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首页> 美国卫生研究院文献>Frontiers in Neurology >Multiple Visual Rating Scales Based on Structural MRI and a Novel Prediction Model Combining Visual Rating Scales and Age Stratification in the Diagnosis of Alzheimers Disease in the Chinese Population
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Multiple Visual Rating Scales Based on Structural MRI and a Novel Prediction Model Combining Visual Rating Scales and Age Stratification in the Diagnosis of Alzheimers Disease in the Chinese Population

机译：基于结构性MRI的多视力评定量表和结合视力评定量表和年龄分层的新型预测模型在中国人群阿尔茨海默氏病的诊断中

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>Objective: To explore the value of multiple visual rating scales based on structural MRI in the diagnosis of Alzheimer's disease (AD) in the Chinese population.>Materials and Methods: One hundred patients with AD and 100 age- and gender- matched cognitively normal controls were enrolled in this study. All the participants underwent neuropsychological tests and a structural MRI scan of the brain, among them, 42 AD cases and 47 cognitively normal controls also underwent 3D-T1 weighted sequence used for the analysis of voxel-based morphometry (VBM). The AD cases were divided into mild and moderate–severe groups according to the mini-mental state examination. Each participant was evaluated by two trained radiologists who were blind to the clinical information, according to the six visual rating scales, including for medial temporal lobe atrophy (MTA), posterior atrophy (PA), anterior temporal (AT), orbitofrontal (OF) cortex, anterior cingulate (AC), and fronto-insula (FI). Finally, we estimated the relationship between the visual rating scales and the volume of corresponding brain regions, using correlation analysis, and evaluated the specificity and sensitivity of every single scale and combination of multiple scales in the diagnosis of AD, using a receiver operating characteristic (ROC) curve and establishing a logistic regression model.>Results: The optimal cutoff of all six visual rating scales for distinguishing AD cases from normal controls was 1.5. Using automated classification based on all six rating scales, the accuracy for distinguishing AD cases from healthy controls ranged from 0.68 to 0.80 (for mild AD) and 0.77–0.90 (for moderate–severe AD), respectively. A diagnostic prediction model with a combination of MTA and OF results was made as follows: Score = BMTA(score) + BOF(score) −1.58 (age < 65 years); Score = BMTA(score) + BOF(score) −4.09 (age ≥65 years). The model was superior to any single visual rating scale in the diagnosis of mild AD (P < 0.05).>Conclusion: Each of the six visual rating scales could be applied to the diagnosis of moderate-severe AD alone in the Chinese population. A prediction model of the combined usage of MTA, OF, and age stratification for the early diagnosis of AD was preliminarily established.
机译：>目的：探讨基于结构MRI的多个视觉评级量表在中国人群阿尔茨海默氏病（AD）诊断中的价值。>材料和方法：这项研究纳入了AD和100位年龄和性别匹配的认知正常对照。所有参与者均接受了神经心理学测试和大脑的结构MRI扫描，其中42例AD患者和47名认知正常对照也接受了3D-T1加权序列，用于基于体素的形态测量（VBM）分析。根据小精神状态检查，将AD病例分为轻度和中度-重度组。每位参与者均由两名训练有素的放射科医生进行评估，他们根据六种视觉评估量表对临床信息不了解，包括对内侧颞叶萎缩症（MTA），后牙萎缩症（PA），颞叶颞部萎缩症（AT），眶额叶（OF）皮层，前扣带回（AC）和额叶鞘（FI）。最后，我们使用相关性分析估算了视觉评定量表与相应大脑区域的体积之间的关系，并使用接收器的操作特征评估了每种单一量表和多个量表组合在AD诊断中的特异性和敏感性（ ROC）曲线并建立逻辑回归模型。>结果：用于区分AD病例和正常对照的全部六个视觉评级量表的最佳截止值为1.5。使用基于所有六个等级量表的自动分类，将AD病例与健康对照区分开的准确性分别为0.68至0.80（对于轻度AD）和0.77–0.90（对于中度至重度AD）。结合MTA和OF结果的诊断预测模型如下：得分= BMTA（得分）+ BOF（得分）-1.58（年龄<65岁）；分数= BMTA（分数）+ BOF（分数）−4.09（年龄≥65岁）。该模型在轻度AD的诊断中优于任何单一的视觉评定量表（P <0.05）。>结论：六个视觉评定量表中的每一个均可用于单独诊断中重度AD在中国人口中。初步建立了MTA，OF和年龄分层结合用于AD早期诊断的预测模型。

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