Transforming Alzheimer’s Diagnosis: Nanotechnology and AI-Driven Neuroimaging for Early Detection and Beyond

Abstract

Background: Alzheimer’s disease (AD), the most prevalent form of dementia, is characterized by progressive cognitive decline and neurodegeneration associated with beta-amyloid plaques and tau protein tangles. Traditional diagnostic tools, while effective in advanced stages, often lack sensitivity for early detection, delaying intervention and limiting treatment efficacy. Innovations in neuroimaging, including the integration of artificial intelligence (AI) and nanotechnology, offer promising advancements in the early identification of AD-related pathologies. Objective: To systematically evaluate the role of advanced neuroimaging techniques—particularly those augmented by AI and nanotechnology—in the early detection, diagnosis, and monitoring of Alzheimer’s disease. Methods: A systematic literature review was conducted in May 2025 using PubMed, Google Scholar, ResearchGate, and Sci-Hub. Search strategies incorporated MeSH terms and free-text keywords. From 503 identified records, 50 studies met inclusion criteria based on relevance to neuroimaging in human AD diagnosis. Data extraction focused on imaging modality, diagnostic performance, population characteristics, and analytic methods. Results: Structural MRI consistently identified hippocampal and medial temporal lobe atrophy, while functional MRI revealed disrupted connectivity in key cognitive networks. PET imaging, particularly with amyloid and tau tracers, demonstrated early molecular changes. AI-based models enhanced diagnostic accuracy across modalities, and nanoparticle-enhanced imaging showed improved sensitivity in preclinical detection. Conclusion: Advanced neuroimaging, particularly when integrated with AI and nanotechnology, significantly improves early diagnostic capabilities in Alzheimer’s disease. These modalities hold potential for earlier intervention, personalized monitoring, and better patient outcomes, although challenges related to standardization, cost, and clinical translation persist.