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.

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

PURPOSE: The early detection of cognitive function decline is crucial to help manage or slow the progression of symptoms. The Mini-Mental State Examination (MMSE) and revised Hasegawa's Dementia Scale (HDS-R) are widely used in screening for cognitive impairment. The purpose of this study was to explore common predictors of the two different cognitive testing systems using MR-based brain morphometry. MATERIALS AND METHODS: This retrospective study included 200 subjects with clinical suspicion of cognitive impairment who underwent 3D T1-weighted MRI at our institution between February 2019 and August 2020. Variables related to the volume of deep gray matter and 70 cortical thicknesses were obtained from the MR images using voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) and FreeSurfer software. The correlation between each variable including age and MMSE/HDS-R scores was evaluated using uni- and multi-variate logistic regression analyses. RESULTS: In univariate analysis, parameters include hippocampal volume and bilateral entorhinal cortex (ERC) thickness showed moderate correlation coefficients with both MMSE and HDS-R scores. Multivariate analysis demonstrated the right ERC thickness was the common parameter which significantly correlates with both MMSE and HDS-R scores (p < 0.05). CONCLUSION: Right ERC thickness appears to offer a useful predictive biomarker for both MMSE and HDS-R scores.

A new physical route to produce monodispersed microsphere nanoparticle-polymer composites.

A new physical route for the production of monodispersed microsphere nanoparticle-polymer composites utilizing a beads milling method, followed by an electrospray method, has been developed. Poly(methyl methacrylate) (PMMA)-TiO2 composites were used as a model to evaluate the performance of this route. SEM images showed that the products were monodispersed, spherical, and nonagglomerate. The mean diameter was in the range of 0.25-1.87 microm, with a standard deviation of 0.06-0.172. TEM images confirmed that nonagglomerated TiO2 nanoparticles were highly dispersed inside the polymer matrices. We found that the concentration ratio of TiO2 to polymer in the precursor led to changes in precursor properties, such as permittivity and electrical conductivity, and resulted in changes in the produced particle size.