Biomarkers have been required for diagnosing early Alzheimer disease. We assessed the utility of hippocampal diffusion parameters for diagnosing Alzheimer disease pathology in mild cognitive impairment.

Sixty-nine patients with mild cognitive impairment underwent both CSF measurement and multi-shell diffusion imaging at 3T. Based on the CSF biomarker level, patients were classified according to the presence (Alzheimer disease group, n = 35) or absence (non-Alzheimer disease group, n = 34) of Alzheimer disease pathology. Neurite orientation dispersion and density imaging and diffusion tensor imaging parametric maps were generated. Two observers independently created the hippocampal region of interest for calculating histogram features. Interobserver correlations were calculated. The statistical significance of intergroup differences was tested by using the Mann-Whitney U test. Logistic regression analyses, using both the clinical scale and the image data, were used to predict intergroup differences, after which group discriminations were performed.

Most intraclass correlation coefficient values were between 0.59 and 0.91. In the regions of interest of both observers, there were statistically significant intergroup differences for the left-side neurite orientation dispersion and density imaging–derived intracellular volume fraction, right-side diffusion tensor imaging-derived mean diffusivity, left-side diffusion tensor imaging–derived mean diffusivity, axial diffusivity, and radial diffusivity (P < .05). Logistic regression models revealed that diffusion parameters contributed the most to discriminating between the groups. The areas under the receiver operating characteristic curve for the regions of interest of observers A/B were 0.69/0.68, 0.69/0.68, 0.73/0.68, 0.71/0.68, and 0.68/0.68 for the left-side intracellular volume fraction (mean), right-side mean diffusivity (mean), left-side mean diffusivity (10th percentile), axial diffusivity (10th percentile), and radial diffusivity (mean).

Hippocampal diffusion parameters might be useful for the early diagnosis of Alzheimer disease.

诊断早期阿尔茨海默病需要生物标志物。我们评估了海马扩散参数在诊断轻度认知障碍中阿尔茨海默病病理学中的效用。

69 名患有轻度认知障碍的患者接受了 CSF 测量和 3T 多壳扩散成像。根据脑脊液生物标志物水平，根据阿尔茨海默病病理学的存在（阿尔茨海默病组，n = 35）或不存在（非阿尔茨海默病组，n = 34）对患者进行分类。生成神经突定向分散和密度成像以及扩散张量成像参数图。两名观察者独立创建海马感兴趣区域以计算直方图特征。计算观察者间的相关性。使用Mann-Whitney U 检验检验组间差异的统计显着性。使用临床量表和图像数据进行逻辑回归分析来预测组间差异，然后进行组歧视。

大多数组内相关系数值在 0.59 至 0.91 之间。在两名观察者的感兴趣区域中，左侧神经突方向分散度和密度成像衍生的细胞内体积分数、右侧扩散张量成像衍生的平均扩散率、左侧扩散张量成像的组间差异具有统计学意义。得出平均扩散率、轴向扩散率和径向扩散率 ( P < .05)。逻辑回归模型显示，扩散参数对区分组别贡献最大。观察者 A/B 感兴趣区域的受试者工作特征曲线下面积分别为 0.69/0.68、0.69/0.68、0.73/0.68、0.71/0.68 和 0.68/0.68（左侧细胞内体积分数） 、右侧平均扩散率（平均值）、左侧平均扩散率（第 10 个百分点）、轴向扩散率（第 10 个百分点）和径向扩散率（平均值）。

海马扩散参数可能有助于阿尔茨海默病的早期诊断。