Diffusion Bridge Networks Simulate Clinical-Grade PET From MRI for Dementia Diagnostics
MCML Authors
Björn Ommer
Prof. Dr.
Principal Investigator
Christian Wachinger
Prof. Dr.
Principal Investigator
Abstract
Björn Ommer
Prof. Dr.
Principal Investigator
Christian Wachinger
Prof. Dr.
Principal Investigator
Abstract
Positron emission tomography (PET) with 18F-Fluorodeoxyglucose (FDG) is an established tool in the diagnostic workup of patients with suspected dementing disorders. However, compared to the routinely available magnetic resonance imaging (MRI), FDG-PET remains significantly less accessible and substantially more expensive. Here, we present SiM2P, a 3D diffusion bridge-based framework that learns a probabilistic mapping from MRI and auxiliary patient information to simulate FDG-PET images of diagnostic quality. In a blinded clinical reader study, two neuroradiologists and two nuclear medicine physicians rated the original MRI and SiM2P-simulated PET images of patients with Alzheimer's disease, behavioral-variant frontotemporal dementia, and cognitively healthy controls. SiM2P significantly improved the overall diagnostic accuracy of differentiating between three groups from 75.0% to 84.7% (p<0.05). Notably, the simulated PET images received higher diagnostic certainty ratings and achieved superior interrater agreement compared to the MRI images. Finally, we developed a practical workflow for local deployment of the SiM2P framework. It requires as few as 20 site-specific cases and only basic demographic information. This approach makes the established diagnostic benefits of FDG-PET imaging more accessible to patients with suspected dementing disorders, potentially improving early detection and differential diagnosis in resource-limited settings.
misc
Preprint
Oct. 2025Authors
Y. Li • R. Buchert • B. Schmitz-Koep • T. Grimmer • B. Ommer • D. M. Hedderich • I. Yakushev • C. WachingerLinks
GitHubResearch Areas
BibTeXKey: LBS+25