Identification of predictors for mini-mental state examination and revised Hasegawa's Dementia Scale scores using MR-based brain morphometry

Spontaneous brain activity in healthy aging: An overview through fluctuations and regional homogeneity

Introduction

This study aims to explore whole-brain resting-state spontaneous brain activity using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) strategies to find differences among age groups within a population ranging from middle age to older adults.

Methods

The sample comprised 112 healthy persons (M = 68.80, SD = 7.99) aged 48-89 who were split into six age groups (< 60, 60-64, 65-69, 70-74, 75-79, and ≥ 80). Fractional amplitude of low-frequency fluctuation and ReHo analyses were performed and were compared among the six age groups, and the significant results commonly found across groups were correlated with the gray matter volume of the areas and the age variable.

Results

Increased activity was found using fALFF in the superior temporal gyrus and inferior frontal gyrus when comparing the first group and the fifth. Regarding ReHo analysis, Group 6 showed increased ReHo in the temporal lobe (hippocampus), right and left precuneus, right caudate, and right and left thalamus depending on the age group. Moreover, significant correlations between age and fALFF and ReHo clusters, as well as with their gray matter volume were found, meaning that the higher the age, the higher the regional synchronization, the lower the fALFF activation, and the lower gray matter of the right thalamus.

Conclusion

Both techniques have been shown to be valuable and usable tools for disentangling brain changes in activation in a very low interval of years in healthy aging.

A modified mental state assessment tool for impact analysis of virtual reality-based therapeutic interventions in patients with cognitive impairment

Objectives

This work has developed a modified mental state assessment tool for impact analysis of therapeutic interventions for patients with cognitive impairment. This work includes a pilot study to validate the proposed tool and assess the impact of virtual reality-based interventions on patient well-being, which includes assessment of cognitive ability and mood.

Methods

The suggested tool's robustness and reliability are assessed in care home facilities with elderly residents over the age of 55. Because of the repetitive nature of the pilot study, test-retest strategy for Cronbach's alpha coefficient is employed to validate the internal consistency of the proposed tool over time. Qualitative and quantitative analyses are performed on the collected data to draw inferences on the impact of virtual reality-based interventions on patients with cognitive impairments.

Results

The Cronbach's alpha coefficient value shows that the proposed tool's resilience is comparable to that of its pre-intervention counterparts. The Cronbach's alpha coefficient values are determined for Pre-virtual reality and Post-virtual reality interventions, which include 116 virtual reality sessions for 52-participant, and three cohorts of virtual reality sessions for 21 participants. These values for a majority of the interventions remained within the acceptable range of 0.6-0.8.

Conclusions

The proposed modified mental state assessment tool is observed to be a reliable tool for investigating the impact of virtual reality-based interventions on patients with cognitive impairments. One of the notable significance of the proposed tool is that this allows for resource allocation for such interventions to be tailored to the needs of the patient, leading to greater therapeutic efficacy and resource efficiency.

Relationship between finger movement characteristics and brain voxel-based morphometry

Background

Aging is the most significant risk factor for dementia. Alzheimer’s disease (AD) accounts for approximately 60–80% of all dementia cases in older adults. This study aimed to examine the relationship between finger movements and brain volume in AD patients using a voxel-based reginal analysis system for Alzheimer’s disease (VSRAD) software.

Methods

Patients diagnosed with AD at the Center for Comprehensive Care and Research on Memory Disorders were included. The diagnostic criteria were based on the National Institute on Aging-Alzheimer’s Association. A finger-tapping device was used for all measurements. Participants performed the tasks in the following order: with their non-dominant hand, dominant hand, both hands simultaneously, and alternate hands. Movements were measured for 15 s each. The relationship between distance and output was measured. Magnetic resonance imaging measurements were performed, and VSRAD was conducted using sagittal section 3D T1-weighted images. The Z-score was used to calculate the severity of medial temporal lobe atrophy. Pearson’s product-moment correlation coefficient analyzed the relationship between the severity of medial temporal lobe atrophy and mean values of the parameters in the finger-tapping movements. The statistical significance level was set at <5%. The calculated p-values were corrected using the Bonferroni method.

Results

Sixty-two patients were included in the study. Comparison between VSRAD and MoCA-J scores corrected for p-values showed a significant negative correlation with the extent of gray matter atrophy (r = -0. 52; p< 0.001). A positive correlation was observed between the severity of medial temporal lobe atrophy and standard deviation (SD) of the distance rate of velocity peak in extending movements in the non-dominant hand (r = 0. 51; p< 0.001).

Conclusions

The SD of distance rate of velocity peak in extending movements extracted from finger taps may be a useful parameter for the early detection of AD and diagnosis of its severity.

Right entorhinal cortical thickness is associated with Mini-Mental State Examination scores from multi-country datasets using MRI

PURPOSE

To discover common biomarkers correlating with the Mini-Mental State Examination (MMSE) scores from multi-country MRI datasets.

METHODS

The first dataset comprised 112 subjects (49 men, 63 women; range, 46-94 years) at the National Hospital Organization Kyushu Medical Center. A second dataset comprised 300 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (177 men, 123 women; range, 57-91 years). Three-dimensional T1-weighted MR images were collected from both datasets. In total, 14 deep gray matter volumes and 70 cortical thicknesses were obtained from MR images using FreeSurfer software. Total hippocampal volume and the ratio of hippocampus to cerebral volume were also calculated. Correlations between each variable and MMSE scores were assessed using Pearson's correlation coefficient. Parameters with moderate correlation coefficients (r > 0.3) from each dataset were determined as independent variables and evaluated using general linear model (GLM) analyses.

RESULTS

In Pearson's correlation coefficient, total and bilateral hippocampal volumes, right amygdala volume, and right entorhinal cortex (ERC) thickness showed moderate correlation coefficients (r > 0.3) with MMSE scores from the first dataset. The ADNI dataset showed moderate correlations with MMSE scores in more variables, including bilateral ERC thickness and hippocampal volume. GLM analysis revealed that right ERC thickness correlated significantly with MMSE score in both datasets. Cortical thicknesses of the left parahippocampal gyrus, left inferior parietal lobe, and right fusiform gyrus also significantly correlated with MMSE score in the ADNI dataset (p < 0.05).

CONCLUSION

A positive correlation between right ERC thickness and MMSE score was identified from multi-country datasets.