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.

中文翻译：

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右侧内嗅皮质厚度与使用 MRI 的多国数据集的简易精神状态检查分数相关

目的

从多国 MRI 数据集中发现与简易精神状态检查 (MMSE) 分数相关的常见生物标志物。

方法

第一个数据集包括国立医院组织九州医疗中心的 112 名受试者（49 名男性，63 名女性；范围，46-94 岁）。第二个数据集包括来自阿尔茨海默病神经影像学倡议 (ADNI) 数据库的 300 名受试者（177 名男性，123 名女性；范围，57-91 岁）。从两个数据集中收集了三维 T1 加权 MR 图像。使用 FreeSurfer 软件从 MR 图像中总共获得了 14 个深灰质体积和 70 个皮质厚度。还计算了总海马体积和海马体积与脑体积的比值。使用 Pearson 相关系数评估每个变量和 MMSE 分数之间的相关性。相关系数适中的参数 ( r> 0.3) 将每个数据集确定为独立变量，并使用一般线性模型 (GLM) 分析进行评估。

结果

在 Pearson 的相关系数中，总和双侧海马体积、右侧杏仁核体积和右侧内嗅皮质 (ERC) 厚度与第一个数据集的 MMSE 评分显示中等相关系数 ( r > 0.3)。ADNI 数据集在更多变量（包括双侧 ERC 厚度和海马体积）中显示出与 MMSE 评分的中度相关性。GLM 分析显示，右侧 ERC 厚度与两个数据集中的 MMSE 评分显着相关。左侧海马旁回、左侧顶下叶和右侧梭状回的皮质厚度也与 ADNI 数据集中的 MMSE 评分显着相关（p < 0.05）。

结论

从多国数据集中确定了右侧 ERC 厚度与 MMSE 评分之间的正相关。