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
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.