Brain Diffusion Tensor Imaging Research Articles

Structural Changes in Brain White Matter Tracts Associated With Overactive Bladder Revealed by Diffusion Tensor Magnetic Resonance Imaging: Findings From a Symptoms of Lower Urinary Tract Dysfunction Research Network Cross-Sectional Case-Control Study.

Our objective was to investigate structural changes in brain white matter tracts using diffusion tensor imaging (DTI) in patients with overactive bladder (OAB). Treatment-seeking OAB patients and matched controls enrolled in the cross-sectional case-control LURN (Symptoms of Lower Urinary Tract Dysfunction Research Network) Neuroimaging Study received a brain DTI scan. Microstructural integrity of brain white matter was assessed using fractional anisotropy (FA) and mean diffusivity. OAB and urgency urinary incontinence (UUI) symptoms were assessed using the OAB Questionnaire Short-Form and International Consultation on Incontinence Questionnaire-Urinary Incontinence. The Lower Urinary Tract Symptoms Tool UUI questions and responses were correlated with FA values. Among 221 participants with evaluable DTI data, 146 had OAB (66 urinary urgency-only without UUI, 80 with UUI); 75 were controls. Compared with controls, participants with OAB showed decreased FA and increased mean diffusivity, representing greater microstructural abnormalities of brain white matter tracts among OAB participants. These abnormalities occurred in the corpus callosum, bilateral anterior thalamic radiation and superior longitudinal fasciculus tracts, and bilateral insula and parahippocampal region. Among participants with OAB, higher OAB Questionnaire Short-Form scores were associated with decreased FA in the left inferior fronto-occipital fasciculus, P < .0001. DTI differences between OAB and controls were driven by the urinary urgency-only (OAB-dry) but not the UUI (OAB-wet) subgroup. Abnormalities in microstructural integrity in specific brain white matter tracts were more frequent in OAB patients. More severe OAB symptoms were correlated with greater degree of microstructural abnormalities in brain white matter tracts in patients with OAB.

Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels.

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.

Non-local diffusion-based biomarkers in patients with cocaine use disorder

Cocaine use disorder (CUD) is widely known to result in neurological reconfiguration which can be observed via local diffusivity characteristics of the brain. These changes can be highly correlated while simultaneously variable across patients with different comorbidities or histories of substance use. This implies that more complex neuroimage analysis tools may be necessary to better detect specific biomarkers that vary across these dimensions. We investigated white and gray matter integrity using voxel-based diktiometry (VBD) on whole brain diffusion tensor images (DTI) across a database of CUD patients and healthy controls using a purely data-driven approach. These VBD maps reveal significant cortical and subcortical differences that are indicative of these neural modifications including the insula, cerebellum, ventricles, thalamo-cortical radiations, and corpus callosum bundles. In order to disambiguate these results and investigate the heterogeneity of CUD, the VBD maps have been decomposed into five decorrelated biomarkers: one in the region surrounding the left insula, one implicating the corpus callosum, two concentrated in the left cerebellum, and the last concerning a proximal region of the interhemispheric fissure which serve as potential biomarkers playing a role in CUD. These decorrelated biomarkers have themselves been correlated with consumption patterns and psychiatric and borderline personality disorder scores on the CUD patient group. This preliminary approach to using machine learning techniques to both detect and disambiguate complex non-linear patterns shows promise for better understanding complex and heterogeneous disorders such as CUD.

Modeling brain network flexibility in networks of coupled oscillators: a feasibility study

Modeling the functionality of the human brain is a major goal in neuroscience for which many powerful methodologies have been developed over the last decade. The impact of working memory and the associated brain regions on the brain dynamics is of particular interest due to their connection with many functions and malfunctions in the brain. In this context, the concept of brain flexibility has been developed for the characterization of brain functionality. We discuss emergence of brain flexibility that is commonly measured by the identification of changes in the cluster structure of co-active brain regions. We provide evidence that brain flexibility can be modeled by a system of coupled FitzHugh-Nagumo oscillators where the network structure is obtained from human brain Diffusion Tensor Imaging (DTI). Additionally, we propose a straightforward and computationally efficient alternative macroscopic measure, which is derived from the Pearson distance of functional brain matrices. This metric exhibits similarities to the established patterns of brain template flexibility that have been observed in prior investigations. Furthermore, we explore the significance of the brain’s network structure and the strength of connections between network nodes or brain regions associated with working memory in the observation of patterns in networks flexibility. This work enriches our understanding of the interplay between the structure and function of dynamic brain networks and proposes a modeling strategy to study brain flexibility.

Abstract WMP24: Association of the Mediterranean Diet With White Matter Integrity Among Hispanics/Latinos. Results From the Study of Latinos-Investigation of Neurocognitive Aging-MRI Ancillary Study

Objective: Investigate the association between adherence to the Mediterranean Diet (MeDi) and white matter (WM) integrity among Hispanic/Latino adults. Background: High adherence to a MeDi was associated with better cognitive performance and decreased memory decline among Hispanic or Latino adults. Methods: We included 2,342 participants from the Study of Latinos-Investigation of Neurocognitive Aging-MRI Ancillary Study. Participants completed 24-hour dietary recalls at baseline (2008-2011) which were used to calculate a MeDi score (MeDiS). Brain MRI and diffusion tensor images were collected between 2018 and 2022 on a 3T MRI scanner using a standardized protocol. WM integrity was ascertained using WM hyperintensity (WMH) volume, fractional anisotropy (FA), and peak skeletonized mean diffusivity (PSMD). WMH volumes were residualized for total cranial volume and Ln-transformed prior to analysis. The association of MRI outcomes with MeDiS was investigated using weighted linear regression analysis with complex survey design adjusting for age, sex, sociodemographic characteristics, and Framingham Risk Score. Results: Mean age (95% CI) at MRI scan was 64.03 (63.1 - 64.9) and 44% were males. Mean MeDiS was 5.05 (4.92 - 5.17). In our fully adjusted model, increasing MeDiS was associated with decreased LnWMH volume (β=-0.07, 95% CI -0.10 to -0.03) and PSMD (β=-0.004, 95% CI -0.006 to -0.002), and increasing FA (β=0.002, 95% CI 0.001 to 0.003). When participants were grouped by background, the results were retained for all the groups except for Puerto Ricans and Mexicans. Conclusions: Among diverse Hispanic/Latino adults, high MeDi adherence was associated with preserved WM integrity. Since our preliminary results were retained after adjustment for Framingham Risk Score, this suggests that vascular mechanisms do not fully account for the observed associations. In addition, our results highlight that the results obtained in selected cohorts may not be generalizable to other Hispanic/Latino heritages. A culturally tailored MeDi may preserve brain health among Hispanic/Latino adults.

Brain multi-contrast, multi-atlas segmentation of diffusion tensor imaging and ensemble learning automatically diagnose late-life depression

We investigated the potential of machine learning for diagnostic classification in late-life major depression based on an advanced whole brain white matter segmentation framework. Twenty-six late-life depression and 12 never depressed individuals aged > 55 years, matched for age, MMSE, and education underwent brain diffusion tensor imaging and a multi-contrast, multi-atlas segmentation in MRIcloud. Fractional anisotropy volume, mean fractional anisotropy, trace, axial and radial diffusivity (RD) extracted from 146 white matter parcels for each subject were used to train and test the AdaBoost classifier using stratified 12-fold cross validation. Performance was evaluated using various measures. The statistical power of the classifier was assessed using label permutation test. Statistical analysis did not yield significant differences in DTI measures between the groups. The classifier achieved a balanced accuracy of 71% and an Area Under the Receiver Operator Characteristic Curve (ROC-AUC) of 0.81 by trace, and a balanced accuracy of 70% and a ROC-AUC of 0.80 by RD, in limbic, cortico-basal ganglia-thalamo-cortical loop, brainstem, external and internal capsules, callosal and cerebellar structures. Both indices shared important structures for classification, while fornix was the most important structure for classification by both indices. The classifier proved statistically significant, as trace and RD ROC-AUC scores after permutation were lower than those obtained with the actual data (P = 0.022 and P = 0.024, respectively). Similar results were obtained with the Gradient Boosting classifier, whereas the RBF-kernel Support Vector Machine with k-best feature selection did not exceed the chance level. Finally, AdaBoost significantly predicted the class using all features together. Limitations are discussed. The results encourage further investigation of the implemented methods for computer aided diagnostics and anatomically informed therapeutics.

Cardiovascular effects on high-resolution 3D multi-shot diffusion MRI of the rhesus macaque brain

Abstract The monkey brain represents a key research model thanks to its strong homologies with the humans, but diffusion-MRI (dMRI) performed at millimeter-level resolution using clinical scanners and pulse-sequences cannot take full advantage of this. Cardiovascular effects on 3D multi-shot Echo-Planar Imaging (3D-msEPI) dMRI were characterized at submillimetric resolution by comparing triggered and non-triggered diffusion-weighted (DW)-images and diffusion tensor imaging (DTI) maps. We also investigated the value of 3D-msEPI with cardiovascular-triggering to achieve dMRI of the anesthetized macaque brain with high resolution previously restricted to ex-vivo brains. Eight DW-images with voxel-size = 0.5 × 0.5 × 1 mm3 and b = 1500 s/mm2 were collected at 3 Tesla from two macaques using triggered and then non-triggered 3D-msEPI. Statistical analysis by mixed models was used to compare signal-to-noise ratio (SNR) and ghost-to-signal ratio (GSR) of DW-images with and without triggering. Brain DTI with isotropic-resolution of 0.4 mm and b = 1000 s/mm2 was also collected in three macaques with triggered 3D-msEPI and reapplied without triggering in one. Cardiovascular pulsations induce inter-shot phase-errors with non-linear spatial dependency on DW-images, resulting in ghost-artifacts and signal loss particularly in the brainstem, thalamus, and cerebellum. Cardiovascular-triggering proved effective in addressing these, recovering SNR in white and gray matter (all p &amp;lt; 0.0001), and reducing GSR from 16.5 ± 10% to 4.7 ± 4.2% on DW-images (p &amp;lt; 0.0001). Triggered 3D-msEPI provided DTI-maps with the unprecedented spatial-resolution of 0.4 mm, enabling several substructures of the macaque brain to be discerned and thus analyzed in vivo. The value of cardiovascular-triggering in maintaining DTI-map sharpness and guaranteeing accurate tractography results in the brainstem, thalamus, and cerebellum was also demonstrated. In conclusion, this work highlights the effects of cardiovascular pulsations on brain 3D-dMRI and the value of triggered 3D-msEPI to provide high-quality diffusion-MRI of the anesthetized macaque brain. For routine studies, 3D-msEPI must be coupled with appropriate techniques to reduce acquisition duration.

Diffusion tensor imaging and voxel-based morphometry in differentiating multiple sclerosis and its mimics

BackgroundThe discrimination between multiple sclerosis (MS) and other white matter lesions in adults is still problematic as multiple diseases have similar clinical and radiological findings, especially at the disease onset. This case–control study aimed to evaluate the efficacy of diffusion tensor imaging (DTI) and brain morphometry in the differentiation between adult MS and its magnetic resonance imaging (MRI) mimics.MethodsFifty-eight patients (49 women and 9 men; mean age 35.74 ± 11.86 years, range 18–50 years) with clinically suspected MS and age- and sex-matched fifteen healthy subjects were included. All study subjects underwent MRI using 3D FLAIR, 3D T1 MPRAGE, axial T2WI fast spin echo, and DTI sequences. The included patients were classified into MS and mimics groups according to MC Donald’s criteria 2017. Image post-processing using the region of interest (ROI) analysis for DTI parameters and automated voxel brain morphometry and segmentation was done for all study groups. Statistical comparison between the two patient groups and between them and the control group was performed regarding DTI indices (fractional anisotropy [FA], mean diffusivity [MD], and relative anisotropy [RA]) and brain morphometry parameters (including white matter volume (WMV), grey matter volume (GMV), cerebrospinal fluid volume (CSFV), T2 lesion load and deep grey matter volume).ResultsA statistically significant difference was observed between the MD, FA, and RA values of the patients and control groups. The MD values were significantly higher in the MS than in its mimics with a cut-off value of > 1.058 × 10−3 mm2/s (p < 0.001). Compared to the mimics group, the MS patients showed significantly lower WMV (33.31 ± 4.40 versus 35.71 ± 4.58; p = 0.047) and higher CSFV (16.38 ± 5.93 versus 13.06 ± 3.09; p = 0.012) with no significant difference regarding the GMV.ConclusionsMD analysis of DTI, WMV, and CSFV are useful quantitative measurements in confirming the diagnosis of MS and differentiating it from its imaging mimics.

White matter fiber integrity and structural brain network topology: implications for balance function in postischemic stroke patients.

Previous studies have suggested that ischemic stroke can result in white matter fiber injury and modifications in the structural brain network. However, the relationship with balance function scores remains insufficiently explored. Therefore, this study aims to explore the alterations in the microstructural properties of brain white matter and the topological characteristics of the structural brain network in postischemic stroke patients and their potential correlations with balance function. We enrolled 21 postischemic stroke patients and 21 age, sex, and education-matched healthy controls (HC). All participants underwent balance function assessment and brain diffusion tensor imaging. Tract-based spatial statistics (TBSS) were used to compare the fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity of white matter fibers between the two groups. The white matter structural brain network was constructed based on the automated anatomical labeling atlas, and we conducted a graph theory-based analysis of its topological properties, including global network properties and local node properties. Additionally, the correlation between the significant structural differences and balance function score was analyzed. The TBSS results showed that in comparison to the HC, postischemic stroke patients exhibited extensive damage to their whole-brain white matter fiber tracts (P < 0.05). Graph theory analysis showed that in comparison to the HC, postischemic stroke patients exhibited statistically significant reductions in the values of global efficiency, local efficiency, and clustering coefficient, as well as an increase in characteristic path length (P < 0.05). In addition, the degree centrality and nodal efficiency of some nodes in postischemic stroke patients were significantly reduced (P < 0.05). The white matter fibers of the entire brain in postischemic stroke patients are extensively damaged, and the topological properties of the structural brain network are altered, which are closely related to balance function. This study is helpful in further understanding the neural mechanism of balance function after ischemic stroke from the white matter fiber and structural brain network topological properties.

Characterizing microstructural development in the fetal brain using diffusion MRI from 23 to 36weeks of gestation.

We utilized motion-corrected diffusion tensor imaging (DTI) to evaluate microstructural changes in healthy fetal brains during the late second and third trimesters. Data were derived from fetal magnetic resonance imaging scans conducted as part of a prospective study spanning from 2013 March to 2019 May. The study included 44 fetuses between the gestational ages (GAs) of 23 and 36weeks. We reconstructed fetal brain DTI using a motion-tracked slice-to-volume registration framework. Images were segmented into 14 regions of interest (ROIs) through label propagation using a fetal DTI atlas, with expert refinement. Statistical analysis involved assessing changes in fractional anisotropy (FA) and mean diffusivity (MD) throughout gestation using mixed-effects models, and identifying points of change in trajectory for ROIs with nonlinear trends. Results showed significant GA-related changes in FA and MD in all ROIs except in the thalamus' FA and corpus callosum's MD. Hemispheric asymmetries were found in the FA of the periventricular white matter (pvWM), intermediate zone, and subplate and in the MD of the ganglionic eminence and pvWM. This study provides valuable insight into the normal patterns of development of MD and FA in the fetal brain. These changes are closely linked with cytoarchitectonic changes and display indications of early functional specialization.

Anti-seizure medication response and the glymphatic system in patients with focal epilepsy.

We aimed to evaluate (i) glymphatic system function in patients with focal epilepsy in comparison with healthy controls, and (ii) the association between anti-seizure medication (ASM) response and glymphatic system function by using diffusion tensor image analysis along the perivascular space (DTI-ALPS). We retrospectively enrolled 100 patients with focal epilepsy who had normal brain magnetic resonance imaging (MRI) findings, and classified them as "poor" or "good" ASM responders according to their seizure control at the time of brain MRI. We also included 79 age- and sex-matched healthy controls. All patients and healthy controls underwent conventional brain MRI and diffusion tensor imaging. The DTI-ALPS index was calculated using the DSI studio program. Of the 100 patients with focal epilepsy, 38 and 62 were poor and good ASM responders, respectively. The DTI-ALPS index differed significantly between patients with focal epilepsy and healthy controls and was significantly lower in patients with focal epilepsy (1.55 vs. 1.70; p < 0.001). The DTI-ALPS index also differed significantly according to ASM response and was lower in poor ASM responders (1.48 vs. 1.59; p = 0.047). Furthermore, the DTI-ALPS index was negatively correlated with age (r = -0.234, p = 0.019) and duration of epilepsy (r = -0.240, p = 0.016) in patients with focal epilepsy. Our study is the first to identify, in focal epilepsy patients, a greater reduction in glymphatic system function among poor ASM responders compared to good responders. To confirm our results, further prospective multicenter studies with large sample sizes are needed.

Disturbed white matter integrity on diffusion tensor imaging in young children with epilepsy

To evaluate whether abnormalities in white matter (WM) integrity are present in young children with epilepsy. Twelve children (3-6 years old) with epilepsy and six matched healthy controls were recruited for brain diffusion tensor imaging (DTI). Track-based spatial statistics (TBSS) was used to analyse and compare DTI indices of mean diffusivity (MD), fractional anisotropy (FA), axial and radial diffusivity (AD/RD) between patients and controls, and correlations between clinical variables and DTI parameters were analysed. Compared with controls, patients showed increased FA in the left superior corona radiata and increased AD in the bilateral superior corona radiata. In children with generalised epilepsy, FA was increased in the left external capsule, while AD was decreased in the body of the corpus callosum, the left external capsule and the left superior longitudinal fasciculus. In those with focal epilepsy, FA was increased in the genu and body of the corpus callosum, and RD was decreased in the genu of the corpus callosum and left external capsule. Compared with partial epilepsy, generalised epilepsy was associated with increased FA in the right anterior corona radiata and decreased RD in the right anterior corona radiata and the genu and body of the corpus callosum. No significant correlations were observed between clinical variables and DTI parameters. The results of this study indicate that the microstructure of the white matter is disturbed by epileptic discharges and a compensatory response occurs during early brain development.

Neuroimmune Mechanisms of Opioid Use Disorder and Recovery: Translatability to Human Studies, and Future Research Directions.

Opioid use disorder (OUD) is a major current cause of morbidity and mortality. Long-term exposure to short-acting opioids (MOP-r agonists such as heroin or fentanyl) results in complex pathophysiological changes to neuroimmune and neuroinflammatory functions, affected in part by peripheral mechanisms (e.g., cytokines in blood), and by neuroendocrine systems such as the hypothalamic-pituitary-adrenal (HPA) stress axis. There are important findings from preclinical models, but their role in the trajectory and outcomes of OUD in humans is not well understood. The goal of this narrative review is to examine available data on immune and inflammatory functions in persons with OUD, and to identify major areas for future research. Peripheral blood biomarker studies revealed a pro-inflammatory state in persons with OUD in withdrawal or early abstinence, consistent with available postmortem brain studies (which show glial activation) and diffusion tensor imaging studies (indicating white matter disruptions), with gradual abstinence-associated recovery. The mechanistic roles of these neuroimmune and neuroinflammatory changes in the trajectory of OUD (including recovery and medication management) cannot be examined practically with postmortem data. Collection of longitudinal data in larger-scale human cohorts would allow examination of these mechanisms associated with OUD stage and progression. Given the heterogeneity in presentation of OUD, a precision medicine approach integrating multi-omic peripheral biomarkers and comprehensive phenotyping, including neuroimaging, can be beneficial in risk stratification, and individually optimized selection of interventions for individuals who will benefit, and assessments under refractory therapy.

Age-related changes in the healthy adult visual pathway: evidence from diffusion tensor imaging with fixel-based analysis.

Fixel-based analysis (FBA) is anew method that overcomes the technical limitations of diffusion tensor imaging (DTI) by enabling the characterization of multiple fiber populations within avoxel, and provides biologically meaningful indicators. This study aimed to explore age-related changes in the visual pathway in healthy adults and to observe differences in imaging quality between data collected using different b‑values. In this prospective cross-sectional study, brain DTI scans which were collected with more than six uniformly distributed gradient directions and higher b‑values (up to 2000 s/mm2) than traditional DTI were performed in 72healthy adults across the adult lifespan (20-79years). After image preprocessing, FBA was used to process the dataset. At the same time, conventional DTI metrics were also calculated. Pearson's correlation analysis showed that DTI parameters of white matter (optic nerve, optic chiasma, optic tract, and optic radiation) in the optic pathway were correlated with age. FA values were negatively correlated with age, while MD/AD/RD showed apositive correlation (P < 0.05). FBA showed that the index including FD/FC/FDC tended to decline with age (P < 0.05). Linear regression analysis showed alinear relationship between DTI metrics of the dataset collected by b‑values of 1000 and 2000 s/mm2 (P < 0.05). FBA provides auseful method to assess age-related changes in the visual pathway, which is sensitive to diffusion. In addition, the b‑value influences DTI parameters and signal-to-noise ratio of the image.

Anxiety adds the risk of cognitive progression and is associated with axon/synapse degeneration among cognitively unimpaired older adults.

Mental symptoms have been shown to be associated with dementia. As the most common neuropsychiatric disorder, it is unclear whether and why anxiety increases the risk of cognitive progression in elderly. The aim of this study was to investigate the longitudinal effects of anxiety on cognitive impairment in non-dementia elderly and to explore the underlying biological processes using multi-omics including microarray-based transcriptomics, mass spectrometry-based proteomics and metabolomics, cerebrospinal fluid (CSF) biochemical markers, and brain diffusion tensor imaging (DTI). The Alzheimer's Disease Neuroimaging Initiative (ADNI), Chinese Longitudinal Healthy Longevity Survey (CLHLS) and Shanghai Mental Health Centre (SMHC) cohorts were included. Anxiety was found to increase the risk of subsequent cognitive progression in the ADNI, and a similar result was observed in the CLHLS cohort. Enrichment analysis indicated activated axon/synapse pathways and suppressed mitochondrial pathways in anxiety, the former confirmed by deviations in frontolimbic tract morphology and altered levels of axon/synapse markers, and the latter supported by decreased levels of carnitine metabolites. Mediation analysis revealed that anxiety's effect on the longitudinal cognition was mediated by brain tau burden. Correlations of mitochondria-related expressed genes with axon/synapse proteins, carnitine metabolites, and cognitive changes were found. This study provides cross-validated epidemiological and biological evidence that anxiety is a risk factor for cognitive progression in non-dementia elderly, and that axon/synapse damage in the context of energy metabolism imbalance may contribute to this phenomenon. The National Natural Science Foundation of China (82271607, 81971682, and 81830059) for data analysis and data collection.

Diffusion tensor imaging techniques show that parkin gene S/N167 polymorphism is responsible for extensive brain white matter damage in patients with Parkinson's disease

ObjectiveTo explore the influence of disease and genetic factors on the white matter microstructure in patients with PD. The white matter microstructural changes in the substantia nigra-striatum system were detected by diffusion tensor imaging (DTI) using the region of interest (ROI) and diffusion tensor tracer (DTT) methods. MethodsPatients with primary Parkinson's disease (PD) without a family history of PD were selected and divided into PD-G/G and PD-G/A groups according to their parkin S/N167 polymorphism. Control groups matched for age, sex, and gene type (G/G and G/A) were also included. Three-dimensional brain volume imaging (3D-BRAVO) and DTI were performed. The microstructural changes in the substantia nigra-striatum system were evaluated by the ROI and DTT methods. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Hoehn-Yahr (H–Y) staging, and the third part of the Unified Parkinson's Disease Rating (UPDRS-III) scales evaluated the cognitive and motor function impairment in patients with PD. Independent samples t-test compared normally-distributed data, and the Wilcoxon rank sum test compared measurement or categorical non-normally distributed data. Multiple regression analysis was used to analyze the correlation between various DTI indicators and the MMSE, MoCA, UPDRS-III, and H–Y scores in the PD-G/G and PD-G/A groups. P < 0.05 was considered statistically significant. ResultsThe white matter microstructural changes in the nigrostriatal pathway differed significantly between the PD or PD-G/A and the control group (P < 0.05)The ROI method showed that the left globus pallidus radial diffusivity (RD) value was negatively correlated with the MMSE score (r = −0.404, P = 0.040), and the left substantia nigra (LSN) fractional anisotropy (FA) value was positively correlated with the MoCA score (r = 0.405, P = 0.040) and negatively with the H–Y stage (r = −0.479, P = 0.013).The DTT method showed that the MMSE score was positively correlated with the right substantia nigra (RSN) FA value (r = 0.592, P = 0.001) and negatively with its RD value (r = −0.439, P = 0.025). The H–Y grade was negatively correlated with the number of fibers in the RSN (r = −0.406, P = 0.040). The UPDRS-Ⅲ score was positively correlated with the mean diffusivity (r = 0.420, P = 0.033) and RD (r = 0.396, P = 0.045) values of the LSN, and the AD value of the RSN (r = 0.439, P = 0.025). ConclusionThe DTI technique detected extensive white matter fiber damage in patients with PD, primarily in those with the G/A genotype, that led to motor and cognitivesymptoms.

Visual alertness and brain diffusion tensor imaging at term age predict neurocognitive development at preschool age in extremely preterm-born children.

Cognitive development is characterized by the structural and functional maturation of the brain. Diffusion-weighted magnetic resonance imaging (dMRI) provides methods of investigating the brain structure and connectivity and their correlations with the neurocognitive outcome. Our aim was to examine the relationship between early visual abilities, brain white matter structures, and the later neurocognitive outcome. This study included 20 infants who were born before 28 gestational weeks and followed until the age of 6.5 years. At term age, visual alertness was evaluated and dMRI was used to investigate the brain white matter structure using fractional anisotropy (FA) in tract-based spatial statistics analysis. The JHU DTI white matter atlas was used to locate the findings. The neuropsychological assessment was used to assess neurocognitive performance at 6.5 years. Optimal visual alertness at term age was significantly associated with better visuospatial processing (p<.05), sensorimotor functioning (p<.05), and social perception (p<.05) at 6.5 years of age. Optimal visual alertness related to higher FA values, and further, the FA values positively correlated with the neurocognitive outcome. The tract-based spatial differences in FA values were detected between children with optimal and nonoptimal visual alertness according to performance at 6.5 years. We provide neurobiological evidence for the global and tract-based spatial differences in the white matter maturation between extremely preterm children with optimal and nonoptimal visual alertness at term age and a link between white matter maturation, visual alertness and the neurocognitive outcome at 6.5 years proposing that early visual function is a building block for the later neurocognitive development.

Visual networks: Electric brain stimulation and diffusion tensor imaging

ObjectiveThe present study investigated the networks of visual functional areas using electric brain stimulation (EBS) and diffusion tensor imaging (DTI). MethodsThirteen patients with intractable focal epilepsy in which visual functional areas were identified by EBS were enrolled. An electric stimulation at 50Hz was applied to electrodes during several tasks. DTI was used to identify subcortical fibers originating from the visual functional areas identified by EBS. ResultThe electrical stimulation induced three types of visual symptoms: visual illusions (change of vision), visual hallucinations (appearance of a new object), and blurred vision. Visual illusions were associated with stimulation of lateral temporo-parieto-occipital areas, and visual hallucinations with stimulation of lateral/basal temporal areas, the occipital lobe and the precuneus. Stimulus intensities eliciting visual illusions were significantly higher than those for visual hallucinations. Tractography revealed that the superior fronto-occipital fasciculus was associated with visual illusions and the middle longitudinal fasciculus with visual hallucinations, and both symptoms shared several subcortical fibers such as the vertical occipital fasciculus, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, inferior longitudinal fasciculus, optic radiations, and commissural fibers. ConclusionThe present study revealed the characteristic cortical regions and networks of visual functional areas. The results obtained provide information on human visual functions and are a practical guide for electrical cortical stimulation.

Brain diffusion tensor imaging reveals altered connections and networks in epilepsy patients.

Accumulating evidence shows that epilepsy is a disease caused by brain network dysfunction. This study explored changes in brain network structure in epilepsy patients based on graph analysis of diffusion tensor imaging data. The brain structure networks of 42 healthy control individuals and 26 epilepsy patients were constructed. Using graph theory analysis, global and local network topology parameters of the brain structure network were calculated, and changes in global and local characteristics of the brain network in epilepsy patients were quantitatively analyzed. Compared with the healthy control group, the epilepsy patient group showed lower global efficiency, local efficiency, clustering coefficient, and a longer shortest path length. Both healthy control individuals and epilepsy patients showed small-world attributes, with no significant difference between groups. The epilepsy patient group showed lower nodal local efficiency and nodal clustering coefficient in the right olfactory cortex and right rectus and lower nodal degree centrality in the right olfactory cortex and the left paracentral lobular compared with the healthy control group. In addition, the epilepsy patient group showed a smaller fiber number of edges in specific regions of the frontal lobe, temporal lobe, and default mode network, indicating reduced connection strength. Epilepsy patients exhibited lower global and local brain network properties as well as reduced white matter fiber connectivity in key brain regions. These findings further support the idea that epilepsy is a brain network disorder.

A Systematic Review of Magnetic Resonance Imaging Studies in Perinatally HIV-Infected Individuals.

Over the past few years, neuroimaging studies have been performed in young adults with perinatally acquired HIV (PHIV) to study the impact of HIV infection on the central nervous system (CNS), but no recent review have been published. This review aims to identify brain areas where PHIV eems to have greater impact taking into account demographic, behavioral, and clinical characteristics in PHIV infected patients. For this purpose, PubMed and Medline searches were carried out which included studies from 2010 to April 2020. We performed a systematic review and included 26 articles using structural (brain morphometry and diffusion tensor imaging) and functional magnetic resonance imaging methods involving 1182 PHIV-infected participants. Ample evidence has been provided of HIV effects on underlying brain structure. However, information recorded in the studies is commonly incomplete and results sometimes contradictory. In addition to future improvements and dissemination of tools for the developing brain MRI processing and analysis, the inclusion of data related to HIV infection itself (including clinical and immunovirological characteristics as well as detailed information about antiretroviral treatment such as age at ART initiation) may be of vital importance to the better understanding of the impact of the disease on CNS.