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Here we developed SynthPET, a multimodal deep learning framework that synthesizes FDG PET images from T1\u2010weighted (T1w) and arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>\n                      Two conditional generative models were trained on paired MRI and FDG PET acquisitions: one using T1w alone (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a01170) and one integrating T1w with ASL via cross\u2010modality transfer learning (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a0220). We evaluated synthetic FDG PET through voxel\u2010wise fidelity metrics, regional correlation and receiver operating characteristic analyses, blinded reader studies, and differential diagnosis across independent external cohorts.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Both models achieved high fidelity with real FDG PET (structural similarity &gt;\u00a093%) and strong diagnostic performance in AD\u2010specific regions, with ASL providing modest improvements. Results generalized to an independent AD external cohort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>SynthPET generates clinically plausible FDG PET from routinely acquired MRI, potentially expanding access to metabolic neuroimaging where PET is unavailable.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.71822","type":"journal-article","created":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T05:23:03Z","timestamp":1789190583000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SynthPET: A 3D generative AI approach for FDG\u2010PET image synthesis from T1\u2010weighted MRI and ASL CBF in Alzheimer's 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