Artificial Intelligence in PET Imaging for Alzheimer’s Disease: A Narrative Review
The rapid advancements in computer processing, algorithmic development, and the availability of large-scale datasets have positioned Artificial Intelligence (AI) as a valuable tool across multiple domains, including Medicine. In the field of Nuclear Medicine neuroimaging, with Positron Emission Tomography (PET), AI has demonstrated significant potential in improving diagnostic accuracy for neurodegenerative cognitive disorders. This is especially relevant for the early diagnosis, preclinical detection, and prediction of disease progression in Alzheimer's disease (AD), the most prevalent form of cognitive impairment in individuals over 65 years of age. This narrative review aims to synthesize current advances, explore future directions, and highlight outstanding challenges in the application of Artificial Intelligence to PET imaging for the clinical management of Alzheimer's disease, with particular focus on three key modalities: <sup>18</sup>F-FDG PET, Amyloid PET, and Tau PET.
Authors
- Francesco Bianconi (ORCID: https://orcid.org/0000-0003-3371-1928)
- Susanna Nuvoli (ORCID: https://orcid.org/0000-0002-7194-985X)
- Angela Spanu (ORCID: https://orcid.org/0000-0001-5753-399X)
- Luca Filippi (ORCID: https://orcid.org/0000-0003-4423-5496)
- Andrea Marongiu (ORCID: https://orcid.org/0000-0001-7038-3615)
- Barbara Palumbo (ORCID: https://orcid.org/0000-0003-2475-343X)
- Giuseppe Madeddu
Institutions
- University of Rome Tor Vergata (IT)
- University of Sassari (IT)
- University of Perugia (IT)
Publication Details
- Journal
- Brain Sciences
- Published
- 2025-09-25
- DOI
- https://doi.org/10.3390/brainsci15101038
- Citations
- 2
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.72