Multiple Visual Rating Scales Based on Structural MRI and a Novel Prediction Model Combining Visual Rating Scales and Age Stratification in the Diagnosis of Alzheimer's Disease in the Chinese Population

• Main Authors: Zhenhua Yuan, Chuzheng Pan, Tingting Xiao, Menghui Liu, Weiwei Zhang, Bin Jiao, Xinxiang Yan, Beisha Tang, Lu Shen
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2019-02-01
• Series: Frontiers in Neurology
• Subjects: visual rating scales; Alzheimer's disease; sensitivity; specificity; Chinese population; prediction model
• Online Access: https://www.frontiersin.org/article/10.3389/fneur.2019.00093/full

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.