The Role of Ultra-High-Resolution Magnetic Resonance Imaging (UHD-MRI) In the Early Detection of Neurodegenerative Diseases: Systematic Review
DOI:
https://doi.org/10.69980/ajpr.v28i5.530Keywords:
Ultra-high-resolution MRI; 7T MRI; Neurodegenerative diseases; Alzheimer’s disease; Parkinson’s disease; Early diagnosis; Structural imaging; Cortical laminae; Subcortical segmentation; Advanced neuroimaging.Abstract
Background: Early detection of neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS) remains a major clinical challenge. Conventional neuroimaging often fails to capture subtle anatomical changes at the preclinical stage. Ultra-high-resolution magnetic resonance imaging (UHD-MRI), especially at field strengths of 7 Tesla (7T) or higher, presents new opportunities for early diagnosis.
Objectives: This systematic review aimed to synthesize recent evidence on the diagnostic utility of UHD-MRI in identifying early structural and functional brain changes associated with neurodegenerative diseases.
Methods: Following PRISMA 2020 guidelines, we searched five databases and included peer-reviewed human studies published between 2010 and 2024. Studies were screened for use of UHD-MRI (≥7T) and relevant neurodegenerative outcomes. A narrative synthesis was conducted based on imaging resolution, anatomical targets, diagnostic performance, and integration with adjunct technologies.
Results: A total of 15 studies met inclusion criteria. UHD-MRI consistently demonstrated superior anatomical resolution, improving detection of hippocampal subfields, cortical laminae, and deep brain nuclei. Sensitivity improvements ranged from 15–30% over 3T MRI. Integration with AI and PET further enhanced diagnostic accuracy, while automated segmentation reduced operator variability.
Conclusion: UHD-MRI offers substantial improvements in detecting early pathological changes in neurodegenerative diseases. Its combination with AI-driven analysis and hybrid PET approaches holds promise for future diagnostic frameworks, though issues of accessibility, cost, and standardization remain.
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