A novel measure of fractional anisotropy based on the tensor distribution function

Age and sex effects on advanced white matter microstructure measures in 15,628 older adults: A UK biobank study

A comprehensive characterization of the brain's white matter is critical for improving our understanding of healthy and diseased aging. Here we used diffusion-weighted magnetic resonance imaging (dMRI) to estimate age and sex effects on white matter microstructure in a cross-sectional sample of 15,628 adults aged 45-80 years old (47.6% male, 52.4% female). Microstructure was assessed using the following four models: a conventional single-shell model, diffusion tensor imaging (DTI); a more advanced single-shell model, the tensor distribution function (TDF); an advanced multi-shell model, neurite orientation dispersion and density imaging (NODDI); and another advanced multi-shell model, mean apparent propagator MRI (MAPMRI). Age was modeled using a data-driven statistical approach, and normative centile curves were created to provide sex-stratified white matter reference charts. Participant age and sex substantially impacted many aspects of white matter microstructure across the brain, with the advanced dMRI models TDF and NODDI detecting such effects the most sensitively. These findings and the normative reference curves provide an important foundation for the study of healthy and diseased brain aging.

Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer's disease deficits

PURPOSE

In diffusion MRI (dMRI), fractional anisotropy derived from the single-tensor model (FA^DTI ) is the most widely used metric to characterize white matter (WM) microarchitecture, despite known limitations in regions with crossing fibers. Due to time constraints when scanning patients in clinical settings, high angular resolution diffusion imaging acquisition protocols, often used to overcome these limitations, are still rare in clinical population studies. However, the tensor distribution function (TDF) may be used to model multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors.

METHODS

We compared the ability of standard FA^DTI and TDF-derived FA (FA^TDF ), calculated from a range of dMRI angular resolutions (41, 30, 15, and 7 gradient directions), to profile WM deficits in 251 individuals from the Alzheimer's Disease Neuroimaging Initiative and to detect associations with 1) Alzheimer's disease diagnosis, 2) Clinical Dementia Rating scores, and 3) average hippocampal volume.

RESULTS

Across angular resolutions and statistical tests, FA^TDF showed larger effect sizes than FA^DTI , particularly in regions preferentially affected by Alzheimer's disease, and was less susceptible to crossing fiber anomalies.

CONCLUSION

The TDF "corrected" form of FA may be a more sensitive and accurate alternative to the commonly used FA^DTI , even in clinical quality dMRI data. Magn Reson Med 78:2322-2333, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Correlation of diffusion tensor imaging parameters in the canine brain

The goal of this study was to determine the degree to which ex vivo diffusion tensor imaging (DTI) parameters correlate to one another in white matter regions on very high resolution MR scans. Specifically, we hypothesized that radial diffusivity (RD) and apparent diffusion coefficient (ADC) would correlate more closely than either would correlate with fractional anisotropy (FA). We performed post mortem DTI imaging on three canine brains on a 7 T MR scanner (TR = 100 ms, NEX = 1, gradient amplitude = 600 mT/m, b = 1492-1,565 s/mm²) and generated maps of FA, RD, and ADC. We measured RD, FA and ADC within 14 regions of interest representative of various portions of white matter. We compared the three combinations of values, i.e., FA vs ADC, FA vs RD and ADC vs RD, using linear regression models. Linear regression demonstrated that RD was significantly correlated with FA (p << 0.01; R² = 0.3053) and also with ADC (p << 0.01; R² = 0.6755), but to a much greater degree. However, ADC was not significantly correlated with FA (p = 0.526; R² = 0.101). Our findings suggest that both RD and ADC reflect similar cytoarchitectural features, most likely that of myelination, whereas FA values likely reflect both myelination and additional microstructural features that constrain the diffusion of water in white matter.

Effects of a Balanced Translocation between Chromosomes 1 and 11 Disrupting the DISC1 Locus on White Matter Integrity

Objective

Individuals carrying rare, but biologically informative genetic variants provide a unique opportunity to model major mental illness and inform understanding of disease mechanisms. The rarity of such variations means that their study involves small group numbers, however they are amongst the strongest known genetic risk factors for major mental illness and are likely to have large neural effects. DISC1 (Disrupted in Schizophrenia 1) is a gene containing one such risk variant, identified in a single Scottish family through its disruption by a balanced translocation of chromosomes 1 and 11; t(1;11) (q42.1;q14.3).

Method

Within the original pedigree, we examined the effects of the t(1;11) translocation on white matter integrity, measured by fractional anisotropy (FA). This included family members with (n = 7) and without (n = 13) the translocation, along with a clinical control sample of patients with psychosis (n = 34), and a group of healthy controls (n = 33).

Results

We report decreased white matter integrity in five clusters in the genu of the corpus callosum, the right inferior fronto-occipital fasciculus, acoustic radiation and fornix. Analysis of the mixed psychosis group also demonstrated decreased white matter integrity in the above regions. FA values within the corpus callosum correlated significantly with positive psychotic symptom severity.

Conclusions

We demonstrate that the t(1;11) translocation is associated with reduced white matter integrity in frontal commissural and association fibre tracts. These findings overlap with those shown in affected patients with psychosis and in DISC1 animal models and highlight the value of rare but biologically informative mutations in modeling psychosis.

White matter integrity and its association with affective and interpersonal symptoms in borderline personality disorder

BACKGROUND

Borderline personality disorder (BPD) is a severe psychiatric disorder involving a range of symptoms including marked affective instability and disturbances in interpersonal interactions. Neuroimaging studies are beginning to provide evidence of altered processing in fronto-limbic network deficits in the disorder, however, few studies directly examine structural connections within this circuitry together with their relation to proposed causative processes and clinical features.

METHODS

In the current study, we investigated whether individuals with BPD (n = 20) have deficits in white matter integrity compared to a matched group of healthy controls (n = 18) using diffusion tensor MRI (DTI). We hypothesized that the BPD group would have decreased fractional anisotropy (FA), a measure of white matter integrity, compared to the controls in white matter tracts connecting frontal and limbic regions, primarily the cingulum, fornix and uncinate fasciculus. We also investigated the extent to which any such deficits related to childhood adversity, as measured by the childhood trauma questionnaire, and symptom severity as measured by the Zanarini rating scale for BPD.

RESULTS

We report decreased white matter integrity in BPD versus controls in the cingulum and fornix. There were no significant relationships between FA and measures of childhood trauma. There were, however, significant associations between FA in the cingulum and clinical symptoms of anger, and in the fornix with affective instability, and measures of avoidance of abandonment from the Zanarini rating scale.

CONCLUSIONS

We report deficits within fronto-limbic connections in individuals with BPD. Abnormalities within the fornix and cingulum were related to severity of symptoms and highlight the importance of these tracts in the pathogenesis of the disorder.

Diffusion weighted imaging-based maximum density path analysis and classification of Alzheimer's disease

Characterizing brain changes in Alzheimer's disease (AD) is important for patient prognosis and for assessing brain deterioration in clinical trials. In this diffusion weighted imaging study, we used a new fiber-tract modeling method to investigate white matter integrity in 50 elderly controls (CTL), 113 people with mild cognitive impairment, and 37 AD patients. After clustering tractography using a region-of-interest atlas, we used a shortest path graph search through each bundle's fiber density map to derive maximum density paths (MDPs), which we registered across subjects. We calculated the fractional anisotropy (FA) and mean diffusivity (MD) along all MDPs and found significant MD and FA differences between AD patients and CTL subjects, as well as MD differences between CTL and late mild cognitive impairment subjects. MD and FA were also associated with widely used clinical scores. As an MDP is a compact low-dimensional representation of white matter organization, we tested the utility of diffusion tensor imaging measures along these MDPs as features for support vector machine based classification of AD.

Altered white matter microstructure is associated with social cognition and psychotic symptoms in 22q11.2 microdeletion syndrome

22q11.2 Microdeletion Syndrome (22q11DS) is a highly penetrant genetic mutation associated with a significantly increased risk for psychosis. Aberrant neurodevelopment may lead to inappropriate neural circuit formation and cerebral dysconnectivity in 22q11DS, which may contribute to symptom development. Here we examined: (1) differences between 22q11DS participants and typically developing controls in diffusion tensor imaging (DTI) measures within white matter tracts; (2) whether there is an altered age-related trajectory of white matter pathways in 22q11DS; and (3) relationships between DTI measures, social cognition task performance, and positive symptoms of psychosis in 22q11DS and typically developing controls. Sixty-four direction diffusion weighted imaging data were acquired on 65 participants (36 22q11DS, 29 controls). We examined differences between 22q11DS vs. controls in measures of fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD), using both a voxel-based and region of interest approach. Social cognition domains assessed were: Theory of Mind and emotion recognition. Positive symptoms were assessed using the Structured Interview for Prodromal Syndromes. Compared to typically developing controls, 22q11DS participants showed significantly lower AD and RD in multiple white matter tracts, with effects of greatest magnitude for AD in the superior longitudinal fasciculus. Additionally, 22q11DS participants failed to show typical age-associated changes in FA and RD in the left inferior longitudinal fasciculus. Higher AD in the left inferior fronto-occipital fasciculus (IFO) and left uncinate fasciculus was associated with better social cognition in 22q11DS and controls. In contrast, greater severity of positive symptoms was associated with lower AD in bilateral regions of the IFO in 22q11DS. White matter microstructure in tracts relevant to social cognition is disrupted in 22q11DS, and may contribute to psychosis risk.

Polygenic risk and white matter integrity in individuals at high risk of mood disorder

BACKGROUND

Bipolar disorder (BD) and major depressive disorder (MDD) are highly heritable and genetically overlapping conditions characterized by episodic elevation and/or depression of mood. Both demonstrate abnormalities in white matter integrity, measured with diffusion tensor magnetic resonance imaging, that are also heritable. However, it is unclear how these abnormalities relate to the underlying genetic architecture of each disorder. Genome-wide association studies have demonstrated a significant polygenic contribution to BD and MDD, where risk is attributed to the summation of many alleles of small effect. Determining the effects of an overall polygenic risk profile score on neuroimaging abnormalities might help to identify proxy measures of genetic susceptibility and thereby inform models of risk prediction.

METHODS

In the current study, we determined the extent to which common genetic variation underlying risk to mood disorders (BD and MDD) was related to fractional anisotropy, an index of white matter integrity. This was conducted in unaffected individuals at familial risk of mood disorder (n = 70) and comparison subjects (n = 62). Polygenic risk scores were calculated separately for BD and MDD on the basis of genome-wide association study data from the Psychiatric GWAS Consortia.

RESULTS

We report that a higher polygenic risk allele load for MDD was significantly associated with decreased white matter integrity across both groups in a large cluster, with a peak in the right-sided superior longitudinal fasciculus.

CONCLUSIONS

These findings suggest that the polygenic approach to examining brain imaging data might be a useful means of identifying traits linked to the genetic risk of mood disorders.

Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging

The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently added diffusion tensor imaging (DTI), among several other new imaging modalities, in an effort to identify sensitive biomarkers of Alzheimer's disease (AD). While anatomical MRI is the main structural neuroimaging method used in most AD studies and clinical trials, DTI is sensitive to microscopic white matter (WM) changes not detectable with standard MRI, offering additional markers of neurodegeneration. Prior DTI studies of AD report lower fractional anisotropy (FA), and increased mean, axial, and radial diffusivity (MD, AxD, RD) throughout WM. Here we assessed which DTI measures may best identify differences among AD, mild cognitive impairment (MCI), and cognitively healthy elderly control (NC) groups, in region of interest (ROI) and voxel-based analyses of 155 ADNI participants (mean age: 73.5 ± 7.4; 90 M/65 F; 44 NC, 88 MCI, 23 AD). Both VBA and ROI analyses revealed widespread group differences in FA and all diffusivity measures. DTI maps were strongly correlated with widely-used clinical ratings (MMSE, CDR-sob, and ADAS-cog). When effect sizes were ranked, FA analyses were least sensitive for picking up group differences. Diffusivity measures could detect more subtle MCI differences, where FA could not. ROIs showing strongest group differentiation (lowest p-values) included tracts that pass through the temporal lobe, and posterior brain regions. The left hippocampal component of the cingulum showed consistently high effect sizes for distinguishing groups, across all diffusivity and anisotropy measures, and in correlations with cognitive scores.

MEASURING INTER-HEMISPHERIC INTEGRATION IN BIPOLAR AFFECTIVE DISORDER USING BRAIN NETWORK ANALYSES AND HARDI

Bipolar disorder is characterized by extreme mood swings, including both manic and depressive episodes commonly accompanied by psychosis. Many imaging studies have investigated white matter changes in bipolar illness, and the results have suggested abnormal intra- and inter-hemispheric white matter structures, particularly in the fronto-limbic and callosal systems. However, some inconsistency remains in the literature, and no study to-date has utilized brain network analysis using graph theory. Here, we acquired 64-direction diffusion weighted imaging (DWI) on 25 euthymic bipolar I subjects and 25 gender/age matched healthy subjects. White matter integrity measures were computed and compared in 50 white matter ROIs. The results indicated impaired integrity in the corpus callosum. Guided by this, we constructed whole brain structural connectivity networks using graph theory. We devised brain network metrics (inter-hemispheric path length and efficiency) to further probe inter-hemispheric integration, and demonstrated relatively preserved intra-hemispheric but significantly impaired inter-hemispheric integration in our bipolar subjects.

Age-related slowing in cognitive processing speed is associated with myelin integrity in a very healthy elderly sample

Performance on measures of cognitive processing speed (CPS) slows with age, but the biological basis associated with this cognitive phenomenon remains incompletely understood. We assessed the hypothesis that the age-related slowing in CPS is associated with myelin breakdown in late-myelinating regions in a very healthy elderly population. An in vivo magnetic resonance imaging (MRI) biomarker of myelin integrity was obtained from the prefrontal lobe white matter and the genu of the corpus callosum for 152 healthy elderly adults. These regions myelinate later in brain development and are more vulnerable to breakdown due to the effects of normal aging. To evaluate regional specificity, we also assessed the splenium of the corpus callosum as a comparison region, which myelinates early in development and primarily contains axons involved in visual processing. The measure of myelin integrity was significantly correlated with CPS in highly vulnerable late-myelinating regions but not in the splenium. These results have implications for the neurobiology of the cognitive changes associated with brain aging.

Opportunities and pitfalls in the quantification of fiber integrity: what can we gain from Q-ball imaging?

The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate directly to superior quantification of fiber integrity. Furthermore, recent developments in QBI reconstruction with solid angle consideration have led to sharper and intrinsically normalized orientation distribution functions. The implications of this technique on quantification are also unknown. To investigate this, the generalized fractional anisotropy (GFA) from the original and the more recent QBI reconstruction scheme and the DTI derived fractional anisotropy (FA) were evaluated comparatively using Monte Carlo simulations and real MRI measurements of crossing fiber phantoms. Contrast-to-noise ratio, accuracy, independence of the acquisition setup and the relation of single fiber anisotropies to measured anisotropy in crossings were assessed. In homogeneous single-fiber regions at b-values around 1000 s/mm2, the FA performed best. While the original QBI reconstruction does not show a clear advantage even at higher b-values and in crossing regions, the new reconstruction scheme yields superior properties and is recommended for quantification at higher b-values and especially in regions of heterogeneous fiber configuration.