Estimating individual trajectories of structural and cognitive decline in mild cognitive impairment for early prediction of progression to dementia of the Alzheimer's type.

Only a third of individuals with mild cognitive impairment (MCI) progress to dementia of the Alzheimer's type (DAT). Identifying biomarkers that distinguish individuals with MCI who will progress to DAT (MCI-Converters) from those who will not (MCI-Non-Converters) remains a key challenge in the field. In our study, we evaluate whether the individual rates of loss of volumes of the Hippocampus and entorhinal cortex (EC) with age in the MCI stage can predict progression to DAT. Using data from 758 MCI patients in the Alzheimer's Disease Neuroimaging Database, we employ Linear Mixed Effects (LME) models to estimate individual trajectories of regional brain volume loss over 12 years on average. Our approach involves three key analyses: (1) mapping age-related volume loss trajectories in MCI-Converters and Non-Converters, (2) using logistic regression to predict progression to DAT based on individual rates of hippocampal and EC volume loss, and (3) examining the relationship between individual estimates of these volumetric changes and cognitive decline across different cognitive functions-episodic memory, visuospatial processing, and executive function. We find that the loss of Hippocampal volume is significantly more rapid in MCI-Converters than Non-Converters, but find no such difference in EC volumes. We also find that the rate of hippocampal volume loss in the MCI stage is a significant predictor of conversion to DAT, while the rate of volume loss in the EC and other additional regions is not. Finally, individual estimates of rates of regional volume loss in both the Hippocampus and EC, and other additional regions, correlate strongly with individual rates of cognitive decline. Across all analyses, we find significant individual variation in the initial volumes and the rates of changes in volume with age in individuals with MCI. This study highlights the importance of personalized approaches in predicting AD progression, offering insights for future research and intervention strategies.

Cognitive profile, neuroimaging and fluid biomarkers in post-acute COVID-19 syndrome.

We aimed to characterize the cognitive profile of post-acute COVID-19 syndrome (PACS) patients with cognitive complaints, exploring the influence of biological and psychological factors. Participants with confirmed SARS-CoV-2 infection and cognitive complaints ≥ 8 weeks post-acute phase were included. A comprehensive neuropsychological battery (NPS) and health questionnaires were administered at inclusion and at 1, 3 and 6 months. Blood samples were collected at each visit, MRI scan at baseline and at 6 months, and, optionally, cerebrospinal fluid. Cognitive features were analyzed in relation to clinical, neuroimaging, and biochemical markers at inclusion and follow-up. Forty-nine participants, with a mean time from symptom onset of 10.4 months, showed attention-executive function (69%) and verbal memory (39%) impairment. Apathy (64%), moderate-severe anxiety (57%), and severe fatigue (35%) were prevalent. Visual memory (8%) correlated with total gray matter (GM) and subcortical GM volume. Neuronal damage and inflammation markers were within normal limits. Over time, cognitive test scores, depression, apathy, anxiety scores, MRI indexes, and fluid biomarkers remained stable, although fewer participants (50% vs. 75.5%; p = 0.012) exhibited abnormal cognitive evaluations at follow-up. Altered attention/executive and verbal memory, common in PACS, persisted in most subjects without association with structural abnormalities, elevated cytokines, or neuronal damage markers.

Serum albumin and white matter hyperintensities.

People living with HIV and those diagnosed with alcohol use disorders (AUD) relative to healthy individuals commonly have low levels of serum albumin, substantiated as an independent predictor of cardiovascular events. White matter hyperintensities (WMH)-a neuroimaging feature of cerebral small vessel disease-are also related to cardiovascular disease. Despite consensus regarding associations between high levels of urine albumin and WMH prevalence, and low serum albumin levels and impaired cognitive functioning, relations between serum albumin and WMH burdens have rarely been evaluated. Here, a sample including 160 individuals with AUD, 142 living with HIV, and 102 healthy controls was used to test the hypothesis that serum albumin would be inversely related to WMH volumes and directly related to cognitive performance in the two diagnostic groups. Although serum albumin and periventricular WMH volumes showed an inverse relationship in both AUD and HIV groups, this relationship persisted only in the HIV group after consideration of traditional cardiovascular (i.e., age, sex, body mass index (BMI), nicotine use, hypertension, diabetes), study-relevant (i.e., race, socioeconomic status, hepatitis C virus status), and disease-specific (i.e., CD4 nadir, HIV viral load, HIV duration) factors. Further, serum albumin contributed more significantly than periventricular WMH volume to variance in performance on a verbal learning and memory composite score in the HIV group only. Relations in both HIV and AUD groups between albumin and hematological red blood cell markers (e.g., hemoglobin, hematocrit) suggest that in this sample, serum albumin reflects hematological abnormalities. Albumin, a simple serum biomarker available in most clinical settings, may therefore help identify periventricular WMH burden and performance levels in specific cognitive domains in people living with HIV. Whether serum albumin contributes mechanistically to periventricular WMH in HIV will require additional investigation.

Amyloid-PET imaging predicts functional decline in clinically normal individuals.

BACKGROUND: There is good evidence that elevated amyloid-ß (Aß) positron emission tomography (PET) signal is associated with cognitive decline in clinically normal (CN) individuals. However, it is less well established whether there is an association between the Aß burden and decline in daily living activities in this population. Moreover, Aß-PET Centiloids (CL) thresholds that can optimally predict functional decline have not yet been established. METHODS: Cross-sectional and longitudinal analyses over a mean three-year timeframe were performed on the European amyloid-PET imaging AMYPAD-PNHS dataset that phenotypes 1260 individuals, including 1032 CN individuals and 228 participants with questionable functional impairment. Amyloid-PET was assessed continuously on the Centiloid (CL) scale and using Aß groups (CL < 12 = Aß-, 12 ≤ CL ≤ 50 = Aß-intermediate/Aß± , CL > 50 = Aß+). Functional abilities were longitudinally assessed using the Clinical Dementia Rating (Global-CDR, CDR-SOB) and the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). The Global-CDR was available for the 1260 participants at baseline, while baseline CDR-SOB and A-IADL-Q scores and longitudinal functional data were available for different subsamples that had similar characteristics to those of the entire sample. RESULTS: Participants included 765 Aß- (61%, Mdnage = 66.0, IQRage = 61.0-71.0; 59% women), 301 Aß± (24%; Mdnage = 69.0, IQRage = 64.0-75.0; 53% women) and 194 Aß+ individuals (15%, Mdnage = 73.0, IQRage = 68.0-78.0; 53% women). Cross-sectionally, CL values were associated with CDR outcomes. Longitudinally, baseline CL values predicted prospective changes in the CDR-SOB (bCL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p = .003) and A-IADL-Q (bCL*Time = -0.010/CL/year, 95% CI [-0.016,-0.004], p = .002) scores in initially CN participants. Increased clinical progression (Global-CDR > 0) was mainly observed in Aß+ CN individuals (HRAß+ vs Aß- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAß+ vs Aß- = 0.137/year, 95% CI [0.069,0.206], p < .001) and 28 CL using the A-IADL-Q (bAß+ vs Aß- = -0.693/year, 95% CI [-1.179,-0.208], p = .005). CONCLUSIONS: Amyloid-PET quantification supports the identification of CN individuals at risk of functional decline. TRIAL REGISTRATION: The AMYPAD PNHS is registered at www.clinicaltrialsregister.eu with the EudraCT Number: 2018-002277-22.

Association of MRI Indexes of the Perivascular Space Network and Cognitive Impairment in Patients with Obstructive Sleep Apnea.

Background The role of perivascular space (PVS) dysfunction in obstructive sleep apnea (OSA) requires further study. Purpose To compare MRI indexes of PVS across patients with differing severities of OSA and relate them with disease characteristics and treatment. Materials and Methods This single-center prospective study included healthy controls (HCs) and patients with complaints of snoring who underwent MRI and cognitive evaluation between June 2021 and December 2022. Participants with complaints of snoring were classified into four groups (snoring, mild OSA, moderate OSA, and severe OSA). PVS networks were assessed at MRI using PVS volume fraction, extracellular free water (FW), and diffusion tensor imaging analysis along the PVS (DTI-ALPS). One-way analysis of variance and Pearson correlation were used for analysis. Alterations in PVS indexes and cognitive performance after treatment were assessed in 15 participants with moderate OSA. Results A total of 105 participants (mean age, 33.4 years ± 8.9 [SD]; 80 males) and 50 HCs (mean age, 37.0 years ± 8.6; 33 males) were included. Higher mean PVS volume fraction was observed in participants with severe OSA (n = 23) than in patients with mild OSA (n = 36) (0.11 vs 0.10; P = .03). Participants with severe OSA exhibited higher mean FW index (0.11) than both HCs (0.10; P < .001) and patients with mild OSA (0.10; P = .003). All patient groups had lower DTI-ALPS than HCs (range, 1.5-1.9 vs 2.1; all P < .001). DTI-ALPS correlated with cognitive performance on the Stroop Color and Word Test (r range, -0.23 to -0.24; P value range, .003-.005). After treatment, PVS indexes changed (P value range, <.001 to .01) and cognitive performance improved (P value range, <.001 to .03). Conclusion Differences in PVS indexes were observed among participants with differing severities of OSA and HCs. Indexes correlated with measures of cognitive function, and changes in indexes and improvement in cognitive performance were observed after treatment in participants with moderate OSA. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Port in this issue.

Latent diffusion model-based MRI superresolution enhances mild cognitive impairment prognostication and Alzheimer's disease classification.

INTRODUCTION: Timely diagnosis and prognostication of Alzheimer's disease (AD) and mild cognitive impairment (MCI) are pivotal for effective intervention. Artificial intelligence (AI) in neuroradiology may aid in such appropriate diagnosis and prognostication. This study aimed to evaluate the potential of novel diffusion model-based AI for enhancing AD and MCI diagnosis through superresolution (SR) of brain magnetic resonance (MR) images. METHODS: 1.5T brain MR scans of patients with AD or MCI and healthy controls (NC) from Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) were superresolved to 3T using a novel diffusion model-based generative AI (d3T*) and a convolutional neural network-based model (c3T*). Comparisons of image quality to actual 1.5T and 3T MRI were conducted based on signal-to-noise ratio (SNR), naturalness image quality evaluator (NIQE), and Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE). Voxel-based volumetric analysis was then conducted to study whether 3T* images offered more accurate volumetry than 1.5T images. Binary and multiclass classifications of AD, MCI, and NC were conducted to evaluate whether 3T* images offered superior AD classification performance compared to actual 1.5T MRI. Moreover, CNN-based classifiers were used to predict conversion of MCI to AD, to evaluate the prognostication performance of 3T* images. The classification performances were evaluated using accuracy, sensitivity, specificity, F1 score, Matthews correlation coefficient (MCC), and area under the receiver-operating curves (AUROC). RESULTS: Analysis of variance (ANOVA) detected significant differences in image quality among the 1.5T, c3T*, d3T*, and 3T groups across all metrics. Both c3T* and d3T* showed superior image quality compared to 1.5T MRI in NIQE and BRISQUE with statistical significance. While the hippocampal volumes measured in 3T* and 3T images were not significantly different, the hippocampal volume measured in 1.5T images showed significant difference. 3T*-based AD classifications showed superior performance across all performance metrics compared to 1.5T-based AD classification. Classification performance between d3T* and actual 3T was not significantly different. 3T* images offered superior accuracy in predicting the conversion of MCI to AD than 1.5T images did. CONCLUSIONS: The diffusion model-based MRI SR enhances the resolution of brain MR images, significantly improving diagnostic and prognostic accuracy for AD and MCI. Superresolved 3T* images closely matched actual 3T MRIs in quality and volumetric accuracy, and notably improved the prediction performance of conversion from MCI to AD.

Divergent functional connectivity changes associated with white matter hyperintensities.

Age-related white matter hyperintensities are a common feature and are known to be negatively associated with structural integrity, functional connectivity, and cognitive performance. However, this has yet to be fully understood mechanistically. We analyzed multiple MRI modalities acquired in 465 non-demented individuals from the Swedish BioFINDER study including 334 cognitively normal and 131 participants with mild cognitive impairment. White matter hyperintensities were automatically quantified using fluid-attenuated inversion recovery MRI and parameters from diffusion tensor imaging were estimated in major white matter fibre tracts. We calculated fMRI resting state-derived functional connectivity within and between predefined cortical regions structurally linked by the white matter tracts. How change in functional connectivity is affected by white matter lesions and related to cognition (in the form of executive function and processing speed) was explored. We examined the functional changes using a measure of sample entropy. As expected hyperintensities were associated with disrupted structural white matter integrity and were linked to reduced functional interregional lobar connectivity, which was related to decreased processing speed and executive function. Simultaneously, hyperintensities were also associated with increased intraregional functional connectivity, but only within the frontal lobe. This phenomenon was also associated with reduced cognitive performance. The increased connectivity was linked to increased entropy (reduced predictability and increased complexity) of the involved voxels' blood oxygenation level-dependent signal. Our findings expand our previous understanding of the impact of white matter hyperintensities on cognition by indicating novel mechanisms that may be important beyond this particular type of brain lesions.

Changes of brain parenchyma free water fraction reflect tissue damage and impaired processing speed in multiple sclerosis.

Free water fraction (FWF) represents the amount of water per unit volume of brain parenchyma, which is not bound to macromolecules. Its excess in multiple sclerosis (MS) is related to increased tissue loss. The use of mcDESPOT (multicomponent driven single pulse observation of T1 and T2), a 3D imaging method which exploits both the T1 and T2 contrasts, allows FWF to be derived in clinically feasible times. However, this method has not been used to quantify changes of FWF and their potential clinical impact in MS. The aim of this study is to investigate the changes in FWF in MS patients and their relationship with tissue damage and cognition, under the hypothesis that FWF is a proxy of clinically meaningful tissue loss. To this aim, we tested the relationship between FWF, MS lesion burden and information processing speed, evaluated via the Symbol Digit Modalities Test (SDMT). In addition to standard sequences, used for T1- and T2-weighted lesion delineation, the mcDESPOT sequence with 1.7 mm isotropic resolution and a diffusion weighted imaging protocol (b = 0, 1200 s/mm2, 40 diffusion directions) were employed at 3 T. The fractional anisotropy map derived from diffusion data was used to define a subject-specific white matter (WM) atlas. Brain parenchyma segmentation returned masks of gray matter (GM) and WM, and normal-appearing WM (NAWM), in addition to the T1 and T2 lesion masks (T1L and T2L, respectively). Ninety-nine relapsing-remitting MS patients (age = 43.3 ± 9.9 years, disease duration 12.3 ± 7.7 years) were studied, together with twenty-five healthy controls (HC, age = 38.8 ± 11.0 years). FWF was higher in GM and NAWM of MS patients, compared to GM and WM of HC (both p < .001). In MS patients, FWF was the highest in the T1L and GM, followed by T2L and NAWM, respectively. FWF increased significantly with T1L and T2L volume (ρ ranging from 0.40 to 0.58, p < .001). FWF in T2L was strongly related to both T1L volume and the volume ratio T1L/T2L (ρ = 0.73, p < .001). MS patients performed worse than HC in the processing speed test (mean ± SD: 54.1 ± 10.3 for MS, 63.8 ± 10.8 for HC). FWF in GM, T2L, perilesional tissue and NAWM increased with SDMT score reduction (ρ = -0.30, -0.29, -0.33 respectively and r = -.30 for T2L, all with p < .005). A regional analysis, conducted to determine which NAWM regions were of particular importance to explain the relationship between FWF and cognitive impairment, revealed that FWF spatial variance was negatively related to SDMT score in the corpus callosum and the superior longitudinal fasciculus, WM structures known to be associated with cognitive impairment, in addition to the left corticospinal tract, the sagittal stratum, the right anterior limb of internal capsule. In conclusion, we found excess free water in brain parenchyma of MS patients, an alteration that involved not only MS lesions, but also the GM and NAWM, impinging on brain function and negatively associated with cognitive processing speed. We suggest that the FWF metric, derived from noninvasive, rapid MRI acquisitions and bearing good biological interpretability, may prove valuable as an MRI biomarker of tissue damage and associated cognitive impairment in MS.

Continuous ß-Amyloid CSF/PET Imbalance Model to Capture Alzheimer Disease Heterogeneity.

BACKGROUND AND OBJECTIVES: Discordance between CSF and PET biomarkers of ß-amyloid (Aß) might reflect an imbalance between soluble and aggregated species, possibly reflecting disease heterogeneity. Previous studies generally used binary cutoffs to assess discrepancies in CSF/PET biomarkers, resulting in a loss of information on the extent of discordance. In this study, we (1) jointly modeled Aß-CSF/PET data to derive a continuous measure of the imbalance between soluble and fibrillar pools of Aß, (2) investigated factors contributing to this imbalance, and (3) examined associations with cognitive trajectories. METHODS: Across 822 cognitively unimpaired (n = 261) and cognitively impaired (n = 561) Alzheimer's Disease Neuroimaging Initiative individuals (384 [46.7%] females, mean age 73.0 ± 7.4 years), we fitted baseline CSF-Aß42 and global Aß-PET to a hyperbolic regression model, deriving a participant-specific Aß-aggregation score (standardized residuals); negative values represent more soluble relative to aggregated Aß and positive values more aggregated relative to soluble Aß. Using linear models, we investigated whether methodological factors, demographics, CSF biomarkers, and vascular burden contributed to Aß-aggregation scores. With linear mixed models, we assessed whether Aß-aggregation scores were predictive of cognitive functioning. Analyses were repeated in an early independent validation cohort of 383 Amyloid Imaging to Prevent Alzheimer's Disease Prognostic and Natural History Study individuals (224 [58.5%] females, mean age 65.2 ± 6.9 years). RESULTS: The imbalance model could be fit (pseudo-R2 = 0.94) in both cohorts, across CSF kits and PET tracers. Although no associations were observed with the main methodological factors, lower Aß-aggregation scores were associated with larger ventricular volume (ß = 0.13, p < 0.001), male sex (ß = -0.18, p = 0.019), and homozygous APOE-ε4 carriership (ß = -0.56, p < 0.001), whereas higher scores were associated with increased uncorrected CSF p-tau (ß = 0.17, p < 0.001) and t-tau (ß = 0.16, p < 0.001), better baseline executive functioning (ß = 0.12, p < 0.001), and slower global cognitive decline (ß = 0.14, p = 0.006). In the validation cohort, we replicated the associations with APOE-ε4, CSF t-tau, and, although modestly, with cognition. DISCUSSION: We propose a novel continuous model of Aß CSF/PET biomarker imbalance, accurately describing heterogeneity in soluble vs aggregated Aß pools in 2 independent cohorts across the full Aß continuum. Aß-aggregation scores were consistently associated with genetic and AD-associated CSF biomarkers, possibly reflecting disease heterogeneity beyond methodological influences.

Brain age as a biomarker for pathological versus healthy ageing - a REMEMBER study.

OBJECTIVES: This study aimed to evaluate the potential clinical value of a new brain age prediction model as a single interpretable variable representing the condition of our brain. Among many clinical use cases, brain age could be a novel outcome measure to assess the preventive effect of life-style interventions. METHODS: The REMEMBER study population (N = 742) consisted of cognitively healthy (HC,N = 91), subjective cognitive decline (SCD,N = 65), mild cognitive impairment (MCI,N = 319) and AD dementia (ADD,N = 267) subjects. Automated brain volumetry of global, cortical, and subcortical brain structures computed by the CE-labeled and FDA-cleared software icobrain dm (dementia) was retrospectively extracted from T1-weighted MRI sequences that were acquired during clinical routine at participating memory clinics from the Belgian Dementia Council. The volumetric features, along with sex, were combined into a weighted sum using a linear model, and were used to predict 'brain age' and 'brain predicted age difference' (BPAD = brain age-chronological age) for every subject. RESULTS: MCI and ADD patients showed an increased brain age compared to their chronological age. Overall, brain age outperformed BPAD and chronological age in terms of classification accuracy across the AD spectrum. There was a weak-to-moderate correlation between total MMSE score and both brain age (r = -0.38,p < .001) and BPAD (r = -0.26,p < .001). Noticeable trends, but no significant correlations, were found between BPAD and incidence of conversion from MCI to ADD, nor between BPAD and conversion time from MCI to ADD. BPAD was increased in heavy alcohol drinkers compared to non-/sporadic (p = .014) and moderate (p = .040) drinkers. CONCLUSIONS: Brain age and associated BPAD have the potential to serve as indicators for, and to evaluate the impact of lifestyle modifications or interventions on, brain health.

Association of Basal Forebrain Atrophy With Cognitive Decline in Early Alzheimer Disease.

BACKGROUND AND OBJECTIVES: In early Alzheimer disease (AD), ß-amyloid (Aß) deposition is associated with volume loss in the basal forebrain (BF) and cognitive decline. However, the extent to which Aß-related BF atrophy manifests as cognitive decline is not understood. This study sought to characterize the relationship between BF atrophy and the decline in memory and attention in patients with early AD. METHODS: Participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study who completed Aß-PET imaging and repeated MRI and cognitive assessments were included. At baseline, participants were classified based on their clinical dementia stage and Aß status, yielding groups that were cognitively unimpaired (CU) Aß-, CU Aß+, and mild cognitive impairment (MCI) Aß+. Linear mixed-effects models were used to assess changes in volumetric measures of BF subregions and the hippocampus and changes in AIBL memory and attention composite scores for each group compared with CU Aß- participants. Associations between Aß burden, brain atrophy, and cognitive decline were evaluated and explored further using mediation analyses. RESULTS: The cohort included 476 participants (72.6 ± 5.9 years, 55.0% female) with longitudinal data from a median follow-up period of 6.1 years. Compared with the CU Aß- group (n = 308), both CU Aß+ (n = 107) and MCI Aß+ (n = 61) adults showed faster decline in BF and hippocampal volumes and in memory and attention (Cohen d = 0.73-1.74). Rates of atrophy in BF subregions and the hippocampus correlated with cognitive decline, and each individually mediated the impact of Aß burden on memory and attention decline. When all mediators were considered simultaneously, hippocampal atrophy primarily influenced the effect of Aß burden on memory decline (ß [SE] = -0.139 [0.032], proportion mediated [PM] = 28.0%) while the atrophy of the posterior nucleus basalis of Meynert in the BF (ß [SE] = -0.068 [0.029], PM = 13.1%) and hippocampus (ß [SE] = -0.121 [0.033], PM = 23.4%) distinctively influenced Aß-related attention decline. DISCUSSION: These findings highlight the significant role of BF atrophy in the complex pathway linking Aß to cognitive impairment in early stages of AD. Volumetric assessment of BF subregions could be essential in elucidating the relationships between the brain structure and behavior in AD.

Process approach as a cognitive biomarker related to gray matter volume in mild cognitive impairment and Alzheimer's disease.

BACKGROUND: Process approach is valuable for memory assessment in Alzheimer's disease (AD) and mild cognitive impairment (MCI), yet its underlying mechanisms remain elusive. This study aims to synergize the process approach with brain structure analysis to explore both the discriminative capacity and potential mechanisms underlying the process approach. METHODS: 37 subjects of MCI, 35 subjects of AD and 38 subjects of healthy control (HC) were included. The process approach in Auditory Verbal Learning Test (AVLT), including discriminability (A'), response bias (B"D), semantic clustering (LBCsem) and serial clustering (LBCser) was performed. The gray matter volume (GMV) was analyzed by voxel-based morphometry. Receiver operating characteristic (ROC) analysis and partial correlations were conducted to explore the value of the process approach and investigate the relationship between the process approach, traditional indices of AVLT and GMV. RESULTS: ROC analysis showed the value of A', B"D and LBCser in differentiating MCI and AD. Combining AVLT-Immediately Recall (AVLT-IR) and LBCser showed a higher value in diagnosing MCI. Partial correlations revealed that in the MCI group, A' and B"D were mainly positively associated with GMV of the hippocampus and temporal lobe. CONCLUSION: This study indicated that the process approach is a promising cognitive biomarker to detect MCI and AD.

Locus coeruleus integrity and left frontoparietal connectivity provide resilience against attentional decline in preclinical alzheimer's disease.

BACKGROUND: Autopsy work reported that neuronal density in the locus coeruleus (LC) provides neural reserve against cognitive decline in dementia. Recent neuroimaging and pharmacological studies reported that left frontoparietal network functional connectivity (LFPN-FC) confers resilience against beta-amyloid (Aß)-related cognitive decline in preclinical sporadic and autosomal dominant Alzheimer's disease (AD), as well as against LC-related cognitive changes. Given that the LFPN and the LC play important roles in attention, and attention deficits have been observed early in the disease process, we examined whether LFPN-FC and LC structural health attenuate attentional decline in the context of AD pathology. METHODS: 142 participants from the Harvard Aging Brain Study who underwent resting-state functional MRI, LC structural imaging, PiB(Aß)-PET, and up to 5 years of cognitive follow-ups were included (mean age = 74.5 ± 9.9 years, 89 women). Cross-sectional robust linear regression associated LC integrity (measured as the average of five continuous voxels with the highest intensities in the structural LC images) or LFPN-FC with Digit Symbol Substitution Test (DSST) performance at baseline. Longitudinal robust mixed effect analyses examined associations between DSST decline and (i) two-way interactions of baseline LC integrity (or LFPN-FC) and PiB or (ii) the three-way interaction of baseline LC integrity, LFPN-FC, and PiB. Baseline age, sex, and years of education were included as covariates. RESULTS: At baseline, lower LFPN-FC, but not LC integrity, was related to worse DSST performance. Longitudinally, lower baseline LC integrity was associated with a faster DSST decline, especially at PiB > 10.38 CL. Lower baseline LFPN-FC was associated with a steeper decline on the DSST but independent of PiB. At elevated PiB levels (> 46 CL), higher baseline LFPN-FC was associated with an attenuated decline on the DSST, despite the presence of lower LC integrity. CONCLUSIONS: Our findings demonstrate that the LC can provide resilience against Aß-related attention decline. However, when Aß accumulates and the LC's resources may be depleted, the functioning of cortical target regions of the LC, such as the LFPN-FC, can provide additional resilience to sustain attentional performance in preclinical AD. These results provide critical insights into the neural correlates contributing to individual variability at risk versus resilience against Aß-related cognitive decline.

Effects of computerized cognitive training on functional brain networks in patients with vascular cognitive impairment and no dementia.

AIMS: Previous neuroimaging studies of vascular cognitive impairment, no dementia (VCIND), have reported functional alterations, but far less is known about the effects of cognitive training on functional connectivity (FC) of intrinsic connectivity networks (ICNs) and how they relate to intervention-related cognitive improvement. This study provides comprehensive research on the changes in intra- and inter-brain functional networks in patients with VCIND who received computerized cognitive training, with a focus on the underlying mechanisms and potential therapeutic strategies. METHODS: We prospectively collected 60 patients with VCIND who were randomly divided into the training group (N = 30) receiving computerized cognitive training and the control group (N = 30) receiving fixed cognitive training. Functional MRI scans and cognitive assessments were performed at baseline, at the 7-week training, and at the 6-month follow-up. Utilizing templates for ICNs, the study employed a linear mixed model to compare intra- and inter-network FC changes between the two groups. Pearson correlation was applied to calculate the relationship between FC and cognitive function. RESULTS: We found significantly decreased intra-network FC within the default mode network (DMN) following computerized cognitive training at Month 6 (p = 0.034), suggesting a potential loss of functional specialization. Computerized training led to increased functional coupling between the DMN and sensorimotor network (SMN) (p = 0.01) and between the language network (LN) and executive control network (ECN) at Month 6 (p < 0.001), indicating compensatory network adaptations in patients with VCIND. Notably, the intra-LN exhibited enhanced functional specialization after computerized cognitive training (p = 0.049), with significant FC increases among LN regions, which correlated with improvements in neuropsychological measures (p < 0.05), emphasizing the targeted impact of computerized cognitive training on language abilities. CONCLUSIONS: This study provides insights into neuroplasticity and adaptive changes resulting from cognitive training in patients with VCIND, with implications for potential therapeutic strategies.

Regional Burden of Enlarged Perivascular Spaces and Cognition and Neuropsychiatric Symptoms in Drug-Naive Patients With Parkinson Disease.

BACKGROUND AND OBJECTIVES: Although the potential role of enlarged perivascular spaces (EPVSs) in Parkinson disease (PD) is increasingly recognized, whether EPVSs located in different anatomical regions exert differential effects on clinical manifestation remains uncertain. We investigated the regional EPVS burden and its association with cognition and neuropsychiatric symptoms (NPSs) in newly diagnosed PD population. METHODS: In this retrospective, cross-sectional study, EPVS in the temporal lobe (T-EPVS), centrum semiovale (CS-EPVS), and basal ganglia (BG-EPVS) were visually rated in drug-naive patients with PD who underwent magnetic resonance imaging, dopamine transporter (DAT) scans, neuropsychological assessments, and Neuropsychiatric Inventory Questionnaire at baseline. Cognitive performance, NPS burden, vascular risk factors, small vessel disease (SVD) imaging markers, and DAT availability were compared across groups dichotomized by their regional EPVS burden (cutoff for high-degree vs low-degree: >10 for T-EPVS/BG-EPVS and >20 for CS-EPVS). RESULTS: A total of 480 patients with PD (123 without cognitive impairment, 291 with mild cognitive impairment, and 66 with dementia) were included. The proportion of high-degree T-EPVS (p for trend <0.001) and BG-EPVS (p for trend = 0.001) exhibited an increasing trend across the cognitive spectrum, corresponding to worsening cognition. Compared with the low-degree group, the high-degree BG-EPVS group showed higher SVD burden (moderate-to-severe white matter hyperintensity [14.8% vs 40.5%, p < 0.001], lacune [10.3% vs 30.7%, p < 0.001], and cerebral microbleeds [8.1% vs 22.2%, p < 0.001]), greater atrophy in cortical gray matter (40.73% ± 1.09% vs 39.96% ± 1.20% of intracranial volume, p < 0.001), and lower cognitive performance (in language [-0.22 ± 1.18 vs -0.53 ± 1.29, p = 0.013], and visual memory domains [-0.24 ± 0.97 vs -0.61 ± 0.96, p = 0.009]). The high-degree T-EPVS group presented with greater NPS burden in decreased motivation (0.61 ± 1.78 vs 1.35 ± 2.36, p = 0.007), affective dysregulation (0.88 ± 2.13 vs 2.36 ± 3.53, p < 0.001), and impulse dyscontrol (0.43 ± 1.67 vs 1.74 ± 4.29, p < 0.001), compared with the low-degree T-EPVS group. Meanwhile, the burden of CS-EPVS did not reveal any differences in cognition or NPS. DISCUSSION: BG-EPVS and T-EPVS seem to exert differential effects on cognition and NPS in patients with PD. Investigating the EPVS profile in distinct anatomical regions may be useful in disentangling the heterogeneity within PD.

Microscopic fractional anisotropy outperforms multiple sclerosis lesion assessment and clinical outcome associations over standard fractional anisotropy tensor.

We aimed to compare the ability of diffusion tensor imaging and multi-compartment spherical mean technique to detect focal tissue damage and in distinguishing between different connectivity patterns associated with varying clinical outcomes in multiple sclerosis (MS). Seventy-six people diagnosed with MS were scanned using a SIEMENS Prisma Fit 3T magnetic resonance imaging (MRI), employing both conventional (T1w and fluid-attenuated inversion recovery) and advanced diffusion MRI sequences from which fractional anisotropy (FA) and microscopic FA (µFA) maps were generated. Using automated fiber quantification (AFQ), we assessed diffusion profiles across multiple white matter (WM) pathways to measure the sensitivity of anisotropy diffusion metrics in detecting localized tissue damage. In parallel, we analyzed structural brain connectivity in a specific patient cohort to fully grasp its relationships with cognitive and physical clinical outcomes. This evaluation comprehensively considered different patient categories, including cognitively preserved (CP), mild cognitive deficits (MCD), and cognitively impaired (CI) for cognitive assessment, as well as groups distinguished by physical impact: those with mild disability (Expanded Disability Status Scale [EDSS] <=3) and those with moderate-severe disability (EDSS >3). In our initial objective, we employed Ridge regression to forecast the presence of focal MS lesions, comparing the performance of µFA and FA. µFA exhibited a stronger association with tissue damage and a higher predictive precision for focal MS lesions across the tracts, achieving an R-squared value of .57, significantly outperforming the R-squared value of .24 for FA (p-value <.001). In structural connectivity, µFA exhibited more pronounced differences than FA in response to alteration in both cognitive and physical clinical scores in terms of effect size and number of connections. Regarding cognitive groups, FA differences between CP and MCD groups were limited to 0.5% of connections, mainly around the thalamus, while µFA revealed changes in 2.5% of connections. In the CP and CI group comparison, which have noticeable cognitive differences, the disparity was 5.6% for FA values and 32.5% for µFA. Similarly, µFA outperformed FA in detecting WM changes between the MCD and CI groups, with 5% versus 0.3% of connections, respectively. When analyzing structural connectivity between physical disability groups, µFA still demonstrated superior performance over FA, disclosing a 2.1% difference in connectivity between regions closely associated with physical disability in MS. In contrast, FA spotted a few regions, comprising only 0.6% of total connections. In summary, µFA emerged as a more effective tool than FA in predicting MS lesions and identifying structural changes across patients with different degrees of cognitive and global disability, offering deeper insights into the complexities of MS-related impairments.

Cognitive impairment in schizophrenia is associated with prefrontal-striatal functional hypoconnectivity and striatal dopaminergic abnormalities.

BACKGROUND: A better understanding of the mechanisms underlying cognitive impairment in schizophrenia is imperative, as it causes poor functional outcomes and a lack of effective treatments. AIMS: This study aimed to investigate the relationships of two proposed main pathophysiology of schizophrenia, altered prefrontal-striatal connectivity and the dopamine system, with cognitive impairment and their interactions. METHODS: Thirty-three patients with schizophrenia and 27 healthy controls (HCs) who are right-handed and matched for age and sex were recruited. We evaluated their cognition, functional connectivity (FC) between the dorsolateral prefrontal cortex (DLPFC)/middle frontal gyrus (MiFG) and striatum, and the availability of striatal dopamine transporter (DAT) using a cognitive battery investigating attention, memory, and executive function, resting-state functional magnetic resonance imaging with group independent component analysis and single-photon emission computed tomography with 99mTc-TRODAT. RESULTS: Patients with schizophrenia exhibited poorer cognitive performance, reduced FC between DLPFC/MiFG and the caudate nucleus (CN) or putamen, decreased DAT availability in the left CN, and decreased right-left DAT asymmetry in the CN compared to HCs. In patients with schizophrenia, altered imaging markers are associated with cognitive impairments, especially the relationship between DLPFC/MiFG-putamen FC and attention and between DAT asymmetry in the CN and executive function. CONCLUSIONS: This study is the first to demonstrate how prefrontal-striatal hypoconnectivity and altered striatal DAT markers are associated with different domains of cognitive impairment in schizophrenia. More research is needed to evaluate their complex relationships and potential therapeutic implications.

Alterations in structural integrity of superior longitudinal fasciculus III associated with cognitive performance in cerebral small vessel disease.

BACKGROUND: This study aimed to investigate the alterations in structural integrity of superior longitudinal fasciculus subcomponents with increasing white matter hyperintensity severity as well as the relationship to cognitive performance in cerebral small vessel disease. METHODS: 110 cerebral small vessel disease study participants with white matter hyperintensities were recruited. According to Fazekas grade scale, white matter hyperintensities of each subject were graded. All subjects were divided into two groups. The probabilistic fiber tracking method was used for analyzing microstructure characteristics of superior longitudinal fasciculus subcomponents. RESULTS: Probabilistic fiber tracking results showed that mean diffusion, radial diffusion, and axial diffusion values of the left arcuate fasciculus as well as the mean diffusion value of the right arcuate fasciculus and left superior longitudinal fasciculus III in high white matter hyperintensities rating group were significantly higher than those in low white matter hyperintensities rating group (p < 0.05). The mean diffusion value of the left superior longitudinal fasciculus III was negatively related to the Montreal Cognitive Assessment score of study participants (p < 0.05). CONCLUSIONS: The structural integrity injury of bilateral arcuate fasciculus and left superior longitudinal fasciculus III is more severe with the aggravation of white matter hyperintensities. The structural integrity injury of the left superior longitudinal fasciculus III correlates to cognitive impairment in cerebral small vessel disease.

Tau follows principal axes of functional and structural brain organization in Alzheimer's disease.

Alzheimer's disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns ("gradient contraction") are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.