Takahashi Hiroto, Takami Yoichi, Takeda Shuko, Hayakawa Naoki, Nakajima Tsuneo, Takeya Yasushi, Matsuo-Hagiyama Chisato, Arisawa Atsuko, Rakugi Hiromi, Tomiyama Noriyuki
From the Department of Diagnostic and Interventional Radiology (H.T., C.M.-H., A.A., N.T.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
Department of Geriatric and General Medicine (Y. Takami, N.H., T.N., Y. Takeya, H.R.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
AJNR Am J Neuroradiol. 2024 Mar 7;45(3):320-327. doi: 10.3174/ajnr.A8106.
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, = 35) or absence (non-Alzheimer disease group, = 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 (< .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方面的效用。
69例轻度认知障碍患者在3T条件下同时进行了脑脊液测量和多壳层扩散成像。根据脑脊液生物标志物水平，患者按是否存在阿尔茨海默病病理分为两组（阿尔茨海默病组，n = 35；非阿尔茨海默病组，n = 34）。生成了神经突方向离散度与密度成像（NODDI）和扩散张量成像（DTI）参数图。两名观察者独立创建海马感兴趣区以计算直方图特征。计算观察者间的相关性。采用曼-惠特尼U检验来检验组间差异的统计学意义。使用临床量表和图像数据进行逻辑回归分析以预测组间差异，之后进行组间判别。
大多数组内相关系数值在0.�9至0.91之间。在两名观察者的感兴趣区内，左侧NODDI衍生的细胞内体积分数、右侧DTI衍生的平均扩散率、左侧DTI衍生的平均扩散率、轴向扩散率和径向扩散率存在统计学显著的组间差异（P < 0.05）。逻辑回归模型显示，扩散参数对组间判别贡献最大。观察者A/B感兴趣区的受试者工作特征曲线下面积，左侧细胞内体积分数（平均值）为0.69/0.68，右侧平均扩散率（平均值）为0.69/0.68，左侧平均扩散率（第10百分位数）为0.73/0.68，轴向扩散率（第10百分位数）为0.71/0.68，径向扩散率（平均值）为0.68/0.68。
海马扩散参数可能有助于阿尔茨海默病的早期诊断。
