APPLICATIONS OF FUNCTIONAL MAGNETIC RESONANCE IMAGING IN THE EARLY DIAGNOSIS OF ALZHEIMER’S DISEASE: A SYSTEMATIC REVIEW
DOI:
https://doi.org/10.56238/levv16n53-096Keywords:
Alzheimer Disease, Magnetic Resonance Imaging, Functional, Early Diagnosis, Mild Cognitive ImpairmentAbstract
Introduction: Alzheimer’s disease (AD) is the most common neurodegenerative disorder globally, characterized by progressive cognitive decline and substantial socioeconomic burden. Early diagnosis is crucial to enable therapeutic interventions before irreversible neuronal loss.
Objective: The primary objective was to systematically review the current evidence on the applications of functional magnetic resonance imaging (fMRI) in the early diagnosis of AD, focusing on diagnostic accuracy, methodological advances, and clinical potential. Secondary objectives included evaluating analytic approaches, such as connectivity metrics and machine learning models, and assessing heterogeneity and gaps in the literature.
Methods: A systematic search was conducted in PubMed, Scopus, Web of Science, Cochrane Library, LILACS, ClinicalTrials.gov, and ICTRP for studies published between 2019 and 2025. Inclusion criteria comprised human fMRI studies investigating early AD or mild cognitive impairment (MCI) with quantitative diagnostic metrics. Studies with small samples or non-standardized protocols were included but noted as limitations. Exclusion criteria involved reviews, editorials, and studies without quantitative diagnostic data. The review followed PRISMA guidelines.
Results and Discussion: Most used resting-state fMRI and advanced computational models to differentiate MCI or early AD from healthy controls. Reported diagnostic accuracies ranged from 83% to 96%, with consistent sensitivity and specificity above 0.85. Deep learning and graph-based models significantly improved classification performance. However, heterogeneity in acquisition parameters, preprocessing pipelines, and small sample sizes limited generalizability.
Conclusion: Functional MRI demonstrates high potential as a noninvasive biomarker for early AD diagnosis, especially when combined with structural and diffusion imaging or artificial intelligence-based analysis. Standardization of acquisition and preprocessing protocols and multicenter validation remain essential for clinical translation.
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References
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