Adaptive Noise Filtering for Accurate and Precise Diffusion Estimation in Fiber Crossings. In: Jiang T, Navab N, Pluim JPW, Viergever MA, editors. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010. Berlin: Springer Berlin Heidelberg; 2010. pp. 167-74. [DOI: 10.1007/978-3-642-15705-9_21]

Neuropsychiatric symptoms of cholinergic deficiency occur with degradation of the projections from the nucleus basalis of Meynert

This study aims to evaluate the relation between a cluster of neuropsychiatric symptoms related to cholinergic deficiency and degradation of the cortical cholinergic projections which project from the nucleus basalis of Meynert to the cerebral cortex. An atlas of the pathway from the nucleus basalis to the cortex (NbM cortical pathway) was constructed using diffusion tensor imaging and tractography in 87 memory clinic patients. Structural degradation was considered to be represented by lower fractional anisotropy (FA) and higher mean diffusivity (MD). Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory. A predefined cluster including agitation, anxiety, apathy, delusions, hallucinations, and irritability was labeled as the cholinergic deficiency syndrome (CDS). In regression analyses, lower FA and higher MD in the NbM cortical pathway were associated with CDS symptoms but not with other neuropsychiatric symptoms. These associations were independent of cerebral atrophy and overall FA or MD. There was no association between interruption of the NbM cortical pathway by white matter hyperintensities and CDS symptoms. Cox regression suggested a trend for higher mortality with lower FA in the NbM cortical pathway may exist. These findings provide anatomical support for the hypothesis that degradation of the cholinergic projections from the nucleus basalis of Meynert may lead to a distinct clinical syndrome. Future studies could use our results to test the utility of assessing NbM projection integrity to identify patients who may benefit from cholinergic treatment or with a worse prognosis.

ADHD and maturation of brain white matter: A DTI study in medication naive children and adults

Several diffusion tensor imaging (DTI) studies in attention deficit hyperactivity disorder (ADHD) have shown a delay in brain white matter (WM) development. Because these studies were mainly conducted in children and adolescents, these WM abnormalities have been assumed, but not proven to progress into adulthood. To provide further insight in the natural history of WM maturation delay in ADHD, we here investigated the modulating effect of age on WM in children and adults. 120 stimulant-treatment naive male ADHD children (10-12 years of age) and adults (23-40 years of age) with ADHD (according to DSM-IV; all subtypes) were included, along with 23 age and gender matched controls. Fractional anisotropy (FA) values were compared throughout the WM by means of tract-based spatial statistics (TBSS) and in specific regions of interest (ROIs). On both TBSS and ROI analyses, we found that stimulant-treatment naive ADHD children did not differ in FA values from control children, whereas adult ADHD subjects had reduced FA values when compared to adult controls in several regions. Significant age × group interactions for whole brain FA (p = 0.015), as well as the anterior thalamic radiation (p = 0.015) suggest that ADHD affects the brain WM age-dependently. In contrast to prior studies conducted in medicated ADHD children, we did not find WM alterations in stimulant treatment naïve children, only treatment-naïve adults. Thus, our findings suggest that the reported developmental delay in WM might appear after childhood, and that previously reported differences between ADHD children and normal developing peers could have been attributed to prior ADHD medications, and/or other factors that affect WM development, such as age and gender.

Decreased uncinate fasciculus tract integrity in male and female patients with PTSD: a diffusion tensor imaging study

BACKGROUND

Posttraumatic stress disorder (PTSD) is a disabling psychiatric disorder that has been associated with lower white matter integrity of tracts connecting the prefrontal cortex with limbic regions. However, previous diffusion tensor imaging (DTI) findings have been inconsistent, showing high variability in the exact location and direction of effects.

METHODS

We performed probabilistic tractography of the bilateral uncinate fasciculus, cingulum and superior longitudinal fasciculus (both temporal and parietal projections) in male and female police officers with and without PTSD.

RESULTS

We included 38 (21 men) police officers with and 39 (20 men) without PTSD in our analyses. Compared with trauma-exposed controls, patients with PTSD showed significantly higher mean diffusivity of the right uncinate fasciculus, the major white matter tract connecting the amygdala to the prefrontal cortex (p = 0.012). No other significant between-group or group × sex differences were observed. Mean diffusivity of the right uncinate fasciculus was positively associated with anxiety symptoms (r = 0.410, p = 0.013) in patients with PTSD as well as with amygdala activity (r = 0.247, p = 0.038) and ventromedial prefrontal cortex (vmPFC) activity (r = 0.283, p = 0.016) in all participants in response to happy and neutral faces.

LIMITATIONS

Our specific sample of trauma-exposed police officers limits the generalizability of our findings to other PTSD patient groups (e.g., civilian trauma).

CONCLUSION

Patients with PTSD showed diminished structural connectivity between the amygdala and vmPFC, which was correlated with higher anxiety symptoms and increased functional activity of these brain regions. Our findings provide additional evidence for the prevailing neurocircuitry model of PTSD, postulating that ineffective communication between the amygdala and vmPFC underlies decreased top-down control over fear responses.

White matter alterations in cocaine users are negatively related to the number of additionally (ab)used substances

Diffusion tensor imaging studies have provided evidence for white matter (WM) alterations in cocaine users. While polysubstance use is a widespread phenomenon among cocaine users, its role in WM alterations in cocaine users is currently unknown. This study examined the relation between the number of substances that are used(cocaine, alcohol and marijuana) and WM alterations in 67 male non-drug users and 67 male regular cocaine users, who were classified into five groups based on the number of used substances. Diffusion-weighted images were acquired on a 3.0 T magnetic resonance imaging scanner. Using tract-based spatial statistics we demonstrated that there was a negative relation between the number of used substances and fractional anisotropy, a global measure of WM integrity. Also, we demonstrated a positive relation between the number of used substance and radial diffusivity within the prefrontal lobe, suggesting an increase in demyelination with the number of used substances. We did not find a dose-effect between the level of substance use and WM alterations. The results of the current study may reflect the presence of a pre-existing vulnerability to polysubstance use resulting from prefrontal WM abnormalities and related impaired cognitive control although WM alterations because of polysubstance use cannot be fully excluded. This study is an important first step in understanding the problems related to polysubstance use among cocaine users.

Age-related differences in autism: The case of white matter microstructure

Autism spectrum disorder (ASD) is typified as a brain connectivity disorder in which white matter abnormalities are already present early on in life. However, it is unknown if and to which extent these abnormalities are hard-wired in (older) adults with ASD and how this interacts with age-related white matter changes as observed in typical aging. The aim of this first cross-sectional study in mid- and late-aged adults with ASD was to characterize white matter microstructure and its relationship with age. We utilized diffusion tensor imaging with head motion control in 48 adults with ASD and 48 age-matched controls (30-74 years), who also completed a Flanker task. Intra-individual variability of reaction times (IIVRT) measures based on performance on the Flanker interference task were used to assess IIVRT-white matter microstructure associations. We observed primarily higher mean and radial diffusivity in white matter microstructure in ASD, particularly in long-range fibers, which persisted after taking head motion into account. Importantly, group-by-age interactions revealed higher age-related mean and radial diffusivity in ASD, in projection and association fiber tracts. Subtle dissociations were observed in IIVRT-white matter microstructure relations between groups, with the IIVRT-white matter association pattern in ASD resembling observations in cognitive aging. The observed white matter microstructure differences are lending support to the structural underconnectivity hypothesis in ASD. These reductions seem to have behavioral percussions given the atypical relationship with IIVRT. Taken together, the current results may indicate different age-related patterns of white matter microstructure in adults with ASD. Hum Brain Mapp 38:82-96, 2017. © 2016 Wiley Periodicals, Inc.

A localized Richardson-Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging

PURPOSE

Diffusion tensor imaging is widely used for studying neural fiber trajectories in white matter and for quantifying changes in tissue using diffusion properties at each voxel in the brain. To better model the nature of crossing fibers within complex architectures, rather than using a simplified tensor model that assumes only a single fiber direction at each image voxel, a model mixing multiple diffusion tensors is used to profile diffusion signals from high angular resolution diffusion imaging (HARDI) data. Based on the HARDI signal and a multiple tensors model, spherical deconvolution methods have been developed to overcome the limitations of the diffusion tensor model when resolving crossing fibers. The Richardson-Lucy algorithm is a popular spherical deconvolution method used in previous work. However, it is based on a Gaussian distribution, while HARDI data are always very noisy, and the distribution of HARDI data follows a Rician distribution. This current work aims to present a novel solution to address these issues.

METHODS

By simultaneously considering both the Rician bias and neighbor correlation in HARDI data, the authors propose a localized Richardson-Lucy (LRL) algorithm to estimate fiber orientations for HARDI data. The proposed method can simultaneously reduce noise and correct the Rician bias.

RESULTS

Mean angular error (MAE) between the estimated Fiber orientation distribution (FOD) field and the reference FOD field was computed to examine whether the proposed LRL algorithm offered any advantage over the conventional RL algorithm at various levels of noise. Normalized mean squared error (NMSE) was also computed to measure the similarity between the true FOD field and the estimated FOD filed. For MAE comparisons, the proposed LRL approach obtained the best results in most of the cases at different levels of SNR and b-values. For NMSE comparisons, the proposed LRL approach obtained the best results in most of the cases at b-value = 3000 s/mm(2), which is the recommended schema for HARDI data acquisition. In addition, the FOD fields estimated by the proposed LRL approach in regions of fiber crossing regions using real data sets also showed similar fiber structures which agreed with common acknowledge in these regions.

CONCLUSIONS

The novel spherical deconvolution method for improved accuracy in investigating crossing fibers can simultaneously reduce noise and correct Rician bias. With the noise smoothed and bias corrected, this algorithm is especially suitable for estimation of fiber orientations in HARDI data. Experimental results using both synthetic and real imaging data demonstrated the success and effectiveness of the proposed LRL algorithm.

Lower cognitive performance and white matter changes in testicular cancer survivors 10 years after chemotherapy

OBJECTIVE

Chemotherapy (CT) is associated with adverse effects on cognition. Only few studies have investigated cognition in testicular cancer (TC) patients and studies on very late effects of CT on cognition are absent. Further, brain changes in relation to treatment have not been investigated in TC. The objective of the present study is to compare psychosocial functioning, cognitive performance and brain (micro)structure following surgery and CT for TC, against surgery (S)-only.

METHODS

Twenty-eight CT (43.1±7.5 y) and 23 S-only (48.2±9.5y) TC survivors on average 14 yr post-treatment were examined using questionnaires, neurocognitive tests, and 3T-MRI [Diffusion Kurtosis Imaging (DKI), T1-weighted and Fluid Attenuated Inversion Recovery]. A multivariate cognitive performance score (Mahalanobis distance) was calculated to indicate the grade of cognitive performance. Kurtosis parameters, gray matter, and white matter (WM) volume were calculated from MRI data.

RESULTS

Overall, the CT group showed lower cognitive performance (5.35±1.7) compared with the S-only group (4.4±0.9; P=0.03; d=0.70). Further, TC patients reported more memory problems after CT. DKI revealed a significantly higher radial kurtosis after CT in several anterior and posterior brain areas (P<0.05, corrected), but this was unrelated to cognitive performance.

CONCLUSIONS

This cross-sectional study suggests that men receiving CT for TC are at risk for long-term lower cognitive performance. Although CT affected WM microstructure, this was unrelated to cognitive performance. More extensive, preferably prospective studies are warranted to confirm these results and to provide more insight into the possible mechanisms behind the observed cognitive sequelae after treatment for TC.

Polyunsaturated fatty acid concentration predicts myelin integrity in early-phase psychosis

BACKGROUND

White matter (WM) abnormalities have been implicated in schizophrenia, yet the mechanisms underlying these abnormalities are not fully understood. Several lines of evidence suggest that polyunsaturated fatty acids (PUFAs) play a role in myelination, and there is substantial evidence documenting decreased PUFA concentrations in schizophrenia. We therefore hypothesized that lower membrane PUFA concentrations may be related to reduced WM integrity in schizophrenia and related disorders.

METHODS

In 30 male patients with a recent-onset psychotic disorder, erythrocyte membrane PUFA concentrations were assessed and diffusion tensor imaging was performed with voxelwise analysis.

RESULTS

Lower total PUFA concentration was associated with lower fractional anisotropy (FA) throughout the corpus callosum and bilateral parietal, occipital, temporal and frontal WM (P < .05, corrected). Of the individual PUFAs, lower arachidonic acid concentration, and to a lesser extent, lower nervonic acid, linoleic acid, and docosapentaenoic acid concentration were significantly associated with lower FA. PUFA concentrations were inversely associated with radial diffusivity but showed little association with axial diffusivity. Greater severity of negative symptoms was associated with lower nervonic acid concentration and lower FA values.

CONCLUSIONS

Membrane PUFA concentrations appear to be robustly related to brain WM integrity in early phase psychosis. These findings may provide a basis for studies to investigate the effects of PUFA supplementation on WM integrity and associated symptomatology in early psychosis.

Improved diffusion imaging through SNR-enhancing joint reconstruction

Quantitative diffusion imaging is a powerful technique for the characterization of complex tissue microarchitecture. However, long acquisition times and limited signal-to-noise ratio represent significant hurdles for many in vivo applications. This article presents a new approach to reduce noise while largely maintaining resolution in diffusion weighted images, using a statistical reconstruction method that takes advantage of the high level of structural correlation observed in typical datasets. Compared to existing denoising methods, the proposed method performs reconstruction directly from the measured complex k-space data, allowing for gaussian noise modeling and theoretical characterizations of the resolution and signal-to-noise ratio of the reconstructed images. In addition, the proposed method is compatible with many different models of the diffusion signal (e.g., diffusion tensor modeling and q-space modeling). The joint reconstruction method can provide significant improvements in signal-to-noise ratio relative to conventional reconstruction techniques, with a relatively minor corresponding loss in image resolution. Results are shown in the context of diffusion spectrum imaging tractography and diffusion tensor imaging, illustrating the potential of this signal-to-noise ratio-enhancing joint reconstruction approach for a range of different diffusion imaging experiments.

Persistent and reversible consequences of combat stress on the mesofrontal circuit and cognition

Prolonged stress can have long-lasting effects on cognition. Animal models suggest that deficits in executive functioning could result from alterations within the mesofrontal circuit. We investigated this hypothesis in soldiers before and after deployment to Afghanistan and a control group using functional and diffusion tensor imaging. Combat stress reduced midbrain activity and integrity, which was associated to compromised sustained attention. Long-term follow-up showed that the functional and structural changes had normalized within 1.5 y. In contrast, combat stress induced a persistent reduction in functional connectivity between the midbrain and prefrontal cortex. These results demonstrate that combat stress has adverse effects on the human mesofrontal circuit and suggests that these alterations are partially reversible.

Parallel MRI noise correction: an extension of the LMMSE to non central chi distributions

Parallel MRI leads to magnitude data corrupted by noise described in most cases as following a Rician or a non central chi distribution. And yet, very few correction methods perform a non central chi noise removal. However, this correction step, adapted to the correct noise model, is of very much importance, especially when working with Diffusion Weighted MR data yielding a low SNR. We propose an extended Linear Minimum Mean Square Error estimator (LMMSE), which is adapted to deal with non central chi distributions. We demonstrate on simulated and real data that the extended LMMSE outperforms the original LMMSE on images corrupted by a non central chi noise.

Estimation of diffusion properties in crossing fiber bundles

There is an ongoing debate on how to model diffusivity in fiber crossings. We propose an optimization framework for the selection of a dual tensor model and the set of diffusion weighting parameters b, such that both the diffusion shape and orientation parameters can be precisely as well as accurately estimated. For that, we have adopted the Cramér-Rao lower bound (CRLB) on the variance of the model parameters, and performed Monte Carlo simulations. We have found that the axial diffusion lambda(parallel) needs to be constrained, while an isotropic fraction can be modeled by a single parameter f(iso). Under these circumstances, the Fractional Anisotropy (FA) of both tensors can theoretically be independently estimated with a precision of 9% (at SNR = 25). Levenberg-Marquardt optimization of the Maximum Likelihood function with a Rician noise model approached this precision while the bias was insignificant. A two-element b-vector b = [1.0 3.5] x 10(3) mm(-2)s was found to be sufficient for estimating parameters of heterogeneous tissue with low error. This has allowed us to estimate consistent FA-profiles along crossing tracts. This work defines fundamental limits for comparative studies to correctly analyze crossing white matter structures.