{"doi":"10.1007/s13139-025-00932-2","title":"18F-FDG-PET and Multimodal Biomarker Integration: A Powerful Tool for Alzheimer’s Disease Diagnosis","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>\n                    An early, biomarker-based diagnosis of Alzheimer’s Disease (AD) is crucial, especially with the emerging availability of novel therapeutic options. However, the role of\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET and its relationship to other PET and CSF biomarkers remains unclear. Therefore, the aim of this study was the evaluation of the role of\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET in AD diagnosis and its relationship to other commonly used fluid and PET biomarkers and their individual and multimodal accuracy in AD diagnosis. We included\n                    <jats:italic>n</jats:italic>\n                     = 157 AD patients,\n                    <jats:italic>n</jats:italic>\n                     = 603 MCI patients, and\n                    <jats:italic>n</jats:italic>\n                     = 380 cognitively normal participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) that underwent PET imaging with\n                    <jats:sup>18</jats:sup>\n                    F-FDG or\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir. Clinical and imaging data including patient characteristics, CSF biomarkers, cognition tests,\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET,\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir-PET, and\n                    <jats:sup>18</jats:sup>\n                    F-Flortaucipir-PET were retrospectively analyzed. PET images were quantified in several brain regions. The uptake of\n                    <jats:sup>18</jats:sup>\n                    F-FDG was inversely correlated with\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir and positively correlated with CSF Aβ42 in several brain regions commonly affected by AD. Additionally,\n                    <jats:sup>18</jats:sup>\n                    F-FDG uptake showed an inverse correlation with both forms of CSF tau, t-tau and p-tau, in various brain regions, but did not correlate with\n                    <jats:sup>18</jats:sup>\n                    F-Flortaucipir uptake. Moreover, regional\n                    <jats:sup>18</jats:sup>\n                    F-FDG uptake was positively correlated with cognitive function. Diagnostic accuracies were similarly high for\n                    <jats:sup>18</jats:sup>\n                    F-FDG uptake in the PCC/Precuneus region,\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir uptake, CSF Aβ42, CSF p-tau, and\n                    <jats:sup>18</jats:sup>\n                    F-Flortaucipir uptake in differentiating AD from cognitively normal individuals.\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET and its combination with CSF p-tau/ Aβ42 ratio showed the highest predictive power for disease severity. The study underscores the potential of integrating\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET with CSF biomarkers to enhance the diagnosis, prognosis, and monitoring of AD, highlighting the complexity and regional specificity of biomarker interactions in neurodegeneration.\n                  </jats:p>","journal":"Nuclear Medicine and Molecular Imaging","year":2025,"id":610349,"datarank":0.31191623125197543,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"self_citation_contribution":0.31191623125197543,"citation_network_contribution":0.0,"self_endowment_contribution":0.31191623125197543,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1569235,"name":"Robert M. Glasnek","orcid":null,"position":1,"is_corresponding":false},{"id":1569236,"name":"Jannis M. Wenzel","orcid":null,"position":2,"is_corresponding":false},{"id":908099,"name":"Caroline Bouter","orcid":"0000-0002-0057-5037","position":3,"is_corresponding":false},{"id":908098,"name":"Yvonne Bouter","orcid":"0009-0002-3893-598X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"18F-FDG-PET and Multimodal Biomarker Integration: A Powerful Tool for Alzheimer’s Disease Diagnosis","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>\n                    An early, biomarker-based diagnosis of Alzheimer’s Disease (AD) is crucial, especially with the emerging availability of novel therapeutic options. However, the role of\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET and its relationship to other PET and CSF biomarkers remains unclear. Therefore, the aim of this study was the evaluation of the role of\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET in AD diagnosis and its relationship to other commonly used fluid and PET biomarkers and their individual and multimodal accuracy in AD diagnosis. We included\n                    <jats:italic>n</jats:italic>\n                     = 157 AD patients,\n                    <jats:italic>n</jats:italic>\n                     = 603 MCI patients, and\n                    <jats:italic>n</jats:italic>\n                     = 380 cognitively normal participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) that underwent PET imaging with\n                    <jats:sup>18</jats:sup>\n                    F-FDG or\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir. Clinical and imaging data including patient characteristics, CSF biomarkers, cognition tests,\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET,\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir-PET, and\n                    <jats:sup>18</jats:sup>\n                    F-Flortaucipir-PET were retrospectively analyzed. PET images were quantified in several brain regions. The uptake of\n                    <jats:sup>18</jats:sup>\n                    F-FDG was inversely correlated with\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir and positively correlated with CSF Aβ42 in several brain regions commonly affected by AD. Additionally,\n                    <jats:sup>18</jats:sup>\n                    F-FDG uptake showed an inverse correlation with both forms of CSF tau, t-tau and p-tau, in various brain regions, but did not correlate with\n                    <jats:sup>18</jats:sup>\n                    F-Flortaucipir uptake. Moreover, regional\n                    <jats:sup>18</jats:sup>\n                    F-FDG uptake was positively correlated with cognitive function. Diagnostic accuracies were similarly high for\n                    <jats:sup>18</jats:sup>\n                    F-FDG uptake in the PCC/Precuneus region,\n                    <jats:sup>18</jats:sup>\n                    F-Florbetapir uptake, CSF Aβ42, CSF p-tau, and\n                    <jats:sup>18</jats:sup>\n                    F-Flortaucipir uptake in differentiating AD from cognitively normal individuals.\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET and its combination with CSF p-tau/ Aβ42 ratio showed the highest predictive power for disease severity. The study underscores the potential of integrating\n                    <jats:sup>18</jats:sup>\n                    F-FDG-PET with CSF biomarkers to enhance the diagnosis, prognosis, and monitoring of AD, highlighting the complexity and regional specificity of biomarker interactions in neurodegeneration.\n                  </jats:p>","is_dataset_classified":null,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"41341151","pmcid":"PMC12669464","openalex_id":"https://openalex.org/W4412154839","authors":[],"funders":[{"funder_name":"Herzzentrum Göttingen","grant_id":"","title":null}],"total_grants":1,"fwci":5.0035,"citation_percentile":0.95788179,"influential_citations":0,"citation_trend":[{"year":2025,"count":1},{"year":2026,"count":5}],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://link.springer.com/content/pdf/10.1007/s13139-025-00932-2.pdf","host_type":"journal"},{"url":"https://link.springer.com/content/pdf/10.1007/s13139-025-00932-2.pdf","host_type":"publisher"},{"url":"https://link.springer.com/article/10.1007/s13139-025-00932-2/fulltext.html","host_type":"publisher"},{"url":"https://doi.org/10.1007/s13139-025-00932-2","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/41341151","host_type":"repository"},{"url":"https://resolver.sub.uni-goettingen.de/purl?gro-2/153715","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC12669464","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC12669464?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Dementia and Cognitive Impairment Research","Medical Imaging Techniques and Applications","Cerebrovascular and Carotid Artery Diseases"],"mesh_terms":[],"keywords":["Medicine","Biomarker","Disease","Positron emission tomography","Pet imaging","Medical physics","Nuclear medicine","Pathology","Alzheimer’s disease","Fdg-pet","Florbetapir"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-31T21:29:10.519383Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}