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Introduction: Hippocampal volume loss occurs physiologically with age, but an accelerated rate of volume loss is linked to neurodegenerative diseases. While evidence suggests that cross-sectional study designs tend to underestimate hippocampal atrophy rates compared to longitudinal approaches, few studies have directly examined the relationship between these two methods in the context of brain aging. This study aims to investigate the association between baseline hippocampal z-scores and hippocampal volume loss over time in a cohort of healthy older adults.

Methods: 182 healthy elderly subjects (mean age: 73.4 +/- 3.5 years) who underwent structural Magnetic resonance imaging (MRI) at two timepoints (mean time between the scans 4.8 +/- 1.0 years) were included. A subset of participants (n = 103) also completed Positron emission tomography (PET) amyloid imaging. Hippocampal volumes were measured at baseline and follow-up using FreeSurfer (v7.1.1). Baseline volumes were adjusted for age and intracranial volume (ICV) and converted into z-scores. The annualized percent change (APC) in hippocampal volume was calculated for each participant. Neuropsychological assessments were conducted at baseline, 18, and 54 months, and APOE genotyping was performed. Correlation analyses examined the relationship between baseline hippocampal volumes and APC, while multiple regression models explored potential influencing factors.

Results: Hippocampal volumes decreased from baseline to follow-up [mean APC (SD): right -1.34% (0.94), left: -1.79% (1.00)]. Small, but statistically significant positive correlations were found between baseline hippocampal z-scores and APC of hippocampal volumes over time, indicating that the lower the volume at baseline, the greater the atrophy rate to timepoint two (right hippocampus: r = 0.17, p = 0.01; left hippocampus: r = 0.14, p = 0.03). No covariates significantly influenced this association (p > 0.05).

Conclusion: Lower baseline hippocampal z-scores are associated with a greater rate of hippocampal atrophy to the follow-up examination. If validated in larger cohorts, these findings could help establish cut-off values for pathological atrophy in cross-sectional studies.

ObjectiveAlzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-epsilon 4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults.MethodsWithin the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 +/- 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid beta 1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 +/- 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract.ResultsAD pathology, APOE-epsilon 4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-epsilon 4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect.InterpretationOur results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.

INTRODUCTION: Unraveling how Alzheimer's disease (AD) genetic risk is related to neuropathological heterogeneity, and whether this occurs through specific biological pathways, is a key step toward precision medicine.

METHODS: We computed pathway-specific genetic risk scores (GRSs) in non-demented individuals and investigated how AD risk variants predict cerebrospinal fluid (CSF) and imaging biomarkers reflecting AD pathology, cardiovascular, white matter integrity, and brain connectivity.

RESULTS: CSF amyloidbeta and phosphorylated tau were related to most GRSs. Inflammatory pathways were associated with cerebrovascular disease, whereas quantitative measures of white matter lesion and microstructure integrity were predicted by clearance and migration pathways. Functional connectivity alterations were related to genetic variants involved in signal transduction and synaptic communication.

DISCUSSION: This study reveals distinct genetic risk profiles in association with specific pathophysiological aspects in predementia stages of AD, unraveling the biological substrates of the heterogeneity of AD-associated endophenotypes and promoting a step forward in disease understanding and development of personalized therapies.

HIGHLIGHTS: Polygenic risk for Alzheimer's disease encompasses six biological pathways that can be quantified with pathway-specific genetic risk scores, and differentially relate to cerebrospinal fluid and imaging biomarkers. Inflammatory pathways are mostly related to cerebrovascular burden. White matter health is associated with pathways of clearance and membrane integrity, whereas functional connectivity measures are related to signal transduction and synaptic communication pathways.

Background and Objectives

Vascular risk factors (VRFs) and cerebral small vessel disease (cSVD) are common in patients with Alzheimer disease (AD). It remains unclear whether this coexistence reflects shared risk factors or a mechanistic relationship and whether vascular and amyloid pathologies have independent or synergistic influence on subsequent AD pathophysiology in preclinical stages. We investigated links between VRFs, cSVD, and amyloid levels (Aβ_1-42) and their combined effect on downstream AD biomarkers, that is, CSF hyperphosphorylated tau (P-tau₁₈₁), atrophy, and cognition.

Methods

This retrospective study included nondemented participants (Clinical Dementia Rating < 1) from the European Prevention of Alzheimer's Dementia (EPAD) cohort and assessed VRFs with the Framingham risk score (FRS) and cSVD features on MRI using visual scales and white matter hyperintensity volumes. After preliminary linear analysis, we used structural equation modeling (SEM) to create a “cSVD severity” latent variable and assess the direct and indirect effects of FRS and cSVD severity on Aβ_1-42, P-tau₁₈₁, gray matter volume (baseline and longitudinal), and cognitive performance (baseline and longitudinal).

Results

A total cohort of 1,592 participants were evaluated (mean age = 65.5 ± 7.4 years; 56.16% F). We observed positive associations between FRS and all cSVD features (all p < 0.05) and a negative association between FRS and Aβ_1-42 (β = −0.04 ± 0.01). All cSVD features were negatively associated with CSF Aβ_1-42 (all p < 0.05). Using SEM, the cSVD severity fully mediated the association between FRS and CSF Aβ_1-42 (indirect effect: β = −0.03 ± 0.01), also when omitting vascular amyloid-related markers. We observed a significant indirect effect of cSVD severity on P-tau₁₈₁ (indirect effect: β = 0.12 ± 0.03), baseline and longitudinal gray matter volume (indirect effect: β = −0.10 ± 0.03; β = −0.12 ± 0.05), and baseline cognitive performance (indirect effect: β = −0.16 ± 0.03) through CSF Aβ_1-42.

Discussion

In a large nondemented population, our findings suggest that cSVD is a mediator of the relationship between VRFs and CSF Aβ_1-42 and affects downstream neurodegeneration and cognitive impairment. We provide evidence of VRFs indirectly affecting the pathogenesis of AD, highlighting the importance of considering cSVD burden in memory clinics for AD risk evaluation and as an early window for intervention. These results stress the role of VRFs and cerebrovascular pathology as key biomarkers for accurate design of anti-amyloid clinical trials and offer new perspectives for patient stratification.

We compared different LLMs, notably chatGPT, GPT4, and Google Bard and we tested whether their performance differs in subspeciality domains, in executing examinations from four different courses of the European Society of Neuroradiology (ESNR) notably anatomy/embryology, neuro-oncology, head and neck and pediatrics. Written exams of ESNR were used as input data, related to anatomy/embryology (30 questions), neuro-oncology (50 questions), head and neck (50 questions), and pediatrics (50 questions). All exams together, and each exam separately were introduced to the three LLMs: chatGPT 3.5, GPT4, and Google Bard. Statistical analyses included a group-wise Friedman test followed by a pair-wise Wilcoxon test with multiple comparison corrections. Overall, there was a significant difference between the 3 LLMs (p < 0.0001), with GPT4 having the highest accuracy (70%), followed by chatGPT 3.5 (54%) and Google Bard (36%). The pair-wise comparison showed significant differences between chatGPT vs GPT 4 (p < 0.0001), chatGPT vs Bard (p < 0. 0023), and GPT4 vs Bard (p < 0.0001). Analyses per subspecialty showed the highest difference between the best LLM (GPT4, 70%) versus the worst LLM (Google Bard, 24%) in the head and neck exam, while the difference was least pronounced in neuro-oncology (GPT4, 62% vs Google Bard, 48%). We observed significant differences in the performance of the three different LLMs in the running of official exams organized by ESNR. Overall GPT 4 performed best, and Google Bard performed worst. This difference varied depending on subspeciality and was most pronounced in head and neck subspeciality.

Background: Impaired cognitive ability is one of the most frequently reported neuropsychiatric symptoms in the post-COVID phase among patients. It is unclear whether this condition is related to structural or functional brain changes.

Purpose: In this study, we present a multimodal magnetic resonance imaging study of 36 post-COVID patients and 36 individually matched controls who had a mild form of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) infection from March 2020 to February 2022. This study aimed to investigate structural and functional brain alterations and their correlation with post-COVID symptoms and neurocognitive functions.

Materials and methods: The study protocol comprised an assessment of physical fatigue [Fatigue Severity Scale (FSS)], mental fatigue (Mental Fatigue Scale (MFS)], depression [Montgomery Asberg Depression Rating Scale (MADRS)], anxiety [Hospital Anxiety and Depression Scale (HAD)], post-COVID Symptoms Severity Score, and neurocognitive status [Repeatable Battery for the Assessment of Neuropsychological Status Update (RBANS)]. The magnetic resonance imaging protocol included morphological sequences, arterial spin labeling (ASL) and dynamic susceptibility contrast-enhanced (DSC) perfusion, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (fMRI) sequences. Using these protocols, the assessments of macrostructural abnormalities, perfusion, gray matter density, white matter integrity, and brain connectivity were performed.

Results: Post-COVID patients had higher levels of physical fatigue, mental fatigue, depression, and anxiety than controls and showed cognitive impairment in all the RBANS domains except in Visuospatial/Construction. The subjective mental fatigue correlated with objective impaired cognitive ability in the RBANS test, particularly in the Attention domain. There were no differences between patients and controls regarding macrostructural abnormalities, regional volumes, regional perfusion metrics, gray matter density, or DTI parameters. We observed a significant positive correlation between RBANS Total Scale Index score and gray matter volume in the right superior/middle-temporal gyrus (p < 0.05) and a significant negative correlation between the white matter integrity and post-COVID symptoms (p < 0.05) in the same area. The connectivity differences were observed between patients and controls in a few regions, including the right middle frontal gyrus, an important area of convergence of the dorsal and ventral attention networks. We also noted a positive correlation between post-COVID symptoms and increased connectivity in the right temporoparietal junction, which is part of the ventral attention system.

Conclusion: In non-hospitalized subjects with post-COVID, we did not find any structural brain changes or changes in perfusion, compared to controls. However, we noted differences in connectivity within an important area for attention processes, which may be associated with post-COVID brain fog.

Background

Cognitive behavioral therapy (CBT) is the current standard treatment for chronic severe tinnitus; however, preliminary evidence suggests that real-time functional MRI (fMRI) neurofeedback therapy may be more effective.

Purpose

To compare the efficacy of real-time fMRI neurofeedback against CBT for reducing chronic tinnitus distress.

Materials and Methods

In this prospective controlled trial, participants with chronic severe tinnitus were randomized from December 2017 to December 2021 to receive either CBT (CBT group) for 10 weekly group sessions or real-time fMRI neurofeedback (fMRI group) individually during 15 weekly sessions. Change in the Tinnitus Handicap Inventory (THI) score (range, 0-100) from baseline to 6 or 12 months was assessed. Secondary outcomes included four quality-of-life questionnaires (Beck Depression Inventory, Pittsburgh Sleep Quality Index, State-Trait Anxiety Inventory, and World Health Organization Disability Assessment Schedule). Questionnaire scores between treatment groups and between time points were assessed using repeated measures analysis of variance and the nonparametric Wilcoxon signed rank test.

Results

The fMRI group included 21 participants (mean age, 49 years ± 11.4 [SD]; 16 male participants) and the CBT group included 22 participants (mean age, 53.6 years ± 8.8; 16 male participants). The fMRI group showed a greater reduction in THI scores compared with the CBT group at both 6 months (mean score change, -28.21 points ± 18.66 vs -12.09 points ± 18.86; P = .005) and 12 months (mean score change, -30 points ± 25.44 vs -4 points ± 17.2; P = .01). Compared with baseline, the fMRI group showed improved sleep (mean score, 8.62 points ± 4.59 vs 7.25 points ± 3.61; P = .006) and trait anxiety (mean score, 44 points ± 11.5 vs 39.84 points ± 10.5; P = .02) at 1 month and improved depression (mean score, 13.71 points ± 9.27 vs 6.53 points ± 5.17; P = .01) and general functioning (mean score, 24.91 points ± 17.05 vs 13.06 points ± 10.1; P = .01) at 6 months. No difference in these metrics over time was observed for the CBT group (P value range, .14 to >.99).

Conclusion

Real-time fMRI neurofeedback therapy led to a greater reduction in tinnitus distress than the current standard treatment of CBT.