159 Longitudinal change in biomarkers previously (11). Forty-two individuals underwent a follow-up [18F]flortaucipir PET scan using the same procedure with a mean follow-up time of 2.1 ± 0.3 years. Baseline structural MRI images were obtained at five different systems (GE Discovery MR750 3T (n=22), Philips PETMR 3T (n=51), Signa 1.5T (n=1), Titan 3T (n=17) and external scan (n=1)). The protocol included 3D T1-weighted images, 3D T2-weighted images, and 3D T2-weighted fluid-attenuated inversion-recovery (FLAIR) images (12). T1-weighted images were used for coregistration to PET images and for determination of the N status. Follow-up MRI was available for 79 individuals with a mean follow-up time of 2.9 ± 0.9 years. Image analysis Data were reconstructed while using standard LOR RAMLA reconstruction algorithm with corrections for dead time, decay, attenuation, random coincidences and scatter. Images were reconstructed with a matrix size of 128 × 128 × 90 and a voxel size of 2 × 2 × 2 mm3. For [18F]flortaucipir, both scan sessions (0-60 and 80-130 minutes) were coregistered into a single dataset of 29 frames (1 × 15, 3×5, 3× 10, 4×60, 2× 150, 2×300, 4 × 600 and 10 × 300 s), in which the last 10 frames belonged to the second PET session. 3D T1-weighted MR images were co-registered to PET images using Vinci software (Max Planck Institute, Cologne, Germany). Next, regions of interest (ROIs) were defined on the co-registered MRI using the probabilistic Hammers brain atlas (13) in PVElab. Receptor parametric mapping (RPM) was used to generate parametric binding potential (BPND) images with cerebellar grey matter as a reference region using PPET (10, 14-16). For [18F]florbetapir, we calculated (volume weighted) mean cortical BPND in a composite ROI consisting of orbitofrontal, temporal, parietal, anterior cingulate, posterior cingulate and precuneus regions (6, 17). Biomarkers: A, T, N Availability of biomarker status at two time points differed for each of the biomarkers (A: n=92; T: n=42; N: n=79). For 39 individuals, a complete ATN profile over time could be constructed. The time difference with the [18F]florbetapir scan was 0.05±0.15y for [18F]flortaucipir scans and 0.16±0.62y for MRI scans. We used visual assessment of [18F]florbetapir PET scans as biomarker for A. We used [18F]flortaucipir PET scans as biomarker for T. We pragmatically used Gaussian Mixture Modeling to obtain a threshold. We first averaged values for the anterior part of the lateral temporal lobe for left and right sides. We then fit Gaussian Mixture Models with two components using the normalmixEM function in R. A threshold was derived representing the mean of the calculated mu of both components, resulting in a threshold 0.08 BPND. We used the average medial temporal atrophy rating (MTA) on MRI as biomarker for 7