aceA review on diffusion tensor imaging-based comprehensive intelligent diagnosis of Alzheimer's disease
AI-assisted early diagnosis of Alzheimer's disease (AD) has substantial clinical value, and diffusion tensor imaging (DTI), which captures white matter microstructural alterations, has considerable potential across the AD continuum. However, major barriers to clinical translation remain. This review systematically evaluated the evolution of algorithmic paradigms, the effectiveness of multimodal fusion, and barriers to clinical generalization in DTI-based AD diagnosis. Using an "Input-Model-Fusion" evaluation fra…
AI models using diffusion tensor imaging to detect white matter changes show potential for early Alzheimer's diagnosis with clinical value.
DTI-based AI models for Alzheimer's diagnosis suffer substantial performance degradation in multicenter or external validation, limiting clinical translation.
Findings are constrained by heterogeneity in data sources, acquisition protocols, and processing pipelines that limit comparability and generalizability, with performance dropping in multicenter validation.
Evidence
- Peer-reviewedReviews in the Neurosciences2026-10-01
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Truvace Impact Record TRV-2026-1244, v1: “A review on diffusion tensor imaging-based comprehensive intelligent diagnosis of Alzheimer's disease.” Truvace, 2026-10-02. /record/TRV-2026-1244 (accessed at citation time). sha256 dcbcee4910fdee54…
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