Diffusion Tensor Imaging Measures Research Articles

NfL and GFAP in serum are associated with microstructural brain damage in progressive multiple sclerosis.

The potential of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) as biomarkers of disease activity and severity in progressive forms of multiple sclerosis (MS) is unclear. To investigate the relationship between serum concentrations of NfL, GFAP, and magnetic resonance imaging (MRI) in progressive MS. Serum concentrations of NfL and GFAP were measured in 32 healthy controls and 32 patients with progressive MS from whom clinical and MRI data including diffusion tensor imaging (DTI) were obtained during three years of follow-up. Serum concentrations of NfL and GFAP at follow-up were higher in progressive MS patients than in healthy controls and serum NfL correlated with the EDSS score. Decreasing fractional anisotropy (FA) in normal-appearing white matter (NAWM) correlated with worsening EDSS scores and higher serum NfL. Higher serum NfL and increasing T2 lesion volume correlated with worsening paced autitory serial addition test scores. In multivariable regression analyses with serum GFAP and NfL as independent factors and DTI measures of NAWM as dependent factors, we showed that high serum NfL at follow-up was independently associated with decreasing FA and increasing MD in NAWM. Moreover, we found that high serum GFAP was independently associated with decreasing MD in NAWM and with decreasing MD and increasing FA in cortical gray matter. Serum concentrations of NfL and GFAP are increased in progressive MS and are associated with distinct microstructural changes in NAWM and CGM.

Altered white matter organization and its correlations with executive functioning among adolescents with epilepsy.

Deficits in executive functions (EF) are a common comorbidity among adolescents with epilepsy. EF deficits were previously correlated with altered connectivity of the fronto-parietal and cingulo-opercular neural networks. The current study investigated white matter integrity in adolescents with epilepsy (n=29) relative to healthy controls (n=19). Participants completed questionnaires, neuropsychological testing, and brain magnetic resonance imaging (MRI) that included diffusion tensor imaging (DTI) sequences. On BRIEF parent-report questionnaires, adolescents with epilepsy demonstrated lower working memory and planning abilities than healthy controls. Among adolescents with epilepsy, DTI measurements revealed lower fractional anisotropy (FA) within the right superior longitudinal fasciculus, forceps minor, and the superior frontal segment of the corpus callosum, and higher FA in the left uncinate fasciculus, compared to healthy controls. Better working memory ability in the epilepsy group was associated with higher FA in the superior frontal segment of the corpus callosum. Only in healthy controls, working memory and planning were positively associated with FA values in the left UF, forceps minor and the superior frontal segment of the corpus callosum. The current study complements previous functional studies on the same cohort and suggests that EF impairments among adolescents with epilepsy may be related to the altered anatomical organization of white matter tracts. Combining structural and functional data could potentially enrich the neuropsychological assessment of executive functioning in adolescents with epilepsy.

Effect of number of diffusion encoding directions in neonatal diffusion tensor imaging using Tract-Based Spatial Statistical analysis.

Diffusion tensor imaging (DTI) has been used to study the developing brain in early childhood, infants and in utero studies. In infants, number of used diffusion encoding directions has traditionally been smaller in earlier studies down to the minimum of 6 orthogonal directions. Whereas the more recent studies often involve more directions, number of used directions remain an issue when acquisition time is optimized without compromising on data quality and in retrospective studies. Variability in the number of used directions may introduce bias and uncertainties to the DTI scalar estimates that affect cross-sectional and longitudinal study of the brain. We analysed DTI images of 133 neonates, each data having 54 directions after quality control, to evaluate the effect of number of diffusion weighting directions from 6 to 54 with interval of 6 to the DTI scalars with Tract-Based Spatial Statistics (TBSS) analysis. The TBSS analysis was applied to DTI scalar maps, and the mean region of interest (ROI) values were extracted using JHU atlas. We found significant bias in ROI mean values when only 6 directions were used (positive in fractional anisotropy [FA] and negative in fractional anisotropy [MD], axial diffusivity [AD] and fractional anisotropy [RD]), while when using 24 directions and above, the difference to scalar values calculated from 54 direction DTI was negligible. In repeated measures voxel-wise analysis, notable differences to 54 direction DTI were observed with 6, 12 and 18 directions. DTI measurements from data with at least 24 directions may be used in comparisons with DTI measurements from data with higher numbers of directions.

Plasma neurofilament light admission levels and development of axonal pathology in mild traumatic brain injury

BackgroundIt is known that blood levels of neurofilament light (NF-L) and diffusion-weighted magnetic resonance imaging (DW-MRI) are both associated with outcome of patients with mild traumatic brain injury (mTBI). Here, we sought to examine the association between admission levels of plasma NF-L and white matter (WM) integrity in post-acute stage DW-MRI in patients with mTBI.MethodsNinety-three patients with mTBI (GCS ≥ 13), blood sample for NF-L within 24 h of admission, and DW-MRI ≥ 90 days post-injury (median = 229) were included. Mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated from the skeletonized WM tracts of the whole brain. Outcome was assessed using the Extended Glasgow Outcome Scale (GOSE) at the time of imaging. Patients were divided into CT-positive and -negative, and complete (GOSE = 8) and incomplete recovery (GOSE < 8) groups.ResultsThe levels of NF-L and FA correlated negatively in the whole cohort (p = 0.002), in CT-positive patients (p = 0.016), and in those with incomplete recovery (p = 0.005). The same groups showed a positive correlation with mean MD, AD, and RD (p < 0.001—p = 0.011). In CT-negative patients or in patients with full recovery, significant correlations were not found.ConclusionIn patients with mTBI, the significant correlation between NF-L levels at admission and diffusion tensor imaging (DTI) measurements of diffuse axonal injury (DAI) over more than 3 months suggests that the early levels of plasma NF-L may associate with the presence of DAI at a later phase of TBI.

Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET

Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r=-0.55, p <0.001, df=31) but not CN (r=0.13, p=0.62, df=15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.

Cerebellar and cerebral white matter changes in Parkinson's disease with resting tremor.

Cerebellum modulates the amplitude of resting tremor in Parkinson's disease (PD) via cerebello-thalamo-cortical (CTC) circuit. Tremor-related white matter alterations have been identified in PD patients by pathological studies, but in vivo evidence is limited; the influence of such cerebellar white matter alterations on tremor-related brain network, including CTC circuit, is also unclear. In this study, we investigated the cerebral and cerebellar white matter alterations in PD patients with resting tremor using diffusion tensor imaging (DTI). In this study, 30 PD patients with resting tremor (PDWR), 26 PD patients without resting tremor (PDNR), and 30 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort were included. Tract-based spatial statistics (TBSS) and region of interest-based analyses were conducted to determine white matter difference. Correlation analysis between DTI measures and clinical characteristics was also performed. In the whole brain, TBSS and region of interest-based analyses identified higher fractional anisotropy (FA) value, lower mean diffusivity (MD) value, and lower radial diffusivity (RD) in multiple fibers. In the cerebellum, TBSS analysis revealed significantly higher FA value, decreased RD value as well as MD value in multiple cerebellar tracts including the inferior cerebellar peduncle (ICP) and middle cerebellar peduncle (MCP) when comparing the PDWR with HC, and higher FA value in the MCP when compared with PDNR. We identified better white matter integrity in the cerebrum and cerebellum in PDWR indicating a potential association between the cerebral and cerebellar white matter and resting tremor in PD.

Functional MRI and Diffusion Tensor Imaging in Migraine: A Review of Migraine Functional and White Matter Microstructural Changes.

Migraine is a complex and heterogenous disorder whose disease mechanisms remain disputed. This narrative review summarizes functional MRI (fMRI) and diffusion tensor imaging (DTI) findings and interprets their association with migraine symptoms and subtype to support and expand our current understanding of migraine pathophysiology. Our PubMed search evaluated and included fMRI and DTI studies involving comparisons between migraineurs vs healthy controls, migraineurs with vs without aura, and episodic vs chronic migraineurs. Migraineurs demonstrate changes in functional connectivity (FC) and regional activation in numerous pain-related networks depending on migraine phase, presence of aura, and chronicity. Changes to diffusion indices are observed in major cortical white matter tracts extending to the brainstem and cerebellum, more prominent in chronic migraine and associated with FC changes. Reported changes in FC and regional activation likely relate to pain processing and sensory hypersensitivities. Diffuse white matter microstructural changes in dysfunctional cortical pain and sensory pathways complement these functional differences. Interpretations of reported fMRI and DTI measure trends have not achieved a clear consensus due to inconsistencies in the migraine neuroimaging literature. Future fMRI and DTI studies should establish and implement a uniform methodology that reproduces existing results and directly compares migraineurs with different subtypes. Combined fMRI and DTI imaging may provide better pathophysiological explanations for nonspecific FC and white matter microstructural differences.

White matter microstructural perturbations after total sleep deprivation in depression.

Total sleep deprivation (TSD) transiently reverses depressive symptoms in a majority of patients with depression. How TSD modulates diffusion tensor imaging (DTI) measures of white matter (WM) microstructure, which may be linked with TSD's rapid antidepressant effects, remains uncharacterized. Patients with depression (N = 48, mean age = 33, 26 women) completed diffusion-weighted imaging and Hamilton Depression Rating (HDRS) and rumination scales before and after >24 h of TSD. Healthy controls (HC) (N = 53, 23 women) completed the same assessments at baseline, and after receiving TSD in a subset of HCs (N = 15). Tract based spatial statistics (TBSS) investigated voxelwise changes in fractional anisotropy (FA) across major WM pathways pre-to-post TSD in patients and HCs and between patients and HCs at baseline. Post hoc analyses tested for TSD effects for other diffusion metrics, and the relationships between change in diffusion measures with change in mood and rumination symptoms. Significant improvements in mood and rumination occurred in patients with depression (both p < 0.001), but not in HCs following TSD. Patients showed significant (p < 0.05, corrected) decreases in FA values in multiple WM tracts, including the body of the corpus callosum and anterior corona radiata post-TSD. Significant voxel-level changes in FA were not observed in HCs who received TSD (p > 0.05). However, differential effects of TSD between HCs and patients were found in the superior corona radiata, frontal WM and the posterior thalamic radiation (p < 0.05, corrected). A significant (p < 0.05) association between change in FA and axial diffusivity within the right superior corona radiata and improvement in rumination was found post-TSD in patients. Total sleep deprivation leads to rapid microstructural changes in WM pathways in patients with depression that are distinct from WM changes associated with TSD observed in HCs. WM tracts including the superior corona radiata and posterior thalamic radiation could be potential biomarkers of the rapid therapeutic effects of TSD. Changes in superior corona radiata FA, in particular, may relate to improvements in maladaptive rumination.

Direct jet coaxial electrospinning of axon-mimicking fibers for diffusion tensor imaging.

Hollow polymer microfibers with variable microstructural and hydrophilic properties were proposed as building elements to create axon-mimicking phantoms for validation of diffusion tensor imaging (DTI). The axon-mimicking microfibers were fabricated in a mm-thick 3D anisotropic fiber strip, by direct jet coaxial electrospinning of PCL/polysiloxane-based surfactant (PSi) mixture as shell and polyethylene oxide (PEO) as core. Hydrophilic PCL-PSi fiber strips were first obtained by carefully selecting appropriate solvents for the core and appropriate fiber collector rotating and transverse speeds. The porous cross-section and anisotropic orientation of axon-mimicking fibers were then quantitatively evaluated using two ImageJ plugins-nearest distance (ND) and directionality based on their scanning electron microscopy (SEM) images. Third, axon-mimicking phantom was constructed from PCL-PSi fiber strips with variable porous-section and fiber orientation and tested on a 3T clinical MR scanner. The relationship between DTI measurements (mean diffusivity [MD] and fractional anisotropy [FA]) of phantom samples and their pore size and fiber orientation was investigated. Two key microstructural parameters of axon-mimicking phantoms including normalized pore distance and dispersion of fiber orientation could well interpret the variations in DTI measurements. Two PCL-PSi phantom samples made from different regions of the same fiber strips were found to have similar MD and FA values, indicating that the direct jet coaxial electrospun fiber strips had consistent microstructure. More importantly, the MD and FA values of the developed axon-mimicking phantoms were mostly in the biologically relevant range.

Deep learning prediction of motor performance in stroke individuals using neuroimaging data

The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have been used as potential biomarkers of motor recovery, with limited accuracy up to date. To address this, the present study aimed to develop a deep learning model based on structural brain images obtained from stroke participants and healthy volunteers. The following inputs were used in a multi-channel 3D convolutional neural network (CNN) model: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps obtained from Diffusion Tensor Imaging (DTI) images, white and gray matter intensity values obtained from Magnetic Resonance Imaging, as well as demographic data (e.g., age, gender). Upper limb motor function was classified into “Poor” and “Good” categories. To assess the performance of the DL model, we compared it to more standard machine learning (ML) classifiers including k-nearest neighbor, support vector machines (SVM), Decision Trees, Random Forests, Ada Boosting, and Naïve Bayes, whereby the inputs of these classifiers were the features taken from the fully connected layer of the CNN model. The highest accuracy and area under the curve values were 0.92 and 0.92 for the 3D-CNN and 0.91 and 0.91 for the SVM, respectively. The multi-channel 3D-CNN with residual blocks and SVM supported by DL was more accurate than traditional ML methods to classify upper limb motor impairment in the stroke population. These results suggest that combining volumetric DTI maps and measures of white and gray matter integrity can improve the prediction of the degree of motor impairment after stroke. Identifying the potential of recovery early on after a stroke could promote the allocation of resources to optimize the functional independence of these individuals and their quality of life.

Unsupervised machine learning model to predict cognitive impairment in subcortical ischemic vascular disease.

It is challenging to predict which patients who meet criteria for subcortical ischemic vascular disease (SIVD) will ultimately progress to subcortical vascular cognitive impairment (SVCI). We collected clinical information, neuropsychological assessments, T1 imaging, diffusion tensor imaging, and resting-state functional magnetic resonance imaging from 83 patients with SVCI and 53 age-matched patients with SIVD without cognitive impairment. We built an unsupervised machine learning model to isolate patients with SVCI. The model was validated using multimodal data from an external cohort comprising 45 patients with SVCI and 32 patients with SIVD without cognitive impairment. The accuracy, sensitivity, and specificity of the unsupervised machine learning model were 86.03%, 79.52%, and 96.23% and 80.52%, 71.11%, and 93.75% for internal and external cohort, respectively. We developed an accurate and accessible clinical tool which requires only data from routine imaging to predict patients at risk of progressing from SIVD to SVCI. Our unsupervised machine learning model provides an accurate and accessible clinical tool to predict patients at risk of progressing from subcortical ischemic vascular disease (SIVD) to subcortical vascular cognitive impairment (SVCI) and requires only data from imaging routinely used during the diagnosis of suspected SVCI. The model yields good accuracy, sensitivity, and specificity and is portable to other cohorts and to clinical practice to distinguish patients with SIVD at risk for progressing to SVCI. The model combines assessment of diffusion tensor imaging and functional magnetic resonance imaging measures in patients with SVCI to analyze whether the "disconnection hypothesis" contributes to functional and structural changes and to the clinical presentation of SVCI.

Dimethyl fumarate treatment of primary progressive multiple sclerosis: results of an open-label extension study.

Dimethyl fumarate treatment is approved in Europe for patients with relapsing-remitting multiple sclerosis (MS) and in the US for relapsing forms of MS. We recently published the results of the first randomized placebo-controlled trial of 48 weeks of treatment with dimethyl fumarate or placebo in primary progressive MS (PPMS) (clinicaltrial.gov NCT02959658). The placebo-controlled phase of the trial did not meet its primary endpoint (reduction in cerebrospinal fluid concentrations of neurofilament light chain [NFL]). To investigate the effects of dimethyl fumarate treatment in the open-label extension phase of the trial (week 48-96), where all patients were treated with DMF. Reported data are from screening, week 48, and week 96 visits. Patients were clinically evaluated with Expanded Disability Status Scale (EDSS), 9-Hole Peg Test (9HPT), Timed 25-Foot Walk (T25FW) test, Symbol Digit Modalities Test (SDMT), California Verbal Learning Test, and Brief Visuospatial Memory-Revised. Serum NFL concentrations were measured by single-molecule array analysis. MRI was performed on a 3 tesla MRI scanner and included: new/enlarging lesions, volume of lesions, cortical grey matter, putamen, thalamus, and normal-appearing white matter, and additional diffusion tensor imaging and magnetization transfer ratio measures. Forty-two patients entered the open-label treatment phase, and 33 patients (61%) had complete data sets at week 96. The remaining 39% did not complete the trial and were not evaluated at week 96. We found no evidence of differences in clinical and MRI measures between patients initially treated with dimethyl fumarate and patients initially treated with placebo from baseline to week 48 and from week 48-96, where all patients were treated with dimethyl fumarate. Serum NFL concentrations remained stable in both groups over 96 weeks. Assessed with either EDSS, T25FW, or 9HPT at week 96, progression was observed for 14 patients (45%). Interestingly, another 15 patients (46%) had improvement in one or more of these domains. Applying a cut-off of 8 points, 2 (6%) patients worsened on SDMT, 25 (78%) did not change, and 5 (16%) improved. Dimethyl fumarate treatment showed no effects on neither clinical nor MRI outcomes or changes in serum concentrations of NFL. An expected number of patients showed evidence of progression on standard clinical scales; however, this was matched by an equal number of patients improving. The reasons for the physical improvement in an unexpectedly high proportion of patients must be addressed in future studies.

Diffusion Changes in Hippocampal Cingulum in Early Biologically Defined Alzheimer's Disease.

Diagnosis of Alzheimer's disease (AD) was recently shifted from clinical to biological construct to reflect underlying neuropathological status, where amyloid deposition designated patients to the Alzheimer's continuum, and additional tau positivity represented AD. To investigate white matter (WM) alteration in the brain of patients in the Alzheimer's continuum. A total of 236 subjects across the clinical and biological spectra of AD were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding five groups: A-T-cognitively normal (CN), A+T-CN, A+T+ CN, A+T+ mild cognitive impairment, and A+T+ AD. WM alteration was measured by diffusion tensor imaging (DTI). Group differences, correlation of DTI measures with amyloid and tau, and diagnostic performance of such measures were evaluated. Compared with A-T-CN, widespread WM alteration was observed in the Alzheimer's continuum, including hippocampal cingulum (CGH), cingulum of the cingulate gyrus, and uncinate fasciculus. Diffusion changes measured by regional mean fractional anisotropy (FA) in the bilateral CGH were first detected in the A+T+ CN group and associated with tau burden in the Alzheimer's continuum (p < 0.001). For discrimination between A+T+ CN and A-T-CN groups, CGH FA achieved accuracy, sensitivity, and specificity of 74%, 58%, and 78% for right CGH and 57%, 83%, and 47% respectively for left CGH. WM alteration is widespread in the Alzheimer's continuum. Diffusion alteration in CGH occurred early and was correlated with tau pathology, thus may be a promising biomarker in preclinical AD.

Diffusion tensor imaging and quantitative T2 mapping to monitor muscle recovery following hamstring injury.

MRI examinations are accurate for diagnosing sports-related acute hamstring injuries. However, sensitive imaging methods for assessing recovery of these injuries are lacking. Diffusion tensor imaging (DTI) and quantitative T2 (qT2) mapping have both shown promise for assessing recovery of muscle micro trauma and exercise effects. The purpose of this study was to explore the potential of DTI and qT2 mapping for monitoring the muscle recovery processes after acute hamstring injury. In this prospective study, athletes with an acute hamstring injury underwent a 3-T MRI examination of the injured and contralateral hamstrings including DTI and qT2 measurements at three time points: (1) within 1 week after sustaining the injury, (2) 2 weeks after time point 1, and (3) return to play (RTP). A linear mixed model was used for time-effect analysis and paired t-tests for the detection of differences between injured and uninjured muscles. Forty-one athletes (age 27.8 ± 7 years; two females and 39 males) were included. Mean RTP time was 50 (range 12-169) days. A significant time effect was found for mean diffusivity, radial diffusivity, and the second and third eigenvalues (p ≤ 0.001) in the injured muscles. Fractional anisotropy (p = 0.40), first eigenvalue (p = 0.02), and qT2 (p = 0.61) showed no significant time effect. All DTI indices, except for fractional anisotropy, were significantly elevated compared with control muscles right after the injury (p < 0.001). Values normalized during the recovery period, with no significant differences between control and injured muscles at RTP (p values ranged from 0.08 to 0.51). Mean qT2 relaxation times in injured muscles were not significantly elevated compared with control muscles at any time point (p > 0.04). In conclusion, DTI can be used to monitor recovery after an acute hamstring injury. Future work should explore the potential of DTI indices to predict RTP and recovery times in athletes after an acute strain injury.

Amnestik hafif kognitif bozuklukta beyaz cevher değişiklikleri: yolak tabanlı uzamsal istatistik çalışması

Purpose: To compare white matter (WM) structural alterations between the subjects with amnestic mild cognitive impairment (MCI) which is a transitional state to Alzheimer's Disease (AD) and healthy elderly controls.&#x0D; Methods: Diffusion tensor imaging (DTI) scans of 20 subjects with amnestic MCI and 20 healthy control groups who are matched by age, gender, and education with the MCI group between 2011 and 2016 were examined by in this retrospective study. WM structural integrity was analyzed using tract based spatial statistics (TBSS) for voxel-based differences in fractional anisotropy (FA) between the two groups. &#x0D; Results: Fractional anisotropy was found significantly lower in the forceps minor, the body and genu of the corpus callosum, the right anterior thalamic radiation, the right cingulum, the right inferior fronto-occipital fasciculus, the right superior longitudinal fasciculus, and the right superior corona radiata in the MCI group than the control group. &#x0D; Conclusion: TBSS analysis is a promising method to examine structural WM integrity. These findings suggested that the DTI measurements may be useful for the detection of preclinical changes in AD.

Baseline free water within the visual processing system predicts future psychosis in Parkinson disease.

As psychosis is associated with decreased quality of life, increased institutionalization, and mortality in Parkinson disease (PD), it is essential to identify individuals at risk for future psychosis. This longitudinal study aimed to investigate whether diffusion tensor imaging (DTI) metrics of white matter hold independent utility for predicting future psychosis in PD, and whether they could be combined with clinical predictors to improve the prognostication of PD psychosis. This study included 123 newly diagnosed PD patients collected in the Parkinson's Progression Markers Initiative. Tract-based spatial statistics were used to compare baseline DTI metrics between PD patients who developed psychosis and those who did not during follow-up. Binary logistic regression analyses were performed to identify the clinical and white matter markers predictive of psychosis. Among DTI measures, both higher baseline whole brain (odds ratio [OR] = 1.711, p= 0.016) free water (FW) and visual processing system (OR=1.680, p< 0.001) FW were associated with an increased risk of future psychosis. Baseline FW remained a significant indicator of future psychosis in PD after controlling for clinical predictors. Moreover, the accuracy of prediction of psychosis using clinical predictors alone (area under the curve [AUC] = 0.742, 95% confidence interval [CI] = 0.655-0.816) was significantly improved by the addition of the visual processing system FW (AUC=0.856, 95% CI=0.781-0.912; Delong method, p= 0.022). Baseline FW of the visual processing system incurs an independent risk of future psychosis in PD, thus providing an opportunity for multiple-modality marker models to include a white matter marker.

Differences in structural MRI and diffusion tensor imaging underlie visuomotor performance declines in older adults with an increased risk for Alzheimer's disease.

Visuomotor impairments have been demonstrated in preclinical AD in individuals with a positive family history of dementia and APOE e4 carriers. Previous behavioral findings have also reported sex-differences in performance of visuomotor tasks involving a visual feedback reversal. The current study investigated the relationship between grey and white matter changes and non-standard visuomotor performance, as well as the effects of APOE status, family history of dementia, and sex on these brain-behavior relationships. Older adults (n = 49) with no cognitive impairments completed non-standard visuomotor tasks involving a visual feedback reversal, plane-change, or combination of the two. Participants with a family history of dementia or who were APOE e4 carriers were considered at an increased risk for AD. T1-weighted anatomical scans were used to quantify grey matter volume and thickness, and diffusion tensor imaging measures were used to quantify white matter integrity. In APOE e4 carriers, grey and white matter structural measures were associated with visuomotor performance. Regression analyses showed that visuomotor deficits were predicted by lower grey matter thickness and volume in areas of the medial temporal lobe previously implicated in visuomotor control (entorhinal and parahippocampal cortices). This finding was replicated in the diffusion data, where regression analyses revealed that lower white matter integrity (lower FA, higher MD, higher RD, higher AxD) was a significant predictor of worse visuomotor performance in the forceps minor, forceps major, cingulum, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Some of these tracts overlap with those important for visuomotor integration, namely the forceps minor, forceps major, SLF, IFOF, and ILF. These findings suggest that measuring the dysfunction of brain networks underlying visuomotor control in early-stage AD may provide a novel behavioral target for dementia risk detection that is easily accessible, non-invasive, and cost-effective. The results also provide insight into the structural differences in inferior parietal lobule that may underlie previously reported sex-differences in performance of the visual feedback reversal task.

Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease.

The causes of the neurodegenerative processes in Alzheimer's disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole-brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid-beta (Aβ42 ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole-brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aβ42 alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aβ42 , phosphorylated tau protein (p-Tau) and total tau (t-Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p-Tau and t-Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early-stage disease and patients with Alzheimer's disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.

Microstructural mapping of dentate gyrus pathology in Alzheimer’s disease: A 16.4 Tesla MRI study

The dentate gyrus (DG) is an integral portion of the hippocampal formation, and it is composed of three layers. Quantitative magnetic resonance (MR) imaging has the capability to map brain tissue microstructural properties which can be exploited to investigate neurodegeneration in Alzheimer’s disease (AD). However, assessing subtle pathological changes within layers requires high resolution imaging and histological validation. In this study, we utilized a 16.4 Tesla scanner to acquire ex vivo multi-parameter quantitative MRI measures in human specimens across the layers of the DG. Using quantitative diffusion tensor imaging (DTI) and multi-parameter MR measurements acquired from AD (N = 4) and cognitively normal control (N = 6) tissues, we performed correlation analyses with histological measurements. Here, we found that quantitative MRI measures were significantly correlated with neurofilament and phosphorylated Tau density, suggesting sensitivity to layer-specific changes in the DG of AD tissues.

Differential age-associated brain atrophy and white matter changes among homeless and precariously housed individuals compared with the general population

BackgroundHomeless or precariously housed individuals live with poor health and experience premature mortality compared with the general population, yet little is known about age-related brain changes among these individuals. We...