## 2 Materials and Methods
### F-FDG-PET Data  
All PET scans were conducted at the Nuclear Medicine Unit of the University Hospital \"Policinico Tor Vergata\" in Rome using a General Electric VCT PET/CT scanner (GE Medical Systems, Powell, TN, USA). Participants fasted for at least 5 h before the intravenous administration of 18F-FDG, and serum glucose concentrations were confirmed to be within acceptable ranges, as recommended by the European Association of Nuclear Medicine guidelines [20]. Patients received an intravenous injection of 18F-FDG (dose ranging from 185 to 295 MBq), followed by hydration with 500 mL of saline solution (0.9% sodium chloride). Imaging began 30 min post-injection and lasted for ten minutes. Detailed acquisition and reconstruction parameters were consistent with those described in the cited guidelines [20]. Brain uptake of 18F-FDG was assessed using Statistical Parametric Mapping (SPM) 12 software (Wellcome Department of Cognitive Neurology, London, UK; available at [[https://www.fil.ion.ucl.ac.uk/spm/software/spm12/](https://www.fil.ion.ucl.ac.uk/spm/software/spm12/)]([https://www.fil.ion.ucl.ac.uk/spm/software/spm12/](https://www.fil.ion.ucl.ac.uk/spm/software/spm12/)), accessed on 1 January 2025) running on MATLAB 2022b (Mathworks, Natick, MA, USA). PET data underwent conversion from DICOM to Nifti format utilizing MRIcoron software (accessible at [[https://www.nitrc.org/projects/micron/](https://www.nitrc.org/projects/micron/)]([https://www.nitrc.org/projects/micron/](https://www.nitrc.org/projects/micron/)), accessed on 1 January 2025), followed by normalization procedures. To minimize image intensity distortions caused by spatially varying artifacts and enhance the accuracy of automated processing, a bias regularization factor of 0.0001 was applied. Additionally, the Gaussian smoothing kernel's full width at half maximum (FWHM) was restricted to 60 mm to prevent the algorithm from modeling intensity variations attributed to distinct tissue types. For image processing, a bias regularization factor and a smoothing kernel of an 8 mm full width at half maximum (FWHM) were selected to balance sensitivity and specificity, minimizing noise while preserving regional anatomical accuracy, consistently with standard PET imaging recommendations. The tissue probability map embedded in SPM12 was internally developed from brain 18F-FDG PET scans, including data from 285 Alzheimer's disease patients and 121 healthy control subjects. An affine registration with mutual information with the tissue probability maps [21] was used to achieve approximate alignment with the ICBM spatial template European brains [22]. Warping regularization was set with 1 \(\times\) 5 arrays (0, 0.001, 0.5, 0.05, 0.2); smoothing (to cope with functional anatomical variability not compensated by spatial normalization and to improve signal-to-noise ratio) was set to 5 mm; and the sampling distance (encoding the approximate distance between sampled points in estimating model parameters) was set to 3. The clusters containing the cortex, ventricles (CSF), and pons (see below) were exported by the means of the WFU PickAtlas tool implemented in SPM 12 (WFU PickAtlas (RRID:SCR_007378); available online: [[https://www.nitrc.org/projects/wfu_pickatlas/](https://www.nitrc.org/projects/wfu_pickatlas/)]([https://www.nitrc.org/projects/wfu_pickatlas/](https://www.nitrc.org/projects/wfu_pickatlas/)) (access on 23 April 2025)) [23] (Figure 1). Specifically, the mean signal intensities calculated from the cortex and ventricles within each subject were normalized to the average intensities of the pons volume of interest. The use of normalization based on activity in the pons, rather than the cerebellum, brainstem, or primary sensorimotor cortex, has been reported to result in greater accuracy in discriminating patients from controls in neurodegenerative diseases [20; 24]. Normalization to the pons was chosen due to its demonstrated stability and robustness in AD, as metabolism in this region is relatively preserved even in early stages of neurodegeneration.