Neuroimaging Laboratory (LINI), Electrical Engineering Department, Universidad Autónoma Metropolitana-Iztapalapa (UAM-I), Mexico City, Mexico.
Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), Sede Mérida, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico.
Comput Intell Neurosci. 2020 Jan 29;2020:4041832. doi: 10.1155/2020/4041832. eCollection 2020.
The 3D tortuosity determined in several brain areas is proposed as a new morphological biomarker (BM) to be considered in early detection of Alzheimer's disease (AD). It is measured using the sum of angles method and it has proven to be sensitive to anatomical changes that appear in gray and white matter and temporal and parietal lobes during mild cognitive impairment (MCI). Statistical analysis showed significant differences ( < 0.05) between tortuosity indices determined for healthy controls (HC) vs. MCI and HC vs. AD in most of the analyzed structures. Other clinically used BMs have also been incorporated in the analysis: beta-amyloid and tau protein CSF and plasma concentrations, as well as other image-extracted parameters. A classification strategy using random forest (RF) algorithms was implemented to discriminate between three samples of the studied populations, selected from the ADNI database. Classification rates considering only image-extracted parameters show an increase of 9.17%, when tortuosity is incorporated. An enhancement of 1.67% is obtained when BMs measured from several modalities are combined with tortuosity.
在几个大脑区域中确定的 3D 迂曲度被提出作为一种新的形态标志物 (BM)，以考虑在阿尔茨海默病 (AD) 的早期检测中。它是使用角度总和法测量的，已被证明对轻度认知障碍 (MCI) 期间出现在灰质和白质以及颞叶和顶叶中的解剖结构变化敏感。统计分析显示，在大多数分析结构中，健康对照组 (HC) 与 MCI 以及 HC 与 AD 之间确定的迂曲度指数存在显著差异 ( < 0.05)。其他临床上使用的 BM 也已纳入分析：β-淀粉样蛋白和tau 蛋白 CSF 和血浆浓度以及其他从图像中提取的参数。使用随机森林 (RF) 算法实施了分类策略，以从 ADNI 数据库中选择研究人群的三个样本进行区分。仅考虑从图像中提取的参数进行分类时，当纳入迂曲度时，分类率会增加 9.17%。当将从多种模式测量的 BM 与迂曲度相结合时，可获得 1.67%的增强。
