Diffusion Bridge Networks Simulate Clinical-grade PET from MRI for Dementia Diagnostics

• URL: http://arxiv.org/abs/2510.15556v1
• Date: Fri, 17 Oct 2025 11:42:11 GMT
• Title: Diffusion Bridge Networks Simulate Clinical-grade PET from MRI for Dementia Diagnostics
• Authors: Yitong Li, Ralph Buchert, Benita Schmitz-Koep, Timo Grimmer, Björn Ommer, Dennis M. Hedderich, Igor Yakushev, Christian Wachinger,
• Abstract summary: We present SiM2P, a framework that learns a probabilistic mapping from MRI and auxiliary patient information to simulate FDG-PET images of diagnostic quality.<n>SiM2P significantly improved the overall diagnostic accuracy of differentiating between three groups from 75.0% to 84.7%.
• Score: 20.93414282937884
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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. Our code is available at https://github.com/Yiiitong/SiM2P.

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