MRI Radiomics Classification and Prediction in Alzheimer's Disease and Mild Cognitive Impairment: A Review

Area of Science:

• Neuroimaging
• Biomarker Discovery
• Medical Informatics

Background:

• Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) are neurodegenerative conditions often diagnosed after irreversible brain changes.
• Early detection biomarkers are crucial for timely intervention and treatment of AD and MCI.
• Current diagnostic methods for AD and MCI lack the sensitivity for early detection.

Purpose of the Study:

• To review the literature on radiomics analysis for diagnosing and classifying AD and MCI.
• To explore the potential of radiomics as an early detection biomarker for neurodegenerative diseases.
• To assess the current state and future directions of radiomics in AD and MCI research.

Main Methods:

• Extensive literature review of MRI radiomics studies.
• Inclusion of 30 completed radiomics studies.
• Analysis of radiomics methodologies including image acquisition, ROI segmentation, feature extraction, and classification.

Main Results:

• Radiomics analysis, particularly texture analysis, is being explored for AD and MCI diagnosis.
• Commonly extracted features include histogram, shape, texture, wavelet, GLCM, and RLM.
• Studies indicate radiomics can aid in the diagnosis and classification of AD and MCI.

Conclusions:

• Radiomics analysis demonstrates potential as a diagnostic and classification tool for AD and MCI.
• Significant advancements in computer-aided diagnostic methods are emerging.
• Further research and development are required to translate radiomics into routine clinical practice for early AD and MCI detection.