A zero-dose synthetic baseline for the personalized analysis of [18F]FDG-PET: Application in Alzheimer’s disease - Hinge, Christian; Henriksen, Otto Mølby; Lindberg, Ulrich; Hasselbalch, Steen Gregers; Højgaard, Liselotte; Law, Ian; Andersen, Flemming Littrup; Ladefoged, Claes Nøhr (Frontiers in Neuroscience, 2022)
Purpose: Brain [18F]FDG-PET is widely used in the diagnostic workup of Alzheimer’s disease (AD). Current tools for uptake analysis rely on non-personalized templates, which poses a challenge as a decreased glucose uptake could reflect neuronal dysfunction, or heterogenous brain morphology associated with normal ageing. Overcoming this, we propose a deep learning method for synthesizing a personalized [18F]FDG-PET baseline from the patient’s own MRI, and showcase its applicability in detecting AD pathology. Methods: We included [18F]FDG-PET/MRI data from 123 patients of a local cohort and 600 patients from ADNI. A supervised, adversarial model with two connected GANs was trained on cognitive normal (CN) patients with transfer-learning to generate full synthetic baseline volumes (sbPET) (192x192x192) which reflect healthy uptake conditioned on brain anatomy. Synthetic accuracy was measured by absolute relative %-difference (Abs%), relative %-difference (RD%), and peak signal-to-noise ratio (PSNR). Lastly, we deployed the sbPET images in a fully personalized method for localizing metabolic abnormalities. Results: The model achieved a spatially uniform Abs% of 9.4%, RD% of 0.5% and a PSNR of 26.3 for CN subjects. The sbPET images conformed to the anatomical information dictated by the MRI and proved robust in presence of atrophy. The personalized abnormality method correctly mapped the pathology of AD subjects while showing little to no anomalies for CN subjects. Conclusion This work demonstrated the feasibility of synthesizing fully-personalized, healthy-appearing [18F]FDG-PET images. Using these, we showcased a promising application in diagnosing AD, and theorized the potential value of sbPET images in other neuroimaging routines.