Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology

Machine learning (ML) algorithms have found increasing utility in the medical imaging field and numerous applications in the analysis of digital biomarkers within positron emission tomography (PET) imaging have emerged. Interest in the use of artificial intelligence in PET imaging for the study of neurodegenerative diseases and oncology stems from the potential for such techniques to streamline decision support for physicians providing early and accurate diagnosis and allowing personalized treatment regimens. In this review, the use of ML to improve PET image acquisition and reconstruction is presented, along with an overview of its applications in the analysis of PET images for the study of Alzheimer's disease and oncology

Emerging PET Radiotracers and Targets for Imaging of Neuroinflammation in Neurodegenerative Diseases: Outlook Beyond TSPO

The dynamic and multicellular processes of neuroinflammation are mediated by the nonneuronal cells of the central nervous system, which include astrocytes and the brain’s resident macrophages, microglia. Although initiation of an inflammatory response may be beneficial in response to injury of the nervous system, chronic or maladaptive neuroinflammation can have harmful outcomes in many neurological diseases. An acute neuroinflammatory response is protective when activated neuroglia facilitate tissue repair by releasing anti-inflammatory cytokines and neurotrophic factors. On the other hand, chronic neuroglial activation is a major pathological mechanism in neurodegenerative diseases, likely contributing to neuronal dysfunction, injury, and disease progression. Therefore, the development of specific and sensitive probes for positron emission tomography (PET) studies of neuroinflammation is attracting immense scientific and clinical interest. An early phase of this research emphasized PET studies of the prototypical imaging biomarker of glial activation, translocator protein-18 kDa (TSPO), which presents difficulties for quantitation and lacks absolute cellular specificity. Many alternate molecular targets present themselves for PET imaging of neuroinflammation in vivo, including enzymes, intracellular signaling molecules as well as ionotropic, G-protein coupled, and immunoglobulin receptors. We now review the lead structures in radiotracer development for PET studies of neuroinflammation targets for neurodegenerative diseases extending beyond TSPO, including glycogen synthase kinase 3, monoamine oxidase-B, reactive oxygen species, imidazoline-2 binding sites, cyclooxygenase, the phospholipase A2/arachidonic acid pathway, sphingosine-1-phosphate receptor-1, cannabinoid-2 receptor, the chemokine receptor CX3CR1, purinergic receptors: P2X 7 and P2Y 12 , the receptor for advanced glycation end products, Mer tyrosine kinase, and triggering receptor expressed on myeloid cells-1. We provide a brief overview of the cellular expression and function of these targets, noting their selectivity for astrocytes and/or microglia, and highlight the classes of PET radiotracers that have been investigated in early-stage preclinical or clinical research studies of neuroinflammation

The Binding of BF-227-Like Benzoxazoles to Human α-Synuclein and Amyloid β Peptide Fibrils

Development of an α-synuclein (α-Syn) positron emission tomography agent for the diagnosis and evaluation of Parkinson disease therapy is a key goal of neurodegenerative disease research. BF-227 has been described as an α-Syn binder and hence was employed as a lead to generate a library of α-Syn-binding compounds. [ 3 H]BF-227 bound to α-Syn and amyloid β peptide (Aβ) fibrils with affinities (K D ) of 46.0 nM and 15.7 nM, respectively. Affinities of BF-227-like compounds (expressed as K i ) for α-Syn and Aβ fibrils were determined, along with 5 reference compounds (flutafuranol, flutemetamol, florbetapir, BF-227, and PiB). Selectivity for α-Syn binding, defined as the K i (Aβ)/K i (α-Syn) ratio, was 0.23 for BF-227. A similar or lower ratio was measured for analogues decorated with alkyl or oxyethylene chains attached to the oxygen at the 6 position of BF-227, suggesting a lack of involvement of the side chain in fibril binding. BF-227-like iodobenzoxazoles had lower affinities and poor α-Syn selectivity. However, BF-227-like fluorobenzoxazoles had improved α-Syn selectively having K i (Aβ)/K i (α-Syn) ranging from 2.2 to 5.1 with appreciable fibril affinity, although not sufficient to warrant further investigation. Compounds based on fluorobenzoxazoles might offer an approach to obtaining an α-Syn imaging agent with an appropriate affinity and selectivity

Preclinical PET Neuroimaging of [C]Bexarotene

Activation of retinoid X receptors (RXRs) has been proposed as a therapeutic mechanism for the treatment of neurodegeneration, including Alzheimer's and Parkinson's diseases. We previously reported radiolabeling of a Food and Drug Administration-approved RXR agonist, bexarotene, by copper-mediated [ 11 C]CO 2 fixation and preliminary positron emission tomography (PET) neuroimaging that demonstrated brain permeability in nonhuman primate with regional binding distribution consistent with RXRs. In this study, the brain uptake and saturability of [ 11 C]bexarotene were studied in rats and nonhuman primates by PET imaging under baseline and greater target occupancy conditions. [ 11 C]Bexarotene displays a high proportion of nonsaturable uptake in the brain and is unsuitable for RXR occupancy measurements in the central nervous system