Abnormal Rich Club Organization in Hemispheric White Matter Networks of ADHD

2019 ◽  
pp. 108705471989288
Author(s):  
Dandan Li ◽  
Xiaohong Cui ◽  
Ting Yan ◽  
Bo Liu ◽  
Hui Zhang ◽  
...  

Objective: Brain network studies have revealed abnormal topology asymmetry of white matter (WM) in ADHD. Recently, rich club organization was proposed to be a key feature of brain network topology. However, abnormalities in the rich club organization of hemispheric WM networks in ADHD remain unclear. Method: Forty ADHD patients and 51 normal controls participated in this study. Structural networks were reconstructed based on diffusion tensor imaging (DTI) and analyzed with graph theory. Results: The two groups exhibited different patterns of asymmetry in connectivity measures of rich club connections. ADHD patients showed more feeder connections than normal controls. Reduced rightward asymmetry was observed in connectivity measures of local connections involving several peripheral regions of the ADHD patients. In addition, abnormal regional asymmetry scores were associated with ADHD symptoms. Conclusion: The topological changes in rich club organization provide a novel insight into the alteration of WM connections in ADHD.

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Michael J. McGill ◽  
Qiuting Wen ◽  
Ho-Ching Yang ◽  
Salman Shahid ◽  
Yu-Chien Wu

Background:  Traumatic brain injury (TBI) is a leading cause of death and disability throughout the world, estimated to carry an annual global incidence of over 27 million cases. Mild TBI (mTBI), commonly known as concussion, is the mildest form of TBI and accounts for roughly 90% of all head injuries. Sports-related concussion (SRC) contributes significantly to this statistic with millions of athletes sustaining high-impact injuries in contact sports such as football, soccer, and lacrosse. By examining the white-matter microstructure, diffusion tensor imaging (DTI) has shown excellent capabilities for detecting pathophysiologic changes after SRC and monitoring symptom progression. Biomarkers including neurofilament light (NfL) and tau have been implicated in SRC and may provide insight into the duration of post-concussive symptoms. At this time, very few studies have been published evaluating the relationship between these serum biomarkers and alterations to DTI metrics.     Methods:  In the present study, we examined the association between serum biomarkers NfL and tau to further understand the relationship between these biomarkers and neuroimaging findings seen with diffusion tensor imaging (DTI) after exposure to a sports-related concussive event.     Results:  Serum tau levels decreased significantly at the 24-48h post-injury time point compared to 6h post-injury. Serum tau levels then elevated significantly at the asymptomatic time point in comparison to the 24-48h post-injury time point. The serum tau level was significantly associated with higher mean diffusivity (MD) in the white-matter tracts. Serum NfL had minimal associations with white matter diffusion metrics.     Conclusion and Potential Impact:  This research serves to better inform future investigations into the relationship between DTI metrics and serum biomarkers in the context of mTBI and SRC. This information may contribute to the development of a simple bedside serum analysis with potential to offer tremendous insight into the comprehensive brain health of patients who are being evaluated for SRC, thereby streamlining the therapeutic process and providing more accessible healthcare to patients in locations where advanced imaging techniques are not readily accessible.  


Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 970
Author(s):  
Maedeh Khalilian ◽  
Kamran Kazemi ◽  
Mahshid Fouladivanda ◽  
Malek Makki ◽  
Mohammad Sadegh Helfroush ◽  
...  

The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm2) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.


Author(s):  
Eric L. Goldwaser ◽  
Joshua Chiappelli ◽  
Mark D. Kvarta ◽  
Xiaoming Du ◽  
Zachary B. Millman ◽  
...  

AbstractStress is implicated in psychosis etiology and exacerbation, but pathogenesis toward brain network alterations in schizophrenia remain unclear. White matter connects limbic and prefrontal regions responsible for stress response regulation, and white matter tissues are also vulnerable to glucocorticoid aberrancies. Using a novel psychological stressor task, we studied cortisol stress responses over time and white matter microstructural deficits in schizophrenia spectrum disorder (SSD). Cortisol was measured at baseline, 0-, 20-, and 40-min after distress induction by a psychological stressor task in 121 SSD patients and 117 healthy controls (HC). White matter microstructural integrity was measured by 64-direction diffusion tensor imaging. Fractional anisotropy (FA) in white matter tracts were related to cortisol responses and then compared to general patterns of white matter tract deficits in SSD identified by mega-analysis. Differences between 40-min post-stress and baseline, but not acute reactivity post-stress, was significantly elevated in SSD vs HC, time × diagnosis interaction F2.3,499.9 = 4.1, p = 0.013. All SSD white matter tracts were negatively associated with prolonged cortisol reactivity but all tracts were positively associated with prolonged cortisol reactivity in HC. Individual tracts most strongly associated with prolonged cortisol reactivity were also most impacted in schizophrenia in general as established by the largest schizophrenia white matter study (r = −0.56, p = 0.006). Challenged with psychological stress, SSD and HC mount similar cortisol responses, and impairments arise in the resolution timeframe. Prolonged cortisol elevations are associated with the white matter deficits in SSD, in a pattern previously associated with schizophrenia in general.


2017 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  

AbstractIn diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.


2019 ◽  
Author(s):  
Hannelore Aerts ◽  
Thijs Dhollander ◽  
Daniele Marinazzo

AbstractThe use of diffusion MRI (dMRI) for assisting in the planning of neurosurgery has become increasingly common practice, allowing to non-invasively map white matter pathways via tractography techniques. Limitations of earlier pipelines based on the diffusion tensor imaging (DTI) model have since been revealed and improvements were made possible by constrained spherical deconvolution (CSD) pipelines. CSD allows to resolve a full white matter (WM) fiber orientation distribution (FOD), which can describe so-called “crossing fibers”: complex local geometries of WM tracts, which DTI fails to model. This was found to have a profound impact on tractography results, with substantial implications for presurgical decision making and planning. More recently, CSD itself has been extended to allow for modeling of other tissue compartments in addition to the WM FOD, typically resulting in a 3-tissue CSD model. It seems likely this may improve the capability to resolve WM FODs in the presence of infiltrating tumor tissue. In this work, we evaluated the performance of 3-tissue CSD pipelines, with a focus on within-tumor tractography. We found that a technique named single-shell 3-tissue CSD (SS3T-CSD) successfully allowed tractography within infiltrating gliomas, without increasing existing single-shell dMRI acquisition requirements.


2004 ◽  
Vol 10 (2) ◽  
pp. 188-196 ◽  
Author(s):  
Emmanuelle Cassol ◽  
Jean-Philippe Ranjeva ◽  
Danielle Ibarrola ◽  
Claude Mékies ◽  
Claude Manelfe ◽  
...  

Our objectives were to determine the reproducibility of diffusion tensor imaging (DTI) in volunteers and to evaluate the ability of the method to monitor longitudinal changes occurring in the normal-appearing white matter (NAWM) of patients with multiple sclerosis (MS). DTI was performed three-mo nthly for one year in seven MS patients: three relapsing-remitting (RRMS), three secondary progressive (SPMS) and one relapsing SP. They were selected with a limited cerebral lesion load. Seven age- and sex-matched controls also underwent monthly examinations for three months. Diffusivity and anisotropy were quantified over the segmented whole supratentorial white matter, with the indices of trace (Tr) and fractional anisotropy (FA). Results obtained in volunteers show the reproducibility of the method. Patients had higher trace and lower anisotropy than matched controls (P B-0.0001). O ver the follow-up, both Tr and FA indicated a recovery after the acute phase in RRMS and a progressive shift towards abnormal values in SPMS. A lthough this result is not statistically significant, it suggests that DTI is sensitive to microscopic changes occurring in tissue of normal appearance in conventional images and could be useful for monitoring the course of the disease, even though it was unable to clearly distinguish between the various physiopathological processes involved.


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