applications. Since diffusion-MRI is a truly quantitative imaging technique, the indices it provides can serve as potential imaging biomarkers which could allow early detection of pathological alterations as well as tracking and possibly predicting subtle changes in follow-up examinations and clinical trials. Accordingly, diffusion-MRI has proven useful in obtaining information to better understand the microstructural changes and neurophysiological mechanisms underlying various neurodegenerative disorders. In this review article, we summarize and explore the main applications, findings, perspectives as well as challenges and future research of diffusion-MRI in various neurodegenerative disorders including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease and degenerative ataxias.

A critical review of the neuroimaging literature on synesthesia

Synesthesia refers to additional sensations experienced by some people for specific stimulations, such as the systematic arbitrary association of colors to letters for the most studied type. Here, we review all the studies (based mostly on functional and structural magnetic resonance imaging) that have searched for the neural correlates of this subjective experience, as well as structural differences related to synesthesia. Most differences claimed for synesthetes are unsupported, due mainly to low statistical power, statistical errors, and methodological limitations. Our critical review therefore casts some doubts on whether any neural correlate of the synesthetic experience has been established yet. Rather than being a neurological condition (i.e., a structural or functional brain anomaly), synesthesia could be reconsidered as a special kind of childhood memory, whose signature in the brain may be out of reach with present brain imaging techniques.

Detection of early changes in the parahippocampal and posterior cingulum bundles during mild cognitive impairment by using high-resolution multi-parametric diffusion tensor imaging

We aimed to determine alterations occurring in the parahippocampal cingulum bundle (PhC) and posterior cingulum bundle (PoC) in patients with mild cognitive impairment (MCI) through analysis of high-resolution multi-parametric diffusion tensor imaging (DTI). Participants comprised 41 patients with MCI (21 AD converters [MCI-C] and 20 non-converters [MCI-NC]), 20 patients with Alzheimer׳s disease (AD), and 26 healthy elderly subjects who underwent prospective examination with high-resolution DTI. An atlas-based regions-of-interest (ROIs) method calculated fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR) in the PhC and PoC. For the PhC, FA values showed significant decreases, and MD and DR values showed significantly increases, in the MCI-C and AD groups compared with the healthy controls, although the MCI-C and MCI-NC groups did not differ significantly in these metrics. Conversely, none of the diffusion metrics for the PoC showed a significant difference among the MCI groups and the control groups, although there were significant differences between the AD group and control groups. High-resolution multi-parametric DTI analysis was able to detect substantial changes in diffusion anisotropy and diffusivity in the PhC of patients with MCI who were destined to convert to AD.

Comparisons of Reproducibility and Mean Values of Diffusion Tensor Imaging-Derived Indices between Unipolar and Bipolar Diffusion Pulse Sequences

Eddy current distortion is an important issue that may influence the quantitative measurements of diffusion tensor imaging (DTI). The corrections of eddy current artifacts could be performed using bipolar diffusion gradients or unipolar gradients with affine registration. Whether the diffusion pulse sequence affects the quantification of DTI indices and the technique that produces more reliable DTI indices in terms of reproducibility both remain unclear. Therefore, the purpose of this study was to compare the reproducibility and mean values of DTI-derived indices between unipolar and bipolar diffusion pulse sequences based on actual human brain data. Five repeated datasets of unipolar and bipolar DTI were acquired from 10 healthy subjects at different echo times (TEs). The reproducibility and mean values of DTI indices were assessed by calculating the coefficient of variation and mean values of the 5 repeated measurements. The results revealed that the reproducibility and mean values of DTI indices were significantly affected by the pulse sequence. Unipolar DTI exhibited significantly higher reproducibility than bipolar DTI even at the same TE, and the mean values of DTI indices were significantly different between them. Therefore, we concluded that the reproducibility and mean values of DTI indices were significantly influenced by diffusion pulse sequences.

Effects of MR parameter changes on the quantification of diffusion anisotropy and apparent diffusion coefficient in diffusion tensor imaging: evaluation using a diffusional anisotropic phantom

Objective

To validate the usefulness of a diffusional anisotropic capillary array phantom and to investigate the effects of diffusion tensor imaging (DTI) parameter changes on diffusion fractional anisotropy (FA) and apparent diffusion coefficient (ADC) using the phantom.

Materials and Methods

Diffusion tensor imaging of a capillary array phantom was performed with imaging parameter changes, including voxel size, number of sensitivity encoding (SENSE) factor, echo time (TE), number of signal acquisitions, b-value, and number of diffusion gradient directions (NDGD), one-at-a-time in a stepwise-incremental fashion. We repeated the entire series of DTI scans thrice. The coefficients of variation (CoV) were evaluated for FA and ADC, and the correlation between each MR imaging parameter and the corresponding FA and ADC was evaluated using Spearman's correlation analysis.

Results

The capillary array phantom CoVs of FA and ADC were 7.1% and 2.4%, respectively. There were significant correlations between FA and SENSE factor, TE, b-value, and NDGD, as well as significant correlations between ADC and SENSE factor, TE, and b-value.

Conclusion

A capillary array phantom enables repeated measurements of FA and ADC. Both FA and ADC can vary when certain parameters are changed during diffusion experiments. We suggest that the capillary array phantom can be used for quality control in longitudinal or multicenter clinical studies.

Functional and anatomical properties of human visual cortical fields

Human visual cortical fields (VCFs) vary in size and anatomical location across individual subjects. Here, we used functional magnetic resonance imaging (fMRI) with retinotopic stimulation to identify VCFs on the cortical surface. We found that aligning and averaging VCF activations across the two hemispheres provided clear delineation of multiple retinotopic fields in visual cortex. The results show that VCFs have consistent locations and extents in different subjects that provide stable and accurate landmarks for functional and anatomical mapping. Interhemispheric comparisons revealed minor differences in polar angle and eccentricity tuning in comparable VCFs in the left and right hemisphere, and somewhat greater intersubject variability in the right than left hemisphere. We then used the functional boundaries to characterize the anatomical properties of VCFs, including fractional anisotropy (FA), magnetization transfer ratio (MTR) and the ratio of T1W and T2W images and found significant anatomical differences between VCFs and between hemispheres.

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

Effects of the coexistence of late-life depression and mild cognitive impairment on white matter microstructure

BACKGROUND AND OBJECTIVE

Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are associated with white matter (WM) disruptions of the fronto-limbic and interhemispheric tracts implicated in mood regulation and episodic memory functions. This work investigates the extent of these WM abnormalities in patients LLD and aMCI when these diseases occur alone and when they coexist.

MATERIALS AND METHODS

Eighty-four subjects separated into cognitively normal (n=33), LLD (n=20), aMCI (n=18), and comorbid aMCI and LLD (n=13) completed Diffusion Tensor Imaging (DTI) scans. Tract-based spatial statistics was employed to skeletonize multiple DTI indices of the cingulum, corpus callosum, fornix and uncinate fasciculus. Analysis of covariance and post-hoc tests compared group differences. Multiple linear regressions were performed between DTI and behavioral measures for the whole sample and within individual patient groups.

RESULTS

Divergent microstructural disruptions were identified in LLD- and aMCI-only groups, whereas the comorbid group showed widespread abnormalities especially in the hippocampal cingulum and fornix tracts. The LLD groups also showed significant disruptions in the uncinate fasciculus and corpus callosal tracts. Higher depressive symptom and lower episodic memory scores were associated with increased diffusivity measures in the fornix and hippocampal cingulum across all subjects.

CONCLUSIONS

Widespread WM microstructural disruptions are present when LLD and aMCI are comorbid -especially in the medial temporal lobe tracts. These WM disruptions may be a marker of disease severity. Also, multiple DTI parameters should be used when evaluating the WM fiber integrity in LLD and aMCI.

Limbic system white matter microstructure and long-term treatment outcome in major depressive disorder: a diffusion tensor imaging study using legacy data

OBJECTIVES

Treatment-resistant depression is a common clinical occurrence among patients with major depressive disorder (MDD), but its neurobiology is poorly understood. We used data collected as part of routine clinical care to study white matter integrity of the brain's limbic system and its association to treatment response.

METHODS

Electronic medical records of multiple large New England hospitals were screened for patients with an MDD billing diagnosis, and natural language processing was subsequently applied to find those with concurrent diffusion-weighted images, but without any diagnosed brain pathology. Treatment outcome was determined by review of clinical charts. MDD patients (n = 29 non-remitters, n = 26 partial-remitters, and n = 37 full-remitters), and healthy control subjects (n = 58) were analyzed for fractional anisotropy (FA) of the fornix and cingulum bundle.

RESULTS

Failure to achieve remission was associated with lower FA among MDD patients, statistically significant for the medial body of the fornix. Moreover, global and regional-selective age-related FA decline was most pronounced in patients with treatment-refractory, non-remitted depression.

CONCLUSIONS

These findings suggest that specific brain microstructural white matter abnormalities underlie persistent, treatment-resistant depression. They also demonstrate the feasibility of investigating white matter integrity in psychiatric populations using legacy data.

Geometrical constraints for robust tractography selection

Tract-based analysis from DTI has become a widely employed procedure to study the white matter of the brain and its alterations in neurological and neurosurgical pathologies. Automatic tractography selection methods, where a subset of detected tracts corresponding to a specific white matter structure are selected, are a key component of the DTI processing pipeline. Using automatic tractography selection, repeatable results free of intra and inter-expert variability can be obtained rapidly, without the need for cumbersome manual segmentation. Many of the current approaches for automatic tractography selection rely on a previous registration procedure using an atlas; hence, these methods are likely very sensitive to the accuracy of the registration. In this paper we show that the performance of the registration step is critical to the overall result. This effect can in turn affect the calculation of scalar parameters derived subsequently from the selected tracts and often used in clinical practice; we show that such errors may be comparable in magnitude to the subtle differences found in clinical studies to differentiate between healthy and pathological. As an alternative, we propose a tractography selection method based on the use of geometrical constraints specific for each fiber bundle. Our experimental results show that the approach proposed performs with increased robustness and accuracy with respect to other approaches in the literature, particularly in the presence of imperfect registration.

Intraoperative high-field magnetic resonance imaging combined with fiber tract neuronavigation-guided resection of cerebral lesions involving optic radiation

BACKGROUND

Intraoperative magnetic resonance imaging (iMRI) combined with optic radiation neuronavigation may be safer for resection of cerebral lesions involving the optic radiation.

OBJECTIVE

To investigate whether iMRI combined with optic radiation neuronavigation can help maximize tumor resection while protecting the patient's visual field.

METHODS

Forty-four patients with cerebral tumors adjacent to the optic radiation were enrolled in the study. The reconstructed optic radiations were observed so that a reasonable surgical plan could be developed. During the surgery, microscope-based fiber tract neuronavigation was routinely implemented. The lesion location (lateral or not to the optic radiation) and course of the optic radiation (stretched or not) were categorized, and their relationships to the visual field defect were determined.

RESULTS

Analysis of the visible relationship between the optic radiation and the lesion led to a change in surgical approach in 6 patients (14%). The mean tumor residual rate for glioma patients was 5.3% (n = 36) and 0% for patients with nonglioma lesions (n = 8). Intraoperative MRI and fiber tract neuronavigation increased the average size of resection (first and last iMRI scanning, 88.3% vs 95.7%; P < .01). Visual fields after surgery improved in 5 cases (11.4%), exhibited no change in 36 cases (81.8%), and were aggravated in 3 cases (6.8%).

CONCLUSION

Diffusion tensor imaging information was helpful in surgical planning. When iMRI was combined with fiber tract neuronavigation, the resection rate of brain lesions involving the optic radiation was increased in most patients without harming the patients' visual fields.

White matter abnormalities and illness severity in major depressive disorder

BACKGROUND

White matter abnormalities have been implicated in the aetiology of major depressive disorder; however, the relationship between the severity of symptoms and white matter integrity is currently unclear.

AIMS

To investigate white matter integrity in people with major depression and healthy controls, and to assess its relationship with depressive symptom severity.

METHOD

Diffusion tensor imaging data were acquired from 66 patients with recurrent major depression and a control group of 66 healthy individuals matched for age, gender and IQ score, and analysed with tract-based spatial statistics. The relationship between white matter integrity and severity of depression as measured by the Beck Depression Inventory was examined.

RESULTS

Depressive illness was associated with widespread regions of decreased white matter integrity, including regions in the corpus callosum, superior longitudinal fasciculus and anterior corona radiata, compared with the control group. Increasing symptom severity was negatively correlated with white matter integrity, predominantly in the corpus callosum.

CONCLUSIONS

Widespread alterations in white matter integrity are evident in major depressive disorder. These abnormalities are heightened with increasing severity of depressive symptoms.

Technical note: DTI measurements of fractional anisotropy and mean diffusivity at 1.5 T: comparison of two radiofrequency head coils with different functional designs and sensitivities

PURPOSE

Diffusion tensor imaging (DTI) is highly sensitive to noise and improvement of radiofrequency coil technology represents a straightforward way for augmenting signal-to-noise ratio (SNR) performance in magnetic resonance imaging (MRI) scanners. The aim of this study was to characterize the dependence of DTI measurements of fractional anisotropy (FA) and mean diffusivity (MD) on the choice of head coil, comparing two head coils with different functional designs and sensitivities.

METHODS

Fourteen healthy subjects underwent DTI acquisitions at 1.5 T. Every subject was scanned twice, using a standard quadrature birdcage head coil (coil-A) and an eight-channel array head coil (coil-B). FA and MD maps, estimated using both the linear least squares (LLS) and nonlinear least squares (NLLS) methods, were nonlinearly normalized into a standard space. Then, volumetric regions of interest encompassing typical white and gray matter structures [splenium of the corpus callosum (SCC), internal capsule (IC), cerebral peduncles (CP), middle cerebellar peduncles (MCP), globus pallidus (GP), thalamus (TH), caudate (CA), and putamen (PU)] were analyzed. Significant differences and trends of variation in DTI measurements were assessed by the Wilcoxon test for paired samples with and without Bonferroni correction for multiple comparisons, respectively.

RESULTS

The overall SNR of coil-B was 30% higher than that of coil-A. When comparing DTI measurements (coil-B versus coil-A), mean FA values (SCC, IC, and TH), mean MD values (IC, CP, GP, and TH), FA standard deviation (CP, MCP, GP, and CA), and MD standard deviation (IC, CP, TH, and PU) resulted decreased (significant difference, p(cor) < 0.05, or trend of variation, P(uncor) < 0.05) in several gray and white matter regions of the human brain. With the exception of CP, the results in terms of revealed significant difference or trend of variation were independent of the method (LLS and NLLS) used for estimating the diffusion tensor.

CONCLUSIONS

In various gray and white matter structures, the eight-channel array head coil yielded more precise and accurate measurements of DTI derived indices compared to the standard quadrature birdcage head coil.

Evaluation of corticospinal tract impairment in the brain of patients with amyotrophic lateral sclerosis by using diffusion tensor imaging acquisition schemes with different numbers of diffusion-weighting directions

Amyotrophic lateral sclerosis is characterized by degeneration of upper and lower motor neurons. Diffusion tensor imaging (DTI) indexes obtained along the corticospinal tracts distinguish ALS patients and control subjects. Diffusion tensor imaging can be estimated from at least 6 diffusion-weighted images; however an acquisition scheme with a higher number of diffusion directions allows a more robust estimation of DTI indexes. The aim of the study was to establish if a higher number of diffusion encoding gradients increases the diagnostic accuracy of DTI in ALS. We studied 18 patients and 16 control subjects acquiring 2 DTI data sets with 6 and 31 gradient orientations. The mean diffusivity and fractional anisotropy values were measured along the corticospinal tract. Mean diffusivity in ALS was significantly increased (P = 0.026) with respect to control subjects in acquisition scheme with 31 but not (P = 0.214) with 6 diffusion-weighting directions. Fractional anisotropy was significantly lower in patients both with 6 (P = 0.0036) and with 31 (P = 0.0004) diffusion-weighting directions (0.538 vs 0.588 and 0.530 vs 0.594). Fractional anisotropy receiver operating characteristic curve analysis showed a higher diagnostic accuracy by using 31 diffusion-weighting direction (85.76%) with respect to 6 directions (79.86%). Diffusion tensor imaging confirms its potentials in diagnosing ALS with a good accuracy; the acquisition scheme with a higher diffusion-weighting directions seems to better discriminate between ALS patients and control subjects.