White matter integrity in mild cognitive impairment: a tract-based spatial statistics study

Characterization of local white matter microstructural alterations in Alzheimer's disease: A reproducible study

Alzheimer's disease (AD) is a neurodegenerative disease with a close association with microstructural alterations in white matter (WM). Current studies lack the characterization and further validation of specific regions in WM fiber tracts in AD. This study subdivided fiber tracts into multiple fiber clusters on the basis of automated fiber clustering and performed quantitative analysis along the fiber clusters to identify local WM microstructural alterations in AD. Diffusion tensor imaging data from a public dataset (53 patients with AD and 70 healthy controls [HCs]) and a clinical dataset (27 patients with AD and 19 HCs) were included for mutual validation. Whole-brain tractograms were automatically subdivided into 800 clusters through the automatic fiber clustering approach. Then, 100 segments were divided along the clusters, and the diffusion properties of each segment were calculated. Results showed that patients with AD had significantly lower fraction anisotropy (FA) and significantly higher mean diffusivity (MD) in some regions of the fiber clusters in the cingulum bundle, uncinate fasciculus, external capsule, and corpus callosum than HCs. Importantly, these changes were reproducible across the two datasets. Correlation analysis revealed a positive correlation between FA and Mini-Mental State Examination (MMSE) scores and a negative correlation between MD and MMSE in these clusters. The accuracy of the constructed classifier reached 89.76% with an area under the curve of 0.93. This finding indicates that this study can effectively identify local WM microstructural changes in AD and provides new insight into the analysis and diagnosis of WM abnormalities in patients with AD.

Mediating role of right superior corona microstructural changes in linking attentional control and trait anxiety among youth with childhood maltreatment

This study explores the neural correlates between attentional control and trait anxiety among youth with a history of childhood maltreatment. Using diffusion tensor imaging, we investigated the microstructural integrity of brain white matter, particularly focusing on the right superior corona radiata (SCA-R). A total of 173 university students with experiences of childhood maltreatment underwent behavioral assessments using the Attentional Control Scale and trait anxiety measurements via the Spielberger State-Trait Anxiety Inventory. Our analysis found significant correlations between fractional anisotropy values in the SCA-R and trait anxiety levels, controlled for age and sex. Notably, SCA-R fractional anisotropy values partially mediated the relationship between attentional control and trait anxiety, suggesting a potential pathway through which attentional control could mitigate trait anxiety. These insights highlight attentional control as a potential mitigating factor against trait anxiety, particularly noting the partial mediation role of the SCA-R. Importantly, this study is descriptive and correlative, highlighting associations rather than causal relationships among the variables studied. These findings enhance our understanding of the neural mechanisms underlying anxiety in individuals with a history of childhood maltreatment.

Neuropathological characteristics of abnormal white matter functional signaling in adolescents with major depression

BACKGROUND

Major depression disorder (MDD) constitutes a significant mental health concern. Epidemiological surveys indicate that the lifetime prevalence of depression in adolescents is much higher than that in adults, with a corresponding increased risk of suicide. In studying brain dysfunction associated with MDD in adole-scents, research on brain white matter (WM) is sparse. Some researchers even mistakenly regard the signals generated by the WM as noise points. In fact, studies have shown that WM exhibits similar blood oxygen level-dependent signal fluctuations. The alterations in WM signals and their relationship with disease severity in adolescents with MDD remain unclear.

AIM

To explore potential abnormalities in WM functional signals in adolescents with MDD.

METHODS

This study involved 48 adolescent patients with MDD and 31 healthy controls (HC). All participants were assessed using the Patient Health Questionnaire-9 Scale and the mini international neuropsychiatric interview (MINI) suicide inventory. In addition, a Siemens Skyra 3.0T magnetic resonance scanner was used to obtain the subjects' image data. The DPABI software was utilized to calculate the WM signal of the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity, followed by a two-sample t-test between the MDD and HC groups. Independent component analysis (ICA) was also used to evaluate the WM functional signal. Pearson's correlation was performed to assess the relationship between statistical test results and clinical scales.

RESULTS

Compared to HC, individuals with MDD demonstrated a decrease in the fALFF of WM in the corpus callosum body, left posterior limb of the internal capsule, right superior corona radiata, and bilateral posterior corona radiata [P < 0.001, family-wise error (FWE) voxel correction]. The regional homogeneity of WM increased in the right posterior limb of internal capsule and left superior corona radiata, and decreased in the left superior longitudinal fasciculus (P < 0.001, FWE voxel correction). The ICA results of WM overlapped with those of regional homo-geneity. The fALFF of WM signal in the left posterior limb of the internal capsule was negatively correlated with the MINI suicide scale (P = 0.026, r = -0.32), and the right posterior corona radiata was also negatively correlated with the MINI suicide scale (P = 0.047, r = -0.288).

CONCLUSION

Adolescents with MDD involves changes in WM functional signals, and these differences in brain regions may increase the risk of suicide.

White matter alterations in mild cognitive impairment revealed by meta-analysis of diffusion tensor imaging using tract-based spatial statistics

The neuropathological mechanism of mild cognitive impairment (MCI) remains unclarified. Diffusion tensor imaging (DTI) studies revealed white matter (WM) microarchitecture alterations in MCI, but consistent findings and conclusions have not yet been drawn. The present coordinate-based meta-analysis (CBMA) of tract-based spatial statistics (TBSS) studies aimed to identify the most prominent and robust WM abnormalities in patients with MCI. A systematic search of relevant studies was conducted through January 2022 to identify TBSS studies comparing fractional anisotropy (FA) between MCI patients and healthy controls (HC). We used the seed-based d mapping (SDM) software to achieve the CBMA and analyze regional FA alterations in MCI. Meta-regression analysis was subsequently applied to explore the potential associations between clinical variables and FA changes. MCI patients demonstrated significantly decreased FA in widely distributed areas in the corpus callosum (CC), including the genu, body, and splenium of the CC, as well as one cluster in the left striatum. FA in the body of the CC and in three clusters in the splenium of the CC was negatively associated with the mean age. Additionally, FA in the genu of the CC and in three clusters in the splenium of the CC had negative correlations with the MMSE scores. Disrupted integrities of the CC and left striatum might play vital roles in the process of cognitive decline. These findings enhanced our understanding of the neural mechanism underlying WM neurodegeneration in MCI and provided perspectives for the early detection and intervention of dementia.Registration number: CRD42022235716.

TBSS++: A novel computational method for Tract-Based Spatial Statistics

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. One of the most common computations in dMRI involves cross-subject tract-specific analysis, whereby dMRI-derived biomarkers are compared between cohorts of subjects. The accuracy and reliability of these studies hinges on the ability to compare precisely the same white matter tracts across subjects. This is an intricate and error-prone computation. Existing computational methods such as Tract-Based Spatial Statistics (TBSS) suffer from a host of shortcomings and limitations that can seriously undermine the validity of the results. We present a new computational framework that overcomes the limitations of existing methods via (i) accurate segmentation of the tracts, and (ii) precise registration of data from different subjects/scans. The registration is based on fiber orientation distributions. To further improve the alignment of cross-subject data, we create detailed atlases of white matter tracts. These atlases serve as an unbiased reference space where the data from all subjects is registered for comparison. Extensive evaluations show that, compared with TBSS, our proposed framework offers significantly higher reproducibility and robustness to data perturbations. Our method promises a drastic improvement in accuracy and reproducibility of cross-subject dMRI studies that are routinely used in neuroscience and medical research.

Alteration of Visuospatial System as an Early Marker of Cognitive Decline: A Double-Center Neuroimaging Study

Amnestic-type mild cognitive impairment (a-MCI) represents the prodromal phase of Alzheimer's disease associated with a high conversion rate to dementia and serves as a potential golden period for interventions. In our study, we analyzed the role of visuospatial (VS) functions and networks in the recognition of a-MCI. We examined 78 participants (32 patients and 46 controls) in a double-center arrangement using neuropsychology, structural, and resting-state functional MRI. We found that imaging of the lateral temporal areas showed strong discriminating power since in patients only the temporal pole (F = 5.26, p = 0.034) and superior temporal gyrus (F = 8.04, p < 0.001) showed reduced cortical thickness. We demonstrated significant differences between controls and patients in various neuropsychological results; however, analysis of cognitive subdomains revealed that the largest difference was presented in VS skills (F = 8.32, p < 0.001). Functional connectivity analysis of VS network showed that patients had weaker connectivity between the left and right frontotemporal areas, while stronger local connectivity was presented between the left frontotemporal structures (FWE corrected p < 0.05). Our results highlight the remarkable potential of examining the VS system in the early detection of cognitive decline. Since resting-state setting of functional MRI simplifies the possible automatization of data analysis, detection of VS system alterations might provide a non-invasive biomarker of a-MCI.

Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis

While mild cognitive impairment (MCI) has been classified into amnestic MCI (aMCI) and nonamnestic MCI (naMCI), the neuropathological bases of these two subtypes remain elusive. Here, we performed a systematic review and meta-analysis to determine the subtype specificity of neuroimaging abnormalities in MCI and to identify neural features that may differ between aMCI and naMCI. We synthesized 50 studies that used common neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, to compare brain atrophy, white matter abnormalities, cortical thinning, cerebral hypometabolism, amyloid/tau deposition, or other features among aMCI, naMCI, and normal cognition. Compared with normal cognition, aMCI shows diverse neuroimaging abnormalities of large effect sizes. In contrast, naMCI exhibits restricted abnormalities of small effect sizes. Some features, including medial temporal lobe atrophy and white matter abnormalities, are shared by the two MCI subtypes. Overall, brain abnormalities are worse, if not similar, in aMCI than in naMCI. The only neuroimaging abnormality specific to aMCI is increased amyloid burden; no feature specific to naMCI was found. Taken together, our findings have elucidated the neuropathological changes that occur in aMCI and naMCI. Clarifying the neuroimaging profiles of aMCI and naMCI can improve the early identification, differentiation, and intervention of prodromal dementia.

Accelerating Structural Degeneration in Temporal Regions and Their Effects on Cognition in Aging of MCI Patients

Age is the major risk factor for Alzheimer's disease (AD) and for mild cognitive impairment (MCI). However, there is limited evidence about MCI-specific aging-related simultaneous changes of the brain structure and their impact on cognition. We analyzed the brain imaging data from 269 subjects (97 MCI patients and 172 cognitively normal [CN] elderly) using voxel-based morphometry and tract-based spatial statistics procedures to explore the special structural pattern during aging. We found that the patients with MCI showed accelerated age-related reductions in gray matter volume in the left planum temporale, thalamus, and posterior cingulate gyrus. The similar age×group interaction effect was found in the fractional anisotropy of the bilateral parahippocampal cingulum white matter tract, which connects the temporal regions. Importantly, the age-related temporal gray matter and white matter alterations were more significantly related to performance in memory and attention tasks in MCI patients. The accelerated degeneration patterns in the brain structure provide evidence for different neural mechanisms underlying aging in MCI patients. Temporal structural degeneration may serve as a potential imaging marker for distinguishing the progression of the preclinical AD stage from normal aging.

Multicenter Tract-Based Analysis of Microstructural Lesions within the Alzheimer's Disease Spectrum: Association with Amyloid Pathology and Diagnostic Usefulness

Diffusion changes as determined by diffusion tensor imaging are potential indicators of microstructural lesions in people with mild cognitive impairment (MCI), prodromal Alzheimer’s disease (AD), and AD dementia. Here we extended the scope of analysis toward subjective cognitive complaints as a pre-MCI at risk stage of AD. In a cohort of 271 participants of the prospective DELCODE study, including 93 healthy controls and 98 subjective cognitive decline (SCD), 45 MCI, and 35 AD dementia cases, we found reductions of fiber tract integrity in limbic and association fiber tracts in MCI and AD dementia compared with controls in a tract-based analysis (p < 0.05, family wise error corrected). In contrast, people with SCD showed spatially restricted white matter alterations only for the mode of anisotropy and only at an uncorrected level of significance. DTI parameters yielded a high cross-validated diagnostic accuracy of almost 80% for the clinical diagnosis of MCI and the discrimination of Aβ positive MCI cases from Aβ negative controls. In contrast, DTI parameters reached only random level accuracy for the discrimination between Aβ positive SCD and control cases from Aβ negative controls. These findings suggest that in prodromal stages of AD, such as in Aβ positive MCI, multicenter DTI with prospectively harmonized acquisition parameters yields diagnostic accuracy meeting the criteria for a useful biomarker. In contrast, automated tract-based analysis of DTI parameters is not useful for the identification of preclinical AD, including Aβ positive SCD and control cases.

Resting state functional connectivity abnormalities and delayed recall performance in patients with amnestic mild cognitive impairment

Amnestic Mild Cognitive Impairment (aMCI) represents the transition between healthy aging and Alzheimer's dementia (AD) wherein gradual impairment of cognitive abilities, especially memory sets in. Impairment in episodic memory, especially delayed recall, is a hallmark of AD and therefore, patients with aMCI with more severe impairment in episodic memory are considered to be at greater risk of imminent conversion to AD. Brain structural and functional abnormalities were examined by comparing gray matter volumes, white matter micro-structural integrity and resting state functional connectivity (rsFC), between patients with aMCI (n = 46) having lower vs. higher episodic memory delayed recall (EM-DR) performance scores, correcting the influences of age, sex, number of years of formal education and total brain volumes using voxel-based morphometry, whole-brain tract based spatial statistics and dual regression analysis respectively. 'Low' performers (n = 27) when compared to 'high' performers (n = 19) showed significantly increased rsFC in the dorsal attention network (DAN) and central executive network (CEN) in the absence of demonstrable gray matter volumetric or white matter micro-structural integrity differences at family-wise error (FWE) corrected (p < 0.05) significance threshold. Follow-up data available for 38 (low performers = 22; high performers = 16) of the above 46 subjects (82.60% follow-up rate) over a median follow-up period of 24.5 months revealed that 7 subjects (18.42%) had converted to dementia. These converted subjects included 5 of the 22 low performers (22.72%) and 2 of the 16 high performers (12.5%) within the follow-up sample (n = 38). The results of the study indicate that imminent conversion of aMCI to dementia is higher in low performers in comparison to high performers, which may be characterized by increased rsFC in task positive networks, viz., DAN and CEN, as opposed to gray or white matter structural changes. This finding, therefore, might be considered as a prognostic indicator of progression from aMCI to dementia.

Dissecting the Fornix in Basic Memory Processes and Neuropsychiatric Disease: A Review

Background: The fornix is the primary axonal tract of the hippocampus, connecting it to modulatory subcortical structures. This review reveals that fornix damage causes cognitive deficits that closely mirror those resulting from hippocampal lesions. Methods: We reviewed the literature on the fornix, spanning non-human animal lesion research, clinical case studies of human patients with fornix damage, as well as diffusion-weighted imaging (DWI) work that evaluates fornix microstructure in vivo. Results: The fornix is essential for memory formation because it serves as the conduit for theta rhythms and acetylcholine, as well as providing mnemonic representations to deep brain structures that guide motivated behavior, such as when and where to eat. In rodents and non-human primates, fornix lesions lead to deficits in conditioning, reversal learning, and navigation. In humans, damage to the fornix manifests as anterograde amnesia. DWI research reveals that the fornix plays a key role in mild cognitive impairment and Alzheimer's Disease, and can potentially predict conversion from the former to the latter. Emerging DWI findings link perturbations in this structure to schizophrenia, mood disorders, and eating disorders. Cutting-edge research has investigated how deep brain stimulation of the fornix can potentially attenuate memory loss, control epileptic seizures, and even improve mood. Conclusions: The fornix is essential to a fully functioning memory system and is implicated in nearly all neurological functions that rely on the hippocampus. Future research needs to use optimized DWI methods to study the fornix in vivo, which we discuss, given the difficult nature of fornix reconstruction. Impact Statement The fornix is a white matter tract that connects the hippocampus to several subcortical brain regions and is pivotal for episodic memory functioning. Functionally, the fornix transmits essential neurotransmitters, as well as theta rhythms, to the hippocampus. In addition, it is the conduit by which memories guide decisions. The fornix is biomedically important because lesions to this tract result in irreversible anterograde amnesia. Research using in vivo imaging methods has linked fornix pathology to cognitive aging, mild cognitive impairment, psychosis, epilepsy, and, importantly, Alzheimer's Disease.

Local White Matter Fiber Clustering Differentiates Parkinson's Disease Diagnoses

Scans without evidence of dopaminergic deficit (SWEDD) patients are often misdiagnosed with Parkinson's disease (PD) but have normal dopamine transporter scans. We hypothesised that white matter tracts associated with motor and cognition functions may be affected differently by SWEDD and PD. Automatically annotated fibre clustering (AAFC) is a novel clustering method based on diffusion magnetic resonance imaging (dMRI) tractography that enables highly robust reconstruction of white matter tracts that are composed of corresponding clusters. This study aimed to investigate the white matter properties in the subdivisions of white matter tracts among SWEDD and PD groups. We applied AAFC to identify white matter tracts related to motion and cognition functions in the dataset consisting of SWEDD (n = 22), PD (n = 30) and normal control (NC) (n = 30). Then, we resampled 200 nodes along fibres of cluster, and the diffusion metric values corresponding to each node were calculated and used for comparison. Compared with NC, PD showed significant difference (p < 0.05) in two clusters in thalamo-frontal (TF), one cluster in thalamo-parietal (TP) and one cluster in thalamo-occipital (TO), whereas SWEDD presented no significant difference. Three clusters in cingulum bundle (CB) commonly exhibited significant differences in PD versus SWEDD and NC versus SWEDD. The support vector machine classifier achieved high accuracies in PD-NC, PD-SWEDD and NC-SWEDD classifications. This outcome validated these local white matter differences were useful to separate the three groups. These results suggest that PD exerts more significant effects on thalamo tracts than SWEDD, and unique microstructural changes occur in CB tract in SWEDD.

Tractography of the external capsule and cognition: A diffusion MRI study of cholinergic fibers

INTRODUCTION

White matter changes (WMC) in the cholinergic tracts contribute to executive dysfunction in the context of cognitive aging. WMC in the external capsule have been associated with executive dysfunction. The objectives of this study were to: 1) Characterize the lateral cholinergic tracts (LCT) and the superior longitudinal fasciculus (SLF). 2) Evaluate the association between diffusion measures within those tracts and cognitive performance.

METHODS

Neuropsychological testing and high angular resolution diffusion imaging (HARDI) of 34 healthy elderly participants was done, followed by anatomically constrained probabilistic tractography reconstruction robust to crossing fibers. The external capsule was manually segmented on a mean T1 image then merged with an atlas, allowing extraction of the LCT. Diffusion tensor imaging (DTI) and HARDI-based measures were obtained.

RESULTS

Correlations between diffusion measures in the LCT and the time of completion of Stroop (left LCT radial and medial diffusivity), the Symbol Search score (right LCT apparent fiber density) and the motor part of Trail-B (left LCT axial and radial diffusivity) were observed. Correlations were also found with diffusion measures in the SLF. WMC burden was low, and no correlation was found with diffusion measures or cognitive performance.

DISCUSSION

DTI and HARDI, with isolation of strategic white matter tracts for cognitive functions, represent complimentary tools to better understand the complex process of brain aging.

Diffusion tensor imaging of white matter degeneration in early stage of Alzheimer's disease: a review

Object: Alzheimer's disease is a progressive, irreversible neurodegenerative disorder associated with brain alterations. Diffusion tensor imaging (DTI) has contributed to identify degeneration in white matter cortical microstructural that can be considered an early and specific biomarker for Alzheimer's disease. This review aimed to provide a summary of DTI studies on white matter damage in Alzheimer's disease.Methods: On PubMed, Web of Science and Scopus databases, we reviewed the studies that used DTI for assessing fractional anisotropy in neurofiber tracts involved in Alzheimer's Disease progression: fornix, the cingulum, uncinate fasciculus, superior and inferior longitudinal fasciculus and corpus callosum. We included nine studies that met search criteria.Results: The results showed decreased fractional anisotropy value in mild cognitive impairment (MCI) patients. White matter diffusivity changes were associated with the progression of Alzheimer's disease.Conclusion: Microstructural alterations of the limbic and cortico-cortical tracts could be potential biomarkers for early diagnosis in preclinical disease phase.

White matter integrity is associated with gait impairment and falls in mild cognitive impairment. Results from the gait and brain study

BACKGROUND

Mild Cognitive Impairment (MCI) is an intermediate state between normal cognition and dementia that is associated with twice the risk of falls. It is unknown whether white matter integrity (WMI) is associated with increased risk of falls in MCI. The purpose of this study was to evaluate if early changes in WMI were associated with gait impairment and falls.

METHODS

Forty-three participants with MCI from the Gait and Brain Study underwent standardized assessment of cognition, gait performance under single and dual-task conditions (walking while talking), and WMI using 3 Tesla diffusion tensor imaging (DTI). Macro-structural imaging characteristics (white and grey matter morphology) as well as microstructural WMI parameters were examined for associations with falls and gait performance. Significantly associated WM tracts were then used to test the interplay between WMI and history of falls, after adjusting for other important covariates.

RESULTS

Multiple WM tracts (corpus callosum, forceps minor, and the left inferior fronto-occipital fasciculus) were significantly associated with history of falls and lower dual-task gait performance. A multivariable regression model showed that fall history was associated with the radial diffusivity in the forceps minor, even after adjusting for education, sex, BMI, MMSE scores, comorbidities, gait velocity and WMH volume as covariates.

CONCLUSIONS

Multiple WM tracts that are known to be involved in executive and visuospatial functions were preferentially affected in MCI individuals with history of falls. Our preliminary findings support the notion that WMI in key brain regions may increase risk of falls in older adults with MCI.

Close-Range Blast Exposure Is Associated with Altered White Matter Integrity in Apolipoprotein ɛ4 Carriers

Evidence suggests that blast exposure has profound negative consequences for the health of the human brain, and that it may confer risk for the development of neurodegenerative diseases such as chronic traumatic encephalopathy and Alzheimer's disease (AD). Although the molecular mechanisms linking blast exposure to subsequent neurodegeneration is an active focus of research, recent studies suggest that genetic risk for AD may elevate the risk of neurodegeneration following traumatic brain injury (TBI). However, it is currently unknown if blast exposure also interacts with AD risk to promote neurodegeneration. In this study we examined whether apolipoprotein (APOE) ɛ4, a well-known genetic risk factor for AD, influenced the relationship between blast exposure and white matter integrity in a cohort of 200 Iraq and Afghanistan war veterans. Analyses revealed a significant interaction between close-range blast exposure (CBE) (close range being within 10 m) and APOE ɛ4 carrier status in predicting white matter abnormalities, measured by a voxelwise cluster-based method that captures spatial heterogeneity in white matter disruptions. This interaction remained significant after controlling for TBI, pointing to the specificity of CBE and APOE in white matter disruptions. Further, among veteran ɛ4 carriers exposed to close-range blast, we observed a positive association between the number of CBEs and the number of white matter abnormalities. These results raise the possibility that CBE interacts with AD genetic influences on neuropathological processes such as the degradation of white matter integrity.

Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification

Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the generalizability of MRI-based classification probability scores to detect MCI on an individual basis within a general population. To determine classification probability scores, an AD, mild-AD, and moderate-AD detection model were created with anatomical and diffusion MRI measures calculated from a clinical Alzheimer's Disease (AD) cohort and subsequently applied to a population-based cohort with 48 MCI and 617 normal aging subjects. Each model's ability to detect MCI was quantified using area under the receiver operating characteristic curve (AUC) and compared with an MCI detection model trained and applied to the population-based cohort. The AD-model and mild-AD identified MCI from controls better than chance level (AUC = 0.600, p = 0.025; AUC = 0.619, p = 0.008). In contrast, the moderate-AD-model was not able to separate MCI from normal aging (AUC = 0.567, p = 0.147). The MCI-model was able to separate MCI from controls better than chance (p = 0.014) with mean AUC values comparable with the AD-model (AUC = 0.611, p = 1.0). Within our population-based cohort, classification models detected MCI better than chance. Nevertheless, classification performance rates were moderate and may be insufficient to facilitate robust MRI-based MCI detection on an individual basis. Our data indicate that multiparametric MRI-based classification algorithms, that are effective in clinical cohorts, may not straightforwardly translate to applications in a general population.

Abnormal dynamic functional connectivity and brain states in Alzheimer's diseases: functional near-infrared spectroscopy study

Communication within the brain is highly dynamic. Alzheimer's disease (AD) exhibits dynamic progression corresponding to a decline in memory and cognition. However, little is known of whether brain dynamics are disrupted in AD and its prodromal stage, mild cognitive impairment (MCI). For our study, we acquired high sampling rate functional near-infrared spectroscopy imaging data at rest from the entire cortex of 23 patients with AD dementia, 25 patients with amnestic mild cognitive impairment (aMCI), and 30 age-matched healthy controls (HCs). Sliding-window correlation and k-means clustering analyses were used to construct dynamic functional connectivity (FC) maps for each participant. We discovered that the brain's dynamic FC variability strength ( Q ) significantly increased in both aMCI and AD group as compared to HCs. Using the Q value as a measurement, the classification performance exhibited a good power in differentiating aMCI [area under the curve ( AUC = 82.5 % )] or AD ( AUC = 86.4 % ) from HCs. Furthermore, we identified two abnormal brain FC states in the AD group, of which the occurrence frequency ( F ) exhibited a significant decrease for the first-level FC state (state 1) and a significant increase for the second-level FC state (state 2). We also found that the abnormal F in these two states significantly correlated with the cognitive impairment in patients. These findings provide the first evidence to demonstrate the disruptions of dynamic brain connectivity in aMCI and AD and extend the traditional static (i.e., time-averaged) FC findings in the disease (i.e., disconnection syndrome) and thus provide insights into understanding the pathophysiological mechanisms occurring in aMCI and AD.

Cerebrospinal fluid biomarkers of neurofibrillary tangles and synaptic dysfunction are associated with longitudinal decline in white matter connectivity: A multi-resolution graph analysis

In addition to the development of beta amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) involves the loss of connecting structures including degeneration of myelinated axons and synaptic connections. However, the extent to which white matter tracts change longitudinally, particularly in the asymptomatic, preclinical stage of AD, remains poorly characterized. In this study we used a novel graph wavelet algorithm to determine the extent to which microstructural brain changes evolve in concert with the development of AD neuropathology as observed using CSF biomarkers. A total of 118 participants with at least two diffusion tensor imaging (DTI) scans and one lumbar puncture for CSF were selected from two observational and longitudinally followed cohorts. CSF was assayed for pathology specific to AD (Aβ42 and phosphorylated-tau), neurodegeneration (total-tau), axonal degeneration (neurofilament light chain protein; NFL), and synaptic degeneration (neurogranin). Tractography was performed on DTI scans to obtain structural connectivity networks with 160 nodes where the nodes correspond to specific brain regions of interest (ROIs) and their connections were defined by DTI metrics (i.e., fractional anisotropy (FA) and mean diffusivity (MD)). For the analysis, we adopted a multi-resolution graph wavelet technique called Wavelet Connectivity Signature (WaCS) which derives higher order representations from DTI metrics at each brain connection. Our statistical analysis showed interactions between the CSF measures and the MRI time interval, such that elevated CSF biomarkers and longer time were associated with greater longitudinal changes in white matter microstructure (decreasing FA and increasing MD). Specifically, we detected a total of 17 fiber tracts whose WaCS representations showed an association between longitudinal decline in white matter microstructure and both CSF p-tau and neurogranin. While development of neurofibrillary tangles and synaptic degeneration are cortical phenomena, the results show that they are also associated with degeneration of underlying white matter tracts, a process which may eventually play a role in the development of cognitive decline and dementia.

Strategic infarct location for post-stroke cognitive impairment: A multivariate lesion-symptom mapping study

Lesion location is an important determinant for post-stroke cognitive impairment. Although several 'strategic' brain regions have previously been identified, a comprehensive map of strategic brain regions for post-stroke cognitive impairment is lacking due to limitations in sample size and methodology. We aimed to determine strategic brain regions for post-stroke cognitive impairment by applying multivariate lesion-symptom mapping in a large cohort of 410 acute ischemic stroke patients. Montreal Cognitive Assessment at three to six months after stroke was used to assess global cognitive functioning and cognitive domains (memory, language, attention, executive and visuospatial function). The relation between infarct location and cognition was assessed in multivariate analyses at the voxel-level and the level of regions of interest using support vector regression. These two assumption-free analyses consistently identified the left angular gyrus, left basal ganglia structures and the white matter around the left basal ganglia as strategic structures for global cognitive impairment after stroke. A strategic network involving several overlapping and domain-specific cortical and subcortical structures was identified for each of the cognitive domains. Future studies should aim to develop even more comprehensive infarct location-based models for post-stroke cognitive impairment through multicenter studies including thousands of patients.

Intrinsic functional connectivity alterations in cognitively intact elderly APOE ε4 carriers measured by eigenvector centrality mapping are related to cognition and CSF biomarkers: a preliminary study

Apolipoprotein E (APOE) ε4 allele is the best established genetic risk factor for sporadic Alzheimer's disease (AD). However, there is a need to understand the effects of this genotype on the brain by simultaneously assessing intrinsic brain network and cerebral spinal fluid (CSF) biomarkers changes in healthy older ε4 carriers. Thirteen cognitively intact, elderly APOE ε4 carriers and 22 ε3 homozygotes were included in the present study. Eigenvector centrality mapping (ECM) was used to identify brain network hub organization based on resting-state functional MRI (rsfMRI). We evaluated comprehensive cognitive ability and tested levels of Aβ_1-42, total-tau (t-tau) and phosphorylated-tau (p-tau₁₈₁) in CSF. Comparisons of ECM between two groups were conducted, followed by correlations analyses between EC values with significant group differences and cognitive ability/CSF biomarkers. APOE ε4 carriers showed significantly decreased EC values in left medial temporal lobe (MTL), left lingual gyrus (LG) and increased EC values in left middle frontal gyrus (MFG) as compared to non-carriers. Correlation analysis demonstrated that left LG EC value correlated with Rey Auditory Verbal Learning Test total learning (RAVLT, r = 0.57, p < 0.05) and t-tau level (r = -0.57, p < 0.05), while left MFG EC values correlated with log-transformed Trail-Making Test B (TMT-B, r = -0.67, p < 0.05) in APOE ε4 carriers. This study suggests the APOE ε4 allele contributes to disruption of brain connectedness in certain functional nodes, which may result from neuronal death caused by toxicity of neurofibrillary tangles.

Faulty Adaptation to Repeated Face-Name Associative Pairs in Mild Cognitive Impairment is Predictive of Cognitive Decline

OBJECTIVE

We examined BOLD (Blood-Oxygen-Level Dependent) activity reduction upon stimuli repetition of face-name pairs in older adults with amnestic (aMCI) and non-amnestic (naMCI) mild cognitive impairment diagnosed using a comprehensive actuarial method, and relationships between activity reduction and behavioral indices.

METHOD

Twenty-nine cognitively healthy older adults (CHs) and 20 with MCI (n = 12 aMCI; n = 8 naMCI) underwent functional MRI event-related imaging, a comprehensive neuropsychological battery, and 1-year follow-up exam. During scanning, participants were shown face-name pairs 1-3 times and administered a post-scan recognition task.

RESULTS

The MCI group demonstrated less activity reduction upon repetition of face-name pairs within the MTL and other regions compared to CHs. Less activity reduction was associated with poorer Time 1 neuropsychological performance for the CH group and poorer post-scan recognition performance for the MCI group. Less activity reduction was related to poorer neuropsychological performance at Time 2 in the MCI group. Within MCIs, those with aMCI demonstrated less activity reduction upon repetition of face-name pairs than those with naMCI.

CONCLUSIONS

Distinct patterns of brain activity were identified in the MCI group compared to CHs, and aMCI compared to naMCI. Activated regions were not restricted to traditional memory circuitry, implicating a wider network of regions involved in the encoding of associative tasks. Findings add support to the hypothesis that lack of reduced BOLD activity reflects "faulty adaptation" to repeated stimuli and that reduction in activity represents successful encoding processes. They also provide further support for use of the face-name paradigm as a marker of prodromal Alzheimer's disease, and method to distinguish between MCI subtypes.

What can DTI tell about early cognitive impairment? - Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging

Mild cognitive impairment (MCI) gained a lot of interest recently, especially that the conversion rate to Alzheimer Disease (AD) in the amnestic subtype (aMCI) is higher than in the non-amnestic subtype (naMCI). We aimed to determine whether and how diffusion-weighted MRI (DWI) using the diffusion tensor model (DTI) can differentiate MCI subtypes from healthy subjects. High resolution 3D T1W and DWI images of patients (aMCI, n = 18; naMCI, n = 20; according to Petersen criteria) and controls (n = 27) were acquired at 3T and processed using ExploreDTI and SPM. Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) were performed with ANCOVA; MD was higher in aMCI compared to controls or naMCI in several grey and white matter (GM, WM) regions (especially in the temporal pole and the inferior temporal lobes), while FA was lower in WM ROI-s (e.g. left Cingulum). Moreover, significant correlations were identified between verbal fluency, visual and verbal memory performance and DTI metrics. Logistic regression showed that measuring FA of the crus of fornix along GM volumetry improves the discrimination of aMCI from naMCI. Additional information from DWI/DTI aids preclinical detection of AD and may help detecting early non-Alzheimer type dementia, too.

Associations of carotid arterial compliance and white matter diffusion metrics during midlife: modulation by sex

Sex differences in cerebral white matter (WM) aging have been debated extensively over the past 2 decades without unequivocal resolution. We aimed to determine if the effects of age and arterial stiffness on WM microstructure differ between sexes. Artery elasticity via carotid artery compliance (CAC) and WM diffusion metrics via diffusion tensor image-derived fractional anisotropy (FA) and mean diffusivity (MD) were measured in 155 (87 females) middle-aged (40-62 years) adults. Males demonstrated poorer water diffusion metrics in WM than women in the corpus callosum body, cingulum, and cingulum (hippocampal). Age and CAC had greater effects on WM water diffusion in males than females in midlife independent of education and cardiovascular risk factors. Sex-moderated age (cingulum FA, cingulum [hippocampal] MD, and uncinate MD, all p < 0.05) and CAC (cingulum FA, p < 0.05) related reductions in regional WM diffusion metrics. CAC mediated age-related associations in regional WM diffusion metrics (cingulum FA, cingulum MD, superior corona radiata MD, and uncinate MD, all p < 0.05) in males but not in females. Age and CAC were associated with WM diffusion metrics independent of cardiovascular risk factors. These associations appear to be stronger in males than in females.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

White matter microstructural abnormalities in amnestic mild cognitive impairment: A meta-analysis of whole-brain and ROI-based studies

Studies that examined white matter (WM) alterations in amnestic mild cognitive impairment (aMCI) abound. This timely meta-analysis aims to synthesize the results of these studies. Seventy-seven studies (totalN_aMCI=1844) were included. Fourteen region-of-interest-based (ROI-based) (k≥8;N_aMCI≥284 per ROI) and two activation likelihood estimation (ALE) meta-analyses (fractional anisotropy [FA]: k=15;N_aMCI=463; mean diffusivity [MD]: k=8;N_aMCI=193) were carried out. Among the many significant ROI-related findings, reliable FA and MD alterations in the fornix, uncinate fasciculus, and parahippocampal cingulum were observed in aMCI. Larger effects were observed in MD relative to FA. The ALE meta-analysis revealed a significant FA decrease among aMCI subjects in the posterior corona radiata. These results provide robust evidence of the presence of WM abnormalities in aMCI. Our findings also highlight the importance of carrying out both ROI-based and whole-brain-based research to obtain a complete picture of WM microstructural alterations associated with the condition..

Structural MRI research in patients with nasopharyngeal carcinoma following radiotherapy: A DTI and VBM study

The aim of the present study was to investigate the microstructural characteristics of the brain lobes following radiotherapy (RT) for patients with nasopharyngeal carcinoma (NPC) at distinct times. Diffusion tensor imaging (DTI) and 3D-T1-weighted imaging was performed in 70 age- and sex-matched subjects, 24 of whom were pre-treatment patients. The patients were divided into three groups, according to the time following completion of RT. Fractional anisotropy (FA) and gray matter (GM) volume were determined. The DTI data were analyzed using tract-based spatial statistics and the GM volume was analyzed using voxel-based morphometry (VBM). Compared with the pre-RT group, the mean FA values in the left parietal lobe white matter (WM) and right cerebellum decreased significantly in the post-RT 0-6 month group (P<0.05). In addition, the mean FA values in the right parietal lobe WM decreased significantly in the post-RT 6-12 month group (P<0.05), compared with the pre-RT group. The FA level in the right temporal lobe remained significantly decreased, compared with that in the pre-RT group (P<0.05) for 1 year after RT. Furthermore, compared with pre-RT group, the GM volume in the bilateral frontal lobe, right occipital lobe, left parietal lobe, right temporal lobe and left cerebellum decreased significantly in the post-RT 0-6 month group (P<0.05), and in the bilateral temporal lobe, parietal lobe, right frontal lobe and left cerebellum, the GM volume decreased significantly in the post-RT 6-12 month group (P<0.05). The GM volume in the right temporal lobe, bilateral frontal lobe and bilateral cerebellum remained significantly decreased compared with that in the pre-RT group (P<0.05) for 1 year after RT. A combination of DTI and VBM may be used to determine radiation-induced brain injury in patients treated for NPC.

Age-related differences in the topological efficiency of the brain structural connectome in amnestic mild cognitive impairment

Amnestic mild cognitive impairment (aMCI) is accompanied by the accelerated cognitive decline and rapid brain degeneration with aging. However, the age-related alterations of the topological organization of the brain connectome in aMCI patients remained largely unknown. In this study, we constructed the brain structural connectome in 51 aMCI patients and 51 healthy controls by diffusion magnetic resonance imaging and deterministic tractography. The different age-related alteration patterns of the global and regional network metrics between aMCI patients and healthy controls were assessed by a linear regression model. Compared with healthy controls, significantly decreased global and local network efficiency in aMCI patients were found. When correlating network efficiency with age, we observed a significant decline in network efficiency with aging in the aMCI patients, while not in the healthy controls. The age-related decreases of nodal efficiency in aMCI patients were mainly distributed in the key regions of the default-mode network, such as precuneus, anterior cingulate gyrus, and parahippocampal gyrus. In addition, age-related decreases in the connection strength of the edges between peripheral nodes were observed in aMCI patients. Moreover, the decreased regional efficiency of the parahippocampal gyrus was correlated with impaired memory performances in patients. The present study suggests an age-related disruption of the topological organization of the brain structural connectome in aMCI patients, which may provide evidence for different neural mechanisms underlying aging in aMCI and may serve as a potential imaging marker for the early diagnosis of Alzheimer's disease.

A T1 and DTI fused 3D corpus callosum analysis in MCI subjects with high and low cardiovascular risk profile

Understanding the extent to which vascular disease and its risk factors are associated with prodromal dementia, notably Alzheimer's disease (AD), may enhance predictive accuracy as well as guide early interventions. One promising avenue to determine this relationship consists of looking for reliable and sensitive in-vivo imaging methods capable of characterizing the subtle brain alterations before the clinical manifestations. However, little is known from the imaging perspective about how risk factors such as vascular disease influence AD progression. Here, for the first time, we apply an innovative T1 and DTI fusion analysis of 3D corpus callosum (CC) on mild cognitive impairment (MCI) populations with different levels of vascular profile, aiming to de-couple the vascular factor in the prodromal AD stage. Our new fusion method successfully increases the detection power for differentiating MCI subjects with high from low vascular risk profiles, as well as from healthy controls. MCI subjects with high and low vascular risk profiles showed differed alteration patterns in the anterior CC, which may help to elucidate the inter-wired relationship between MCI and vascular risk factors.

Brain atrophy in Alzheimer's Disease and aging

Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer's disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression.

Diffusion tensor imaging predicts cognitive function change following partial brain radiotherapy for low-grade and benign tumors

PURPOSE/OBJECTIVES

Radiation injury to parahippocampal cingulum white matter is associated with cognitive decline. Diffusion tensor imaging (DTI) detects micropathologic changes in white matter. Increased radial diffusion (RD) and decreased axial diffusion (AD) correspond to demyelination and axonal degeneration/gliosis respectively. We aimed to develop a predictive model for radiation-induced cognitive changes based upon DTI changes.

MATERIALS/METHODS

Twenty-seven adults with benign or low-grade tumors received partial brain radiation therapy (RT) to a median dose of 54Gy. Patients underwent DTI before RT, during RT, and at the end of RT. Cognitive testing was performed before RT, and 6 and 18months after RT. Parahippocampal cingulum white matter was contoured to obtain mean values of AD and RD.

RESULTS

By univariate analysis, decreasing AD and increasing RD during RT predicted declines in verbal memory and verbal fluency. By multivariate analysis, baseline neurocognitive score was the only clinical variable predicting verbal memory change; no clinical variables predicted verbal fluency change. In a multivariate model, increased RD at the end of RT significantly predicted decline in verbal fluency 18months after RT.

CONCLUSIONS

Imaging biomarkers of white matter injury contributed to predictive models of cognitive function change after RT.

Disrupted white matter integrity is associated with cognitive deficits in patients with amnestic mild cognitive impairment: An atlas-based study

Objective:

This study investigated white matter integrity in patients with amnestic mild cognitive impairment by diffusion tensor imaging.

Methods:

A total of 83 patients with amnestic mild cognitive impairment and 85 elderly healthy controls underwent neuropsychological testing and a diffusion tensor imaging scan. Whole-brain white matter data were parcellated into 50 regions based on the anatomical ICBM-DTI-81 atlas, and regional diffusion metrics consisting of fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity were calculated for each region. Diffusion tensor imaging indices were compared between groups, and it was determined that between-group differences were significantly correlated with neurocognitive performance.

Results:

Relative to the healthy controls group, the amnestic mild cognitive impairment group exhibited poorer cognitive performance in all neuropsychological tests except the complex figure test (p = 0.083) and showed decreased mean fractional anisotropy in the fornix, increased mean diffusivity in the fornix and bilateral uncinate fasciculus, elevated axial diffusivity in the fornix and genu of corpus callosum, and elevated radial diffusivity in the fornix and bilateral uncinate fasciculus (p < 0.05). Behaviorally, integrity of the bilateral uncinate fasciculus was correlated positively with episodic memory function, while left uncinate fasciculus integrity was positively associated with language function in the amnestic mild cognitive impairment group (p < 0.05).

Conclusion:

White matter abnormalities in neural pathways associated with memory were correlated with neurocognitive deficiencies in amnestic mild cognitive impairment. Given that amnestic mild cognitive impairment is putatively a prodromal syndrome for Alzheimer’s disease, this study furthers our understanding of the white matter changes associated with Alzheimer’s disease pathogenesis in the predementia stage.

Whole-brain changes in white matter microstructure after radiotherapy for nasopharyngeal carcinoma: a diffusion tensor imaging study

Radiation-induced local white matter (WM) damage has been observed by diffusion tensor imaging (DTI) within a priori-defined regions of interest following radiotherapy (RT) for nasopharyngeal carcinoma (NPC). In this study, we aimed to detect WM changes throughout the brain of NPC patients by DTI. Tract-based spatial statistics (TBSS) was used to analyze DTI data from 81 NPC patients. Fractional anisotropy (FA) and mean diffusivity (MD) were quantified across the whole brain in separate groups: pre-RT, and <6, 6-12, and >12 months post-RT. We found that fractional anisotropy values were significantly lower in the right frontal, parietal, and occipital WM <6 months post-RT compared with pre-RT and remained significantly lower in the right frontal and parietal WM at >12 months. MD values were significantly higher in the right occipital, bilateral temporal, right occipital-temporal junction, left parietal, left centrum semiovale, and left frontal-parietal junction WM <6 months post-RT and remained higher in the right occipital WM at >12 months. This study suggests that changes in white matter microstructure following RT for NPC were widespread, complex, and dynamic. Diffusion tensor imaging with TBSS analysis allows for early non-invasive detection of RT-induced WM damage.

A novel method for evaluating brain function and microstructural changes in Parkinson's disease

In this study, microstructural brain damage in Parkinson's disease patients was examined using diffusion tensor imaging and tract-based spatial statistics. The analyses revealed the presence of neuronal damage in the substantia nigra and putamen in the Parkinson's disease patients. Moreover, disease symptoms worsened with increasing damage to the substantia nigra, confirming that the substantia nigra and basal ganglia are the main structures affected in Parkinson's disease. We also found that microstructural damage to the putamen, caudate nucleus and frontal lobe positively correlated with depression. Based on the tract-based spatial statistics, various white matter tracts appeared to have microstructural damage, and this correlated with cognitive disorder and depression. Taken together, our results suggest that diffusion tensor imaging and tract-based spatial statistics can be used to effectively study brain function and microstructural changes in patients with Parkinson's disease. Our novel findings should contribute to our understanding of the histopathological basis of cognitive dysfunction and depression in Parkinson's disease.

White matter compromise in veterans exposed to primary blast forces

OBJECTIVE

Use diffusion tensor imaging to investigate white matter alterations associated with blast exposure with or without acute symptoms of traumatic brain injury (TBI).

PARTICIPANTS

Forty-five veterans of the recent military conflicts included 23 exposed to primary blast without TBI symptoms, 6 having primary blast with mild TBI, and 16 unexposed to blast.

DESIGN

Cross-sectional case-control study.

MAIN MEASURES

Neuropsychological testing and diffusion tensor imaging metrics that quantified the number of voxel clusters with altered fractional anisotropy (FA) radial diffusivity, and axial diffusivity, regardless of their spatial location.

RESULTS

Significantly lower FA and higher radial diffusivity were observed in veterans exposed to primary blast with and without mild TBI relative to blast-unexposed veterans. Voxel clusters of lower FA were spatially dispersed and heterogeneous across affected individuals.

CONCLUSION

These results suggest that lack of clear TBI symptoms following primary blast exposure may not accurately reflect the extent of brain injury. If confirmed, our findings would argue for supplementing the established approach of making diagnoses based purely on clinical history and observable acute symptoms with novel neuroimaging-based diagnostic criteria that "look below the surface" for pathology.

Imaging of Functional and Dysfunctional Episodic Memory

A foundational framework for understanding functional and dysfunctional imaging of episodic memory emerges from the last 3 decades of human and animal research. This comprehensive review is presented from the vantage point of the fornix, a white matter bridge that occupies a central position in this functional network. Salient insights are identified, spanning topics such as hippocampal efferent and afferent networks, input and processing streams, hemispheric specialization, dysfunctional effects of pathologic and surgical injury, optimization of functional magnetic resonance imaging design and neuropsychological tests, and rehabilitation strategies. Far-reaching implications are considered for radiologists, whose clinical effect stretches beyond imaging and interfaces with neurosurgeons, neuropsychologists, and other neurospecialists.

Altered white matter integrity in individuals with cognitive vulnerability to depression: a tract-based spatial statistics study

The microstructure of white matter in patients with major depressive disorder (MDD) has been demonstrated to be abnormal. However, it remains unclear whether these changes exist prior to the onset of disease. In this study, diffusion tensor imaging was used to evaluate white matter integrity in individuals who exhibited cognitive vulnerability to depression (CVD), MDD, and healthy controls (HC). Compared with the HC, MDD exhibited a lower fractional anisotropy (FA) in ten brain regions: the cerebral peduncle, the anterior and posterior limbs of the internal capsule (ALIC and PLIC), the external capsule, the retrolenticular part of the internal capsule (RLIC), the body and splenium of the corpus callosum, the superior and posterior corona radiata, and the cingulum. Moreover, CVD had significantly lower FA in the ALIC, the PLIC, the external capsule, the RLIC, the cerebral peduncle, and the superior corona radiata than did the HC. However, the white matter integrity was not significantly different between the CVD and MDD. These preliminary results indicate that alterations in the white matter observed in CVD may be a marker of vulnerability to MDD and that these alterations may exist prior to the onset of depression.

Changes of gray matter volume and amplitude of low-frequency oscillations in amnestic MCI: An integrative multi-modal MRI study

BACKGROUND

Numerous studies have reported that the amnestic-type mild cognitive impairment (aMCI) patients have impaired brain structural integrity and functional alterations separately.

PURPOSE

To investigate the changes of gray matter and amplitude of low-frequency oscillations in patients with aMCI by combining structural and functional magnetic resonance imaging (fMRI).

MATERIAL AND METHODS

Thirty-four patients with aMCI and 34 controls were recruited. We adopted optimized voxel-based morphometry to detect regions with gray matter volume (GMV) loss induced by aMCI. Then regional differences in amplitude of slow-4 band (0.027-0.073 Hz) oscillations among these regions between patients and healthy controls were examined. Both slow-4 amplitude of low-frequency fluctuations (ALFF) and slow-4 fractional ALFF (fALFF; the relative amplitude that resides in the low frequencies) were employed.

RESULTS

Patients with aMCI demonstrated significant GMV loss in the ventral medial prefrontal cortex (vMPFC), posterior cingulate cortex (PCC), bilateral hippocampus, right superior parietal gyrus, left insula and left middle temporal gyrus (P < 0.01). The patients exhibited significant decreases of slow-4 ALFF in the left hippocampus (P = 0.05) and PCC (P = 0.02), while the decreased slow-4 fALFF was detected in PCC (P = 0.01) and increased slow-4 fALFF in vMPFC (P = 0.03). In PCC, aMCI and controls exhibited significant different GMV-fALFF correlation (P < 0.05), with opposite correlation trend.

CONCLUSION

The correlates between anatomical deficits and functional alterations in aMCI suggest that anatomical and functional deficits are linked to each other. The differences of GMV-fALFF correlations demonstrated altered anatomical-functional relationship in aMCI.

Disrupted functional and structural networks in cognitively normal elderly subjects with the APOE ɛ4 allele

As the Apolipoprotein E (APOE) ɛ4 allele is a major genetic risk factor for sporadic Alzheimer's disease (AD), which has been suggested as a disconnection syndrome manifested by the disruption of white matter (WM) integrity and functional connectivity (FC), elucidating the subtle brain structural and functional network changes in cognitively normal ɛ4 carriers is essential for identifying sensitive neuroimaging based biomarkers and understanding the preclinical AD-related abnormality development. We first constructed functional network on the basis of resting-state functional magnetic resonance imaging and a structural network on the basis of diffusion tensor image. Using global, local and nodal efficiencies of these two networks, we then examined (i) the differences of functional and WM structural network between cognitively normal ɛ4 carriers and non-carriers simultaneously, (ii) the sensitivity of these indices as biomarkers, and (iii) their relationship to behavior measurements, as well as to cholesterol level. For ɛ4 carriers, we found reduced global efficiency significantly in WM and marginally in FC, regional FC dysfunctions mainly in medial temporal areas, and more widespread for WM network. Importantly, the right parahippocampal gyrus (PHG.R) was the only region with simultaneous functional and structural damage, and the nodal efficiency of PHG.R in WM network mediates the APOE ɛ4 effect on memory function. Finally, the cholesterol level correlated with WM network differently than with the functional network in ɛ4 carriers. Our results demonstrated ɛ4-specific abnormal structural and functional patterns, which may potentially serve as biomarkers for early detection before the onset of the disease.

Neuropsychological and neuroimaging characteristics of amnestic mild cognitive impairment subtypes: a selective overview

Alzheimer's disease (AD) is a progressive age-related neurodegenerative disease. Amnestic mild cognitive impairment (aMCI) is considered to represent early AD. Various aMCI clinical subtypes have been identified as either single domain (SD) or multidomain (MD). The various subtypes represent heterogeneous syndrome, indicating the different probability of progression to AD. Understanding the heterogeneous concept of aMCI can help to construct potential biomarkers to monitor the progression of aMCI to AD. This review provides an overview of various neuroimaging measures for subtypes of aMCI. Focusing on neuropsychological, structural, and functional neuroimaging findings, we found that aMCI showed differences in clinical progression and the abnormalities in MD-aMCI were distributed across temporal, frontal, and parietal cortices, which is similar to AD. This is also compatible with the notion that MD-aMCI is a transition stage between SD-aMCI and AD. Our review provided a framework for the diagnosis of clinical subtypes of aMCI and early detection and intervention of the progression from aMCI to AD.

Memory binding and white matter integrity in familial Alzheimer's disease

Binding information in short-term and long-term memory are functions sensitive to Alzheimer's disease. They have been found to be affected in patients who meet criteria for familial Alzheimer's disease due to the mutation E280A of the PSEN1 gene. However, only short-term memory binding has been found to be affected in asymptomatic carriers of this mutation. The neural correlates of this dissociation are poorly understood. The present study used diffusion tensor magnetic resonance imaging to investigate whether the integrity of white matter structures could offer an account. A sample of 19 patients with familial Alzheimer's disease, 18 asymptomatic carriers and 21 non-carrier controls underwent diffusion tensor magnetic resonance imaging, neuropsychological and memory binding assessment. The short-term memory binding task required participants to detect changes across two consecutive screens displaying arrays of shapes, colours, or shape-colour bindings. The long-term memory binding task was a Paired Associates Learning Test. Performance on these tasks were entered into regression models. Relative to controls, patients with familial Alzheimer's disease performed poorly on both memory binding tasks. Asymptomatic carriers differed from controls only in the short-term memory binding task. White matter integrity explained poor memory binding performance only in patients with familial Alzheimer's disease. White matter water diffusion metrics from the frontal lobe accounted for poor performance on both memory binding tasks. Dissociations were found in the genu of corpus callosum which accounted for short-term memory binding impairments and in the hippocampal part of cingulum bundle which accounted for long-term memory binding deficits. The results indicate that white matter structures in the frontal and temporal lobes are vulnerable to the early stages of familial Alzheimer's disease and their damage is associated with impairments in two memory binding functions known to be markers for Alzheimer's disease.

White matter integrity in small vessel disease is related to cognition

Cerebral small vessel disease, including white matter hyperintensities (WMH) and lacunes of presumed vascular origin, is common in elderly people and is related to cognitive impairment and dementia. One possible mechanism could be the disruption of white matter tracts (both within WMH and normal-appearing white matter) that connect distributed brain regions involved in cognitive functions. Here, we investigated the relation between microstructural integrity of the white matter and cognitive functions in patients with small vessel disease. The Radboud University Nijmegen Diffusion tensor and Magnetic resonance Cohort study is a prospective cohort study among 444 independently living, non-demented elderly with cerebral small vessel disease, aged between 5500 and 85 years. All subjects underwent magnetic resonance imaging and diffusion tensor imaging scanning and an extensive neuropsychological assessment. We showed that loss of microstructural integrity of the white matter at specific locations was related to specific cognitive disturbances, which was mainly located in the normal-appearing white matter (p < 0.05, FWE-corrected for multiple comparisons). The microstructural integrity in the genu and splenium showed the highest significant relation with global cognitive function and executive functions, in the cingulum bundle with verbal memory performance. Associations between diffusion tensor imaging parameters and most cognitive domains remained present after adjustment for WMH and lacunes. In conclusion, cognitive disturbances in subjects with cerebral small vessel disease are related to microstructural integrity of multiple white matter fibers (within WMH and normal-appearing white matter) connecting different cortical and subcortical regions.

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White matter integrity in small vessel disease (SVD) was assessed with DTI.

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White matter integrity was related to cognition independent of SVD-markers.

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This relation was seen in multiple fibers within white matter hyperintensities.

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But also in normal-appearing white matter connecting different (sub)cortical regions

Fornix White Matter is Correlated with Resting-State Functional Connectivity of the Thalamus and Hippocampus in Healthy Aging but Not in Mild Cognitive Impairment - A Preliminary Study

In this study, we wished to examine the relationship between the structural connectivity of the fornix, a white matter (WM) tract in the limbic system, which is affected in amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease, and the resting-state functional connectivity (FC) of two key related subcortical structures, the thalamus, and hippocampus. Twenty-two older healthy controls (HC) and 18 older adults with aMCI underwent multi-modal MRI scanning. The fornix was reconstructed using constrained-spherical deconvolution-based tractography. The FC between the thalamus and hippocampus was calculated using a region-of-interest approach from which the mean time series were exacted and correlated. Diffusion tensor imaging measures of the WM microstructure of the fornix were correlated against the Fisher Z correlation values from the FC analysis. There was no difference between the groups in the fornix WM measures, nor in the resting-state FC of the thalamus and hippocampus. We did however find that the relationship between functional and structural connectivity differed significantly between the groups. In the HCs, there was a significant positive association between linear diffusion (CL) in the fornix and the FC of the thalamus and hippocampus, however, there was no relationship between these measures in the aMCI group. These preliminary findings suggest that in aMCI, the relationship between the functional and structural connectivity of regions of the limbic system may be significantly altered compared to healthy ageing. The combined use of diffusion weighted imaging and functional MRI may advance our understanding of neural network changes in aMCI, and elucidate subtle changes in the relationship between structural and functional brain networks.

White matter disruption at the prodromal stage of Alzheimer's disease: relationships with hippocampal atrophy and episodic memory performance

White matter tract alterations have been consistently described in Alzheimer's disease (AD). In particular, limbic fronto-temporal connections, which are critical to episodic memory function, may degenerate early in the course of the disease. However the relation between white matter tract degeneration, hippocampal atrophy and episodic memory impairment at the earliest stages of AD is still unclear. In this magnetic resonance imaging study, white matter integrity and hippocampal volumes were evaluated in patients with amnestic mild cognitive impairment due to AD (Albert et al., 2011) (n = 22) and healthy controls (n = 15). Performance in various episodic memory tasks was also evaluated in each participant. Relative to controls, patients showed a significant reduction of white matter fractional anisotropy (FA) and increase of radial diffusivity (RD) in the bilateral uncinate fasciculus, parahippocampal cingulum and fornix. Within the patient group, significant intra-hemispheric correlations were notably found between hippocampal grey matter volume and FA in the uncinate fasciculus, suggesting a relationship between atrophy and disconnection of the hippocampus. Moreover, episodic recognition scores were related with uncinate fasciculus FA across patients. These results indicate that fronto-hippocampal connectivity is reduced from the earliest pre-demential stages of AD. Disruption of fronto-hippocampal connections may occur progressively, in parallel with hippocampal atrophy, and may specifically contribute to early initial impairment in episodic memory.

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Limbic fronto-temporal connections (cingulum, uncinate fasciculus and fornix) are altered from the prodromal stage of AD.

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In prodromal AD patients, intra-hemispheric correlations were found between uncinate fasciculus FA and hippocampal atrophy.

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In prodromal AD patients, uncinate fasciculus FA was correlated with scores on episodic recognition.

Integrating retrogenesis theory to Alzheimer's disease pathology: insight from DTI-TBSS investigation of the white matter microstructural integrity

Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD) and may reflect primary or secondary circuitry degeneration (i.e., due to cortical atrophy). The interpretation of diffusion tensor imaging (DTI) eigenvectors, known as multiple indices, may provide new insights into the main pathological models supporting primary or secondary patterns of WM disruption in AD, the retrogenesis, and Wallerian degeneration models, respectively. The aim of this review is to analyze the current literature on the contribution of DTI multiple indices to the understanding of AD neuropathology, taking the retrogenesis model as a reference for discussion. A systematic review using MEDLINE, EMBASE, and PUBMED was performed. Evidence suggests that AD evolves through distinct patterns of WM disruption, in which retrogenesis or, alternatively, the Wallerian degeneration may prevail. Distinct patterns of WM atrophy may be influenced by complex interactions which comprise disease status and progression, fiber localization, concurrent risk factors (i.e., vascular disease, gender), and cognitive reserve. The use of DTI multiple indices in addition to other standard multimodal methods in dementia research may help to determine the contribution of retrogenesis hypothesis to the understanding of neuropathological hallmarks that lead to AD.

Fornix as an imaging marker for episodic memory deficits in healthy aging and in various neurological disorders

The fornix is a part of the limbic system and constitutes the major efferent and afferent white matter tracts from the hippocampi. The underdevelopment of or injuries to the fornix are strongly associated with memory deficits. Its role in memory impairments was suggested long ago with cases of surgical forniceal transections. However, recent advances in brain imaging techniques, such as diffusion tensor imaging, have revealed that macrostructural and microstructural abnormalities of the fornix correlated highly with declarative and episodic memory performance. This structure appears to provide a robust and early imaging predictor for memory deficits not only in neurodegenerative and neuroinflammatory diseases, such as Alzheimer's disease and multiple sclerosis, but also in schizophrenia and psychiatric disorders, and during neurodevelopment and “typical” aging. The objective of the manuscript is to present a systematic review regarding published brain imaging research on the fornix, including the development of its tracts, its role in various neurological diseases, and its relationship to neurocognitive performance in human studies.

Widespread white matter degeneration preceding the onset of dementia

BACKGROUND

Brain atrophy in subjects with mild cognitive impairment (MCI) introduces partial volume effects, limiting the sensitivity of diffusion tensor imaging to white matter microstructural degeneration. Appropriate correction isolates microstructural effects in MCI that might be precursors of Alzheimer's disease (AD).

METHODS

Forty-eight participants (18 MCI, 15 AD, and 15 healthy controls) had magnetic resonance imaging scans and clinical evaluations at baseline and follow-up after 36 months. Ten MCI subjects were diagnosed with AD at follow-up and eight remained MCI. Free-water (FW) corrected measures on the white matter skeleton were compared between groups.

RESULTS

FW corrected radial diffusivity, but not uncorrected radial diffusivity, was increased across the brain of the converted group compared with the nonconverted group (P < .05). The extent of increases was similar to that found comparing AD with controls.

CONCLUSION

Partial volume elimination reveals microstructural alterations preceding dementia. These alterations may prove to be an effective and feasible early biomarker of AD.