School of Information Science and Engineering, Shandong Normal University, Ji'nan 250014, China.
School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
Cereb Cortex. 2021 Jul 5;31(8):3950-3961. doi: 10.1093/cercor/bhab061.
Growing evidence indicates that amyloid-beta (Aβ) accumulation is one of the most common neurobiological biomarkers in Alzheimer's disease (AD). The primary aim of this study was to explore whether the radiomic features of Aβ positron emission tomography (PET) images are used as predictors and provide a neurobiological foundation for AD. The radiomics features of Aβ PET imaging of each brain region of the Brainnetome Atlas were computed for classification and prediction using a support vector machine model. The results showed that the area under the receiver operating characteristic curve (AUC) was 0.93 for distinguishing AD (N = 291) from normal control (NC; N = 334). Additionally, the AUC was 0.83 for the prediction of mild cognitive impairment (MCI) converting (N = 88) (vs. no conversion, N = 100) to AD. In the MCI and AD groups, the systemic analysis demonstrated that the classification outputs were significantly associated with clinical measures (apolipoprotein E genotype, polygenic risk scores, polygenic hazard scores, cerebrospinal fluid Aβ, and Tau, cognitive ability score, the conversion time for progressive MCI subjects and cognitive changes). These findings provide evidence that the radiomic features of Aβ PET images can serve as new biomarkers for clinical applications in AD/MCI, further providing evidence for predicting whether MCI subjects will convert to AD.
越来越多的证据表明，β淀粉样蛋白（Aβ）的积累是阿尔茨海默病（AD）中最常见的神经生物学生物标志物之一。本研究的主要目的是探索 Aβ 正电子发射断层扫描（PET）图像的放射组学特征是否可用作预测指标，并为 AD 提供神经生物学基础。使用支持向量机模型对脑网络图谱中每个脑区的 Aβ PET 图像的放射组学特征进行分类和预测计算。结果表明，区分 AD（N=291）与正常对照（NC；N=334）的受试者工作特征曲线下面积（AUC）为 0.93。此外，预测轻度认知障碍（MCI）向 AD 转化（N=88）（与无转化，N=100）的 AUC 为 0.83。在 MCI 和 AD 组中，系统分析表明，分类输出与临床指标（载脂蛋白 E 基因型、多基因风险评分、多基因危险评分、脑脊液 Aβ 和 Tau、认知能力评分、进行性 MCI 患者的转化时间和认知变化）显著相关。这些发现为 Aβ PET 图像的放射组学特征可作为 AD/MCI 临床应用的新生物标志物提供了证据，进一步为预测 MCI 患者是否会转化为 AD 提供了证据。
