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Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
Published on: April 18, 2025
Neuroinflammation in Neurodegenerative Diseases: Current Multi-modal Imaging Studies and Future Opportunities for
Marco Aiello1, Carlo Cavaliere1, Dario Fiorenza1
1NAPLab, IRCCS SDN Istituto di Ricerca Diagnostica e Nucleare, Via E. Gianturco 113, 80143 Naples, Italy.
Abstract:
Positron emission tomography (PET) provides spatially localized information about brain metabolism and function and innovative tracers have extended this potential to the study of neuroinflammation (NI), an important process in the pathophysiology of several neurological disorders. However, PET is limited by low spatial resolution. Conversely, Magnetic Resonance Imaging (MRI) affords high-resolution information about brain anatomy and metabolism which can complement PET-related information as well as aid in post-processing of PET data. For sequentially acquired MR/PET data, anatomical correspondence is often capped by the limited structural detail afforded by PET, and the assumption that no significant changes in subject state has occurred between sessions. Hybrid PET/MRI offers the unique opportunity to overcome these limitations by providing access to temporal and spatial cross-modal alignment/synchronization, hence opening novel avenues for exploiting multivariate and multiparametric information regarding brain structure and function. While, the clinical applicability and impact on diagnostic accuracy of PET/MRI in neurological disorders is still under investigation, the study of NI, a complex processes mediated by multiple metabolic pathways and hence likely characterized by different biomarkers, represents an opportunity to characterize the added value of joint MRI-PET techniques in a clinical context. This would in turn offer improved diagnostic and prognostic tools in several neurological disorders in which NI is a key mediator. This review aims at summarizing the current state as well as future potential of using hybrid PET/MRI for characterizing NI phenomena, both in terms of technical challenges and clinical relevance.
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