Background: Alzheimer’s Disease (AD) is a progressive neurodegenerative disease that threatens the health of the elderly. Mild Cognitive Impairment (MCI) is considered to be the prodromal stage of AD. To date, AD or MCI diagnosis is established after irreversible brain structure alterations. Therefore, the development of new biomarkers is crucial to the early detection and treatment of this disease. At present, there exist some research studies showing that radiomics analysis can be a good diagnosis and classification method in AD and MCI.

Objective: An extensive review of the literature was carried out to explore the application of radiomics analysis in the diagnosis and classification among AD patients, MCI patients, and Normal Controls (NCs).

Results: Thirty completed MRI radiomics studies were finally selected for inclusion. The process of radiomics analysis usually includes the acquisition of image data, Region of Interest (ROI) segmentation, feature extracting, feature selection, and classification or prediction. From those radiomics methods, texture analysis occupied a large part. In addition, the extracted features include histogram, shapebased features, texture-based features, wavelet features, Gray Level Co-Occurrence Matrix (GLCM), and Run-Length Matrix (RLM).

Conclusion: Although radiomics analysis is already applied to AD and MCI diagnosis and classification, there still is a long way to go from these computer-aided diagnostic methods to the clinical application.

中文翻译：

---

阿尔茨海默氏病和轻度认知障碍的MRI放射学分类和预测：综述。

背景：阿尔茨海默氏病（AD）是一种进行性神经退行性疾病，威胁着老年人的健康。轻度认知障碍（MCI）被认为是AD的前驱阶段。迄今为止，AD或MCI诊断是在不可逆的大脑结构改变后建立的。因此，开发新的生物标志物对于这种疾病的早期发现和治疗至关重要。目前，已有一些研究表明，放射学分析可以作为AD和MCI的良好诊断和分类方法。

目的：对文献进行了广泛的综述，以探索放射线分析法在AD患者，MCI患者和正常对照组（NC）的诊断和分类中的应用。

结果：最终选择了30项完成的MRI放射学研究。放射线分析的过程通常包括图像数据的获取，感兴趣区域（ROI）分割，特征提取，特征选择以及分类或预测。从那些放射学方法中，纹理分析占据了很大一部分。此外，提取的特征包括直方图，基于形状的特征，基于纹理的特征，小波特征，灰度共生矩阵（GLCM）和运行长度矩阵（RLM）。

结论：尽管放射组学分析已经用于AD和MCI的诊断和分类，但是从这些计算机辅助诊断方法到临床应用还有很长的路要走。