Fornix Integrity Is Differently Associated With Cognition in Healthy Aging and Non-amnestic Mild Cognitive Impairment: A Pilot Diffusion Tensor Imaging Study in Thai Older Adults

Lifespan trajectories of fornix volume and tractography: a 5.0 T MRI study

The fornix, playing a critical role in memory formation and maintenance, is recognized as an ultra-early biomarker for dementia. However, its trajectory during healthy aging remains incompletely understood. This study employed an ultra-high-field 5.0 T MRI to acquire high-resolution anatomical and multishell diffusion imaging data from 376 healthy adults aged 18 to 85. The aim was to correlate fornix characteristics with cognitive performance across multiple domains and map its lifespan trajectories. Using these data, we quantified fornix volume and tractography. Lifespan trajectories were identified by computing age-specific average patterns, which revealed distinct changes. Notably, nonlinear declines in fornix volume were observed, contrasting with fiber tract peaks between ages 18 to 40, which subsequently influenced volume-connectivity interactions. Additionally, a shift from predominant left-side to right-side fornix dominance was noted with aging. Regression analyses indicated that variations in fornix structure significantly moderated, rather than mediated, age-related differences in cognitive performance. These high-resolution imaging results provide novel insights into the role of the fornix's morphology and structural connectivity in individual cognitive differences and aging.

White matter correlates of cognition: A diffusion magnetic resonance imaging study

BACKGROUND

Our comprehension of the interplay of cognition and the brain remains constrained. While functional imaging studies have identified cognitive brain regions, structural correlates of cognitive functions remain underexplored. Advanced methods like Diffusion Magnetic Resonance Imaging (DMRI) facilitate the exploration of brain connectivity and White Matter (WM) tract microstructure. Therefore, we conducted connectometry method on DMRI data, to reveal WM tracts associated with cognition.

METHODS

125 healthy participants from the National Institute of Mental Health Intramural Healthy Volunteer Dataset were recruited. Multiple regression analyses were conducted between DMRI-derived Quantitative Anisotropy (QA) values within WM tracts and scores of participants in Flanker Inhibitory Control and Attention Test (attention), Dimensional Change Card Sort (executive function), Picture Sequence Memory Test (episodic memory), and List Sorting Working Memory Test (working memory) tasks from National Institute of Health toolbox. The significance level was set at False Discovery Rate (FDR)<0.05.

RESULTS

We identified significant positive correlations between the QA of WM tracts within the left cerebellum and bilateral fornix with attention, executive functioning, and episodic memory (FDR=0.018, 0.0002, and 0.0002, respectively), and a negative correlation between QA of WM tracts within bilateral cerebellum with attention (FDR=0.028). Working memory demonstrated positive correlations with QA of left inferior longitudinal and left inferior fronto-occipital fasciculi (FDR=0.0009), while it showed a negative correlation with QA of right cerebellar tracts (FDR=0.0005).

CONCLUSION

Our results underscore the intricate link between cognitive performance and WM integrity in frontal, temporal, and cerebellar regions, offering insights into early detection and targeted interventions for cognitive disorders.

Hippocampal atrophy and white matter lesions characteristics can predict evolution to dementia in patients with vascular mild cognitive impairment

BACKGROUND

Vascular mild cognitive impairment (VMCI) is a transitional condition that may evolve into Vascular Dementia(VaD). Hippocampal volume (HV) is suggested as an early marker for VaD, the role of white matter lesions (WMLs) in neurodegeneration remains debated.

OBJECTIVES

Evaluate HV and WMLs as predictive markers of VaD in VMCI patients by assessing: (i)baseline differences in HV and WMLs between converters to VaD and non-converters, (ii) predictive power of HV and WMLs for VaD, (iii) associations between HV, WMLs, and cognitive decline, (iv)the role of WMLs on HV.

METHODS

This longitudinal multicenter study included 110 VMCI subjects (mean age:74.33 ± 6.63 years, 60males/50females) from the VMCI-Tuscany Study database. Subjects underwent brain MRI and cognitive testing, with 2-year follow-up data on VaD progression. HV and WMLs were semi-automatically segmented and measured. ANCOVA assessed group differences, while linear and logistic regression models evaluated predictive power.

RESULTS

After 2 years, 32/110 VMCI patients progressed to VaD. Converting patients had lower HV(p = 0.015) and higher lesion volumes in the posterior thalamic radiation (p = 0.046), splenium of the corpus callosum (p = 0.016), cingulate gyrus (p = 0.041), and cingulum hippocampus(p = 0.038). HV alone did not fully explain progression (p = 0.059), but combined with WMLs volume, the model was significant (p = 0.035). The best prediction model (p = 0.001) included total HV (p = 0.004) and total WMLs volume of the posterior thalamic radiation (p = 0.005) and cingulate gyrus (p = 0.005), achieving 80% precision, 81% specificity, and 74% sensitivity. Lower HV were linked to poorer performance on the Rey Auditory-Verbal Learning Test delayed recall (RAVLT) and Mini Mental State Examination (MMSE).

CONCLUSIONS

HV and WMLs are significant predictors of progression from VMCI to VaD. Lower HV correlate with worse cognitive performance on RAVLT and MMSE tests.

The White Matter Integrity and Functional Connection Differences of Fornix (Cres)/Stria Terminalis in Individuals with Mild Cognitive Impairment Induced by Occupational Aluminum Exposure

Long-term aluminum (Al) exposure increases the risk of mild cognitive impairment (MCI). The aim of the present study was to investigate the neural mechanisms of Al-induced MCI. In our study, a total of 52 individuals with occupational Al exposure >10 years were enrolled and divided into two groups: MCI (Al-MCI) and healthy controls (Al-HC). Plasma Al concentrations and Montreal Cognitive Assessment (MoCA) score were collected for all participants. And diffusion tensor imaging and resting-state functional magnetic resonance imaging were used to examine changes of white matter (WM) and functional connectivity (FC). There was a negative correlation between MoCA score and plasma Al concentration. Compared with the Al-HC, fractional anisotropy value for the right fornix (cres)/stria terminalis (FX/ST) was higher in the Al-MCI. Furthermore, there was a difference in FC between participants with and without MCI under Al exposure. We defined the regions with differing FC as a "pathway," specifically the connectivity from the right temporal pole to the right FX/ST, then to the right sagittal stratum, and further to the right anterior cingulate and paracingulate gyri and right inferior frontal gyrus, orbital part. In summary, we believe that the observed differences in WM integrity and FC in the right FX/ST between participants with and without MCI under long-term Al exposure may represent the neural mechanisms underlying MCI induced by Al exposure.

A deep neural network estimation of brain age is sensitive to cognitive impairment and decline

The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62×10-32; T1: r=0.61, p=1.45×10-26, FW+T1: r=0.77, p=6.48×10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: β=-1.094, p=6.32×10-7; T1: β=-1.331, p=6.52×10-7; FW+T1: β=-1.476, p=2.53×10-10; executive function, FW: β=-1.276, p=1.46×10-9; T1: β=-1.337, p=2.52×10-7; FW+T1: β=-1.850, p=3.85×10-17) and longitudinal cognition (memory, FW: β=-0.091, p=4.62×10-11; T1: β=-0.097, p=1.40×10-8; FW+T1: β=-0.101, p=1.35×10-11; executive function, FW: β=-0.125, p=1.20×10-10; T1: β=-0.163, p=4.25×10-12; FW+T1: β=-0.158, p=1.65×10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline.

Characterization of diffusion magnetic resonance imaging revealing relationships between white matter disconnection and behavioral disturbances in mild cognitive impairment: a systematic review

White matter disconnection is the primary cause of cognition and affection abnormality in mild cognitive impairment (MCI). Adequate understanding of behavioral disturbances, such as cognition and affection abnormality in MCI, can help to intervene and slow down the progression of Alzheimer's disease (AD) promptly. Diffusion MRI is a non-invasive and effective technique for studying white matter microstructure. This review searched the relevant papers published from 2010 to 2022. Sixty-nine studies using diffusion MRI for white matter disconnections associated with behavioral disturbances in MCI were screened. Fibers connected to the hippocampus and temporal lobe were associated with cognition decline in MCI. Fibers connected to the thalamus were associated with both cognition and affection abnormality. This review summarized the correspondence between white matter disconnections and behavioral disturbances such as cognition and affection, which provides a theoretical basis for the future diagnosis and treatment of AD.

Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review

Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.

The Value of Clock Drawing Process Assessment in Screening for Mild Cognitive Impairment and Alzheimer's Dementia

Many clock drawing test (CDT) scoring systems focus on drawing results and lack drawing process assessments. This study created a CDT scoring procedure with drawing process assessment and explored its diagnostic value in screening for mild cognitive impairment (MCI) and early Alzheimer's disease (AD) from normal control (NC). We used logistic regression and receiver operating characteristic (ROC) curves to determine a new, sensitive scoring system for AD and MCI patients in a derivation cohort. The new scoring method was then compared to two common scoring systems and externally validated in a second cohort. We developed a new scoring system named CDT5, which contained one process assessment item: remember setting time without asking. Compared with two published scoring systems, CDT5 had better discriminatory power in distinguishing AD patients from NCs in derivation (area under the ROC curve [area under the curve, AUC] = .890) and validation (AUC = .867) cohorts. Three scoring systems had poor diagnostic accuracy at discriminating MCI patients from controls, with CDT5 being the most sensitive (78.57%). Adding the drawing process in CDT helps accurately detect patients with early AD, but its role in identifying patients with MCI needs to be further explored.

Diffusion tensor tractography of the fornix in cerebral amyloid angiopathy, mild cognitive impairment and Alzheimer's disease

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The fornix was delineated with deterministic tractography from diffusion tensor images (DTI).

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Fornix diffusion changes were found in the fornix in CAA, AD and MCI compared to controls.

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Higher fornix diffusivity correlated with smaller hippocampal volume and larger ventricles.

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Fornix diffusion measures correlated with cognitive measures in the combined disease groups.

Purpose

Cerebral amyloid angiopathy (CAA) is a common neuropathological finding and clinical entity that occurs independently and with co-existent Alzheimer’s disease (AD) and small vessel disease. We compared diffusion tensor imaging (DTI) metrics of the fornix, the primary efferent tract of the hippocampus between CAA, AD and Mild Cognitive Impairment (MCI) and healthy controls.

Methods

Sixty-eight healthy controls, 32 CAA, 21 AD, and 26 MCI patients were recruited at two centers. Diffusion tensor images were acquired at 3 T with high spatial resolution and fluid-attenuated inversion recovery (FLAIR) to suppress cerebrospinal fluid (CSF) and minimize partial volume effects on the fornix. The fornix was delineated with deterministic tractography to yield mean diffusivity (MD), axial diffusivity (AXD), radial diffusivity (RD), fractional anisotropy (FA) and tract volume. Volumetric measurements of the hippocampus, thalamus, and lateral ventricles were obtained using T1-weighted MRI.

Results

Diffusivity (MD, AXD, and RD) of the fornix was highest in AD followed by CAA compared to controls; the MCI group was not significantly different from controls. FA was similar between groups. Fornix tract volume was ∼ 30% lower for all three patient groups compared to controls, but not significantly different between the patient groups. Thalamic and hippocampal volumes were preserved in CAA, but lower in AD and MCI compared to controls. Lateral ventricular volumes were increased in CAA, AD and MCI. Global cognition, memory, and executive function all correlated negatively with fornix diffusivity across the combined clinical group.

Conclusion

There were significant diffusion changes of the fornix in CAA, AD and MCI compared to controls, despite relatively intact thalamic and hippocampal volumes in CAA, suggesting the mechanisms for fornix diffusion abnormalities may differ in CAA compared to AD and MCI.

DWI Hyperintensity in the Fornix Fimbria on MRI in Children

BACKGROUND AND PURPOSE

The fornix-fimbria complex is mainly involved in emotions and memory. In brain MR imaging studies of young children, we have occasionally noted DWI hyperintensity in this region. The significance of this finding remains unclear. This study evaluated the DWI signal in the fornix-fimbria complex of children 0-2 years of age, including the frequency of signal hyperintensity and clinical context.

MATERIALS AND METHODS

Brain MR imaging of 714 children 0-2 years of age (mean, 11 months), performed between September 2018 and May 2021, was reviewed and evaluated for DWI signal changes in the fornix-fimbria. All children with available MR imaging studies including DWI were included. Children with poor image quality, poor visualization of the fornix-fimbria region, and missing medical data were excluded. Additional imaging findings were also evaluated. Demographic data were retrieved from the medical files. We compared the ADC values of the fimbria and fornix between children with and without signal changes. The unpaired 2-tailed Student t test and χ² test were used for statistical analysis.

RESULTS

DWI signal hyperintensity of the Fornix-fimbria complex was noted in 53 (7.4%) children (mean age, 10 months). Their mean ADC values were significantly lower than those of the children with normal DWI findings (P < .05). About half of the children had otherwise normal MR imaging findings. When detected, the most common abnormality was parenchymal volume loss (15%). The most common indication for imaging was seizures (26.5%).

CONCLUSIONS

DWI hyperintensity in the fornix-fimbria complex was detected in 7.4% of children 0-2 years of age. The etiology is not entirely clear, possibly reflecting a transient phenomenon.