scholarly journals Hedonic tone is associated with left supero-lateral medial forebrain bundle microstructure

2014 ◽  
Vol 45 (4) ◽  
pp. 865-874 ◽  
Author(s):  
T. Bracht ◽  
A. N. Doidge ◽  
P. A. Keedwell ◽  
D. K. Jones
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
Medial Forebrain Bundle ◽  
High Angular Resolution ◽  
Hedonic Tone ◽  
Microstructural Alterations ◽  
White Matter Microstructure ◽  
Hedonic Capacity ◽  
Cerebellar Peduncle ◽  
Magnetic Resonance Imaging Mri

Background.The medial forebrain bundle (MFB) is an important pathway of the reward system. Two branches have been described using diffusion magnetic resonance imaging (MRI)-based tractography: the infero-medial MFB (imMFB) and the supero-lateral MFB (slMFB). Previous studies point to white-matter microstructural alterations of the slMFB in major depressive disorder (MDD) during acute episodes. To extend this finding, this study investigates whether white-matter microstructure is also altered in MDD patients that are in remission. Further, we explore associations between diffusion MRI-based metrics of white-matter microstructure of imMFB, slMFB and hedonic tone, the ability to derive pleasure.Method.Eighteen remitted depressed (RD) and 22 never depressed (ND) participants underwent high angular resolution diffusion-weighted imaging (HARDI) scans. To reconstruct the two pathways of the MFB (imMFB and slMFB) we used the damped Richardson–Lucy (dRL) algorithm. Mean fractional anisotropy (FA) was sampled along the tracts.Results.Mean FA of imMFB, slMFB and a comparison tract (the middle cerebellar peduncle) did not differ between ND and RD participants. Hedonic capacity correlated negatively with mean FA of the left slMFB, explaining 21% of the variance.Conclusions.Diffusion MRI-based metrics of white-matter microstructure of the MFB in RD do not differ from ND. Hedonic capacity is associated with altered white-matter microstructure of the slMFB.

scholarly journals Diffusion MRI biomarkers of white matter microstructure vary nonmonotonically with increasing cerebral amyloid deposition

2020 ◽  
Vol 89 ◽  
pp. 118-128 ◽  
Author(s):  
Jian W. Dong ◽  
Ileana O. Jelescu ◽  
Benjamin Ades-Aron ◽  
Dmitry S. Novikov ◽  
Kent Friedman ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
Amyloid Deposition ◽  
White Matter Microstructure ◽  
Cerebral Amyloid

scholarly journals Assessing white matter microstructure of the newborn with multi-shell diffusion MRI and biophysical compartment models

NeuroImage ◽  
2014 ◽  
Vol 96 ◽  
pp. 288-299 ◽  
Author(s):  
Nicolas Kunz ◽  
Hui Zhang ◽  
Lana Vasung ◽  
Kieran R. O'Brien ◽  
Yaniv Assaf ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
Compartment Models ◽  
White Matter Microstructure

scholarly journals Superficial white matter microstructure affects processing speed in cerebral small vessel disease

2022 ◽  
Author(s):  
Shuyue Wang ◽  
Fan Zhang ◽  
Peiyu Huang ◽  
Hui Hong ◽  
Yeerfan Jiaerken ◽  
...  
Keyword(s):  
White Matter ◽  
Processing Speed ◽  
Diffusion Mri ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Large Contribution ◽  
Vessel Disease ◽  
White Matter Microstructure ◽  
Patient Subgroups

White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD). This condition contributes to about 50% of dementias worldwide, a massive health burden in aging. Microstructural alterations in the deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in the superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In this paper, 141 patients with CSVD were studied. Processing speed was assessed by the completion time of the Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (lesion volume on T2-FLAIR) and diffusion MRI, including DTI and free-water (FW) imaging microstructure measures. The results of our study indicate that the superficial white matter may play a particularly important role in cognitive decline in CSVD. SWM imaging measures resulted in a large contribution to processing speed, despite a relatively small WMH burden in the SWM. SWM FW had the strongest association with processing speed among all imaging markers and, unlike the other diffusion MRI measures, significantly increased between two patient subgroups with the lowest WMH burdens (possibly representing early stages of disease). When comparing two patient subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Given significant effects of WMH volume and regional FW on processing speed, we performed a mediation analysis. SWM FW was found to fully mediate the association between WMH volume and processing speed, while no mediation effect of DWM FW was observed. Overall, our findings identify SWM abnormalities in CSVD and suggest that the SWM has an important contribution to processing speed. Results indicate that FW in the SWM is a sensitive marker of microstructural changes associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes in future research.

scholarly journals The prospective association of objectively measured sleep and cerebral white matter microstructure in middle-aged and older persons

SLEEP ◽  
2019 ◽  
Author(s):  
Desana Kocevska ◽  
Henning Tiemeier ◽  
Thom S Lysen ◽  
Marius de Groot ◽  
Ryan L Muetzel ◽  
...  
Keyword(s):  
White Matter ◽  
Corpus Callosum ◽  
Older Persons ◽  
Sleep Onset ◽  
Cerebral White Matter ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Middle Aged ◽  
Microstructural Alterations ◽  
White Matter Microstructure

AbstractStudy ObjectivesPoor sleep may destabilize axonal integrity and deteriorate cerebral white matter. In middle-aged and older adults sleep problems increase alongside structural brain changes, but the temporal relation between these processes is poorly understood. We studied longitudinal associations between sleep and cerebral white matter microstructure.MethodsOne thousand one persons (59.3 ± 7.9 years, 55% women) were followed across 5.8 years (3.9–10.8). Total sleep time (TST, hours), sleep efficiency (SE, percentage), sleep onset latency (SOL, minutes), and wake after sleep onset (WASO, minutes) were measured at baseline using a wrist-worn actigraph. White matter microstructure (global and tract-specific fractional anisotropy [FA] and mean diffusivity [MD]) was measured twice with diffusion tensor imaging (DTI).ResultsPoor sleep was associated with worse white matter microstructure up to 7 years later but did not predict trajectories of DTI over time. Longer TST was associated with higher global FA (β = 0.06, 95% CI: 0.01 to 0.12), but not with MD. Persons with higher SE had higher global FA (β = 0.01, 95% CI: 0.002 to 0.01) and lower MD (β = −0.01, 95% CI: −0.01 to −0.0004). Consistently, those with more WASO had lower global FA (β = −0.003, 95% CI: −0.005 to −0.001) and higher MD (β = 0.002, 95% CI: 0.0004 to 0.004). Global findings seemed to be driven by microstructural alterations in the cingulum, anterior forceps of corpus callosum, projection and association tracts.ConclusionsMiddle-aged and older persons with more WASO, lower SE and shorter TST have worse microstructure of cerebral white matter. Microstructural alterations are most pronounced projection and association tracts, in the cingulum, and in the anterior forceps of corpus callosum.

Another Piece of the Puzzle of Anomalous Connectivity in Joubert's Syndrome

2021 ◽  
Author(s):  
Avner Meoded ◽  
Marcia Kukreja ◽  
Gunes Orman ◽  
Eugen Boltshauser ◽  
Thierry A.G.M. Huisman
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Three Dimensional ◽  
Axonal Guidance ◽  
Molar Tooth ◽  
Superior Cerebellar Peduncle ◽  
Corticospinal Tracts ◽  
Cerebellar Peduncles ◽  
Cerebellar Peduncle ◽  
Magnetic Resonance Imaging Mri

AbstractWe report on the conventional and diffusion tensor imaging (DTI) findings of a 2-year-old child with clinical presentation of Joubert's Syndrome (JS) and brainstem structural abnormalities as depicted by neuroimaging.Conventional magnetic resonance imaging (MRI) showed a “molar tooth” configuration of the brainstem. A band-like formation coursing in an apparent axial plane anterior to the interpeduncular fossa was noted and appeared to partially cover the interpeduncular fossa.DTI maps and three-dimensional (3D) tractography demonstrated a prominent red-encoded white matter bundle anterior to the midbrain. Probable aberrant course of the bilateral corticospinal tracts (CST) was also depicted. Absence of the decussation of the superior cerebellar peduncles and elongated thickened, horizontal superior cerebellar peduncle (SCP) reflecting the molar tooth sign were also shown.Our report and the review of the published cases suggest that DTI and tractography may be very helpful to differentiate between interpeduncular heterotopias and similarly located white matter bundles corroborating the underlying etiology of axonal guidance disorders in the complex group of ciliopathies including JS. Our case represents an important additional puzzle piece to explore the variability of these ciliopathies.

scholarly journals In vivo microstructural heterogeneity of white matter lesions in Alzheimer’s disease using tissue compositional analysis of diffusion MRI data

2019 ◽  
Author(s):  
Remika Mito ◽  
Thijs Dhollander ◽  
Ying Xia ◽  
David Raffelt ◽  
Olivier Salvado ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Diffusion Mri ◽  
Classification Scheme ◽  
Free Water ◽  
Imaging Biomarkers ◽  
White Matter Microstructure ◽  
Periventricular Lesions

AbstractWhite matter hyperintensities (WMH) are commonly observed in elderly individuals, and are typically more prevalent in Alzheimer’s disease subjects than in healthy subjects. These lesions can be identified on fluid attenuated inversion recovery (FLAIR) MRI, on which they are hyperintense compared to their surroundings. These MRI-visible lesions appear homogeneously hyperintense despite known heterogeneity in their pathological underpinnings, and are commonly regarded as surrogate markers of small vessel disease in in vivo studies. Consequently, the extent to which these lesions contribute to Alzheimer’s disease remains unclear, likely due to the somewhat limited way in which these lesions are assessed in vivo. Diffusion MRI is sensitive to white matter microstructure, and might thus be used to investigate microstructural changes within WMH. In this study, we applied a method called single-shell 3-tissue constrained spherical deconvolution, which models white matter microstructure while also accounting for other tissue compartments, to investigate WMH in vivo. Diffusion MRI data and FLAIR images were obtained from Alzheimer’s disease (n = 48) and healthy elderly control (n = 94) subjects from the Australian Imaging, Biomarkers and Lifestyle study of ageing. WMH were automatically segmented and classified as periventricular or deep lesions from FLAIR images based on their continuity with the lateral ventricles, and the 3-tissue profile of different classes of WMH was characterised by three metrics, which together characterised the relative tissue profile in terms of the white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our findings revealed that periventricular and deep lesion classes could be distinguished from one another, and from normal-appearing white matter based on their 3-tissue profile, with substantially higher free water content in periventricular lesions than deep. Given the higher lesion load of periventricular lesions in Alzheimer’s disease patients, the 3-tissue profile of these WMH could be interpreted as reflecting the more deleterious pathological underpinnings that are associated with disease. However, when alternatively classifying lesion sub-regions in terms of distance contours from the ventricles to account for potential heterogeneity within confluent lesions, we found that the highest fluid content was present in lesion areas most proximal to the ventricles, which were common to both Alzheimer’s disease subjects and healthy controls. We argue that whatever classification scheme is used when investigating WMH, failure to account for heterogeneity within lesions may result in classification-scheme dependent conclusions. Future studies of WMH in Alzheimer’s Disease would benefit from inclusion of microstructural information when characterising lesions.

scholarly journals The role of diffusion MRI in neuroscience

2017 ◽  
Author(s):  
Yaniv Assaf ◽  
Heidi Johansen-Berg ◽  
Michel Thiebaut de Schotten
Keyword(s):  
White Matter ◽  
Diffusion Weighted Imaging ◽  
Diffusion Mri ◽  
Future Generations ◽  
Brain Anatomy ◽  
Diffusion Weighted ◽  
White Matter Microstructure ◽  
Functional Models ◽  
Key Questions

AbstractDiffusion weighted imaging has further pushed the boundaries of neuroscience by allowing us to peer farther into the white matter microstructure of the living human brain. By doing so, it has provided answers to fundamental neuroscientific questions, launching a new field of research that had been largely inaccessible. We will briefly summarise key questions, that have historically been raised in neuroscience, concerning the brain’s white matter. We will then expand on the benefits of diffusion weighted imaging and its contribution to the fields of brain anatomy, functional models and plasticity. In doing so, this review will highlight the invaluable contribution of diffusion weighted imaging in neuroscience, present its limitations and put forth new challenges for the future generations who may wish to exploit this powerful technology to gain novel insights.

scholarly journals Comparison of Neurite Orientation Dispersion and Density Imaging and Two-Compartment Spherical Mean Technique Parameter Maps in Multiple Sclerosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Daniel Johnson ◽  
Antonio Ricciardi ◽  
Wallace Brownlee ◽  
Baris Kanber ◽  
Ferran Prados ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Diffusion Mri ◽  
Volume Fraction ◽  
Diffusion Tensor ◽  
Healthy Controls ◽  
Age And Gender ◽  
Spherical Mean ◽  
White Matter Microstructure ◽  
And Gender

Background: Neurite orientation dispersion and density imaging (NODDI) and the spherical mean technique (SMT) are diffusion MRI methods providing metrics with sensitivity to similar characteristics of white matter microstructure. There has been limited comparison of changes in NODDI and SMT parameters due to multiple sclerosis (MS) pathology in clinical settings.Purpose: To compare group-wise differences between healthy controls and MS patients in NODDI and SMT metrics, investigating associations with disability and correlations with diffusion tensor imaging (DTI) metrics.Methods: Sixty three relapsing-remitting MS patients were compared to 28 healthy controls. NODDI and SMT metrics corresponding to intracellular volume fraction (vin), orientation dispersion (ODI and ODE), diffusivity (D) (SMT only) and isotropic volume fraction (viso) (NODDI only) were calculated from diffusion MRI data, alongside DTI metrics (fractional anisotropy, FA; axial/mean/radial diffusivity, AD/MD/RD). Correlations between all pairs of MRI metrics were calculated in normal-appearing white matter (NAWM). Associations with expanded disability status scale (EDSS), controlling for age and gender, were evaluated. Patient-control differences were assessed voxel-by-voxel in MNI space controlling for age and gender at the 5% significance level, correcting for multiple comparisons. Spatial overlap of areas showing significant differences were compared using Dice coefficients.Results: NODDI and SMT show significant associations with EDSS (standardised beta coefficient −0.34 in NAWM and −0.37 in lesions for NODDI vin; 0.38 and −0.31 for SMT ODE and vin in lesions; p < 0.05). Significant correlations in NAWM are observed between DTI and NODDI/SMT metrics. NODDI vin and SMT vin strongly correlated (r = 0.72, p < 0.05), likewise NODDI ODI and SMT ODE (r = −0.80, p < 0.05). All DTI, NODDI and SMT metrics detect widespread differences between patients and controls in NAWM (12.57% and 11.90% of MNI brain mask for SMT and NODDI vin, Dice overlap of 0.42).Data Conclusion: SMT and NODDI detect significant differences in white matter microstructure between MS patients and controls, concurring on the direction of these changes, providing consistent descriptors of tissue microstructure that correlate with disability and show alterations beyond focal damage. Our study suggests that NODDI and SMT may play a role in monitoring MS in clinical trials and practice.

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