AI Article Synopsis
- The review focuses on the latest advancements in brain imaging techniques, particularly for diagnosing Alzheimer's disease (AD).
- Recent developments like FDA approval of new anti-amyloid therapies highlight the importance of amyloid-PET imaging in treatment planning, while tau-PET imaging is crucial for tracking disease progression.
- Emerging techniques and AI applications in MRI show promise for early AD detection, though further research is needed for clinical validation.
Article Abstract
Purpose Of Review: The purpose is to review the latest advances of brain imaging for the diagnosis of Alzheimer disease (AD).
Recent Findings: Brain imaging techniques provide valuable and complementary information to support the diagnosis of Alzheimer disease in clinical and research settings. The recent FDA accelerated approvals of aducanumab, lecanemab and donanemab made amyloid-PET critical in helping determine the optimal window for anti-amyloid therapeutic interventions. Tau-PET, on the other hand, is considered of key importance for the tracking of disease progression and for monitoring therapeutic interventions in clinical trials. PET imaging for microglial activation, astrocyte reactivity and synaptic degeneration are still new techniques only used in the research field, and more studies are needed to validate their use in the clinical diagnosis of AD. Finally, artificial intelligence has opened new prospective in the early detection of AD using MRI modalities.
Summary: Brain imaging techniques using PET improve our understanding of the different AD-related pathologies and their relationship with each other along the course of disease. With more robust validation, machine learning and deep learning algorithms could be integrated with neuroimaging modalities to serve as valuable tools for clinicians to make early diagnosis and prognosis of AD.
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| http://dx.doi.org/10.1097/WCO.0000000000001198 | DOI Listing |
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