Abstract
BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by progressive cognitive decline and is traditionally associated with grey matter pathology. Recent research highlights the significance of white matter and myelin damage in AD, presenting a paradigm shift in understanding the disease. The aim of this study was to summarize current advancements in magnetic resonance imaging (MRI) techniques and their applications in assessing myelin and brain pathology in AD with a special focus on ultrashort echo time (UTE) based techniques, alongside the role of artificial intelligence (AI) in enhancing diagnostic accuracy. METHODS: Between April and May 2024, we conducted a literature search using Google Scholar, Web of Science, and PubMed, focusing on publications from 1990 to 2024. Search terms included "Quantitative imaging", "Alzheimer's MRI", "T1ρ Alzheimer's", "MT imaging Alzheimer's", and "myelin water fraction Alzheimer's". We included quantitative MRI studies involving AD brains and excluded volumetric analyses, non-quantitative studies, non-English reports, non-peer-reviewed studies, and animal research. KEY CONTENT AND FINDINGS: Quantitative MRI techniques, including T1, T1ρ, magnetization transfer ratio (MTR), T2, T2*, susceptibility, myelin water fraction (MWF), and non-aqueous myelin proton density (PD) were described. These biomarkers represent different pathophysiological elements of brain damage and may have distinct functions at different phases of the disease. The role of AI in enhancing diagnostic accuracy is also discussed. CONCLUSIONS: In conclusion, integrating advanced MRI techniques and AI offers promising avenues for understanding and diagnosing AD. The focus on myelin damage and white matter integrity underscores the importance of comprehensive imaging approaches. Continued research and development are essential to address current challenges and improve clinical practice in AD diagnostics.