SILA algorithm estimates tau positivity onset from PET imaging in Alzheimer's disease cohorts

Understanding the time course of Alzheimer's disease biomarkers of amyloid and tau pathology and their temporal relation to clinical symptoms is key to identifying optimal windows for disease intervention and planning future drug trials. The goal of this work was to determine the extent to which Sampled Iterative Local Approximation (SILA), an algorithm extensively validated for amyloid PET, is capable of modeling longitudinal tau (T) PET trajectories and estimating person-level tau positivity onset ages in two commonly analyzed brain regions and two tracers from two different cohorts. Methods: 385 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI; mean (SD) age = 73.4 (7.3) years) with longitudinal flortaucipir tau PET and 288 participants from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center (collectively referred to as WISC; mean (SD) age = 67.4 (6.7) years) with longitudinal MK-6240 tau PET were included in the study. Standard uptake value ratios (SUVRs) in the entorhinal cortex and a meta-temporal ROI were modeled with SILA separately, for each cohort and region. Forward and backward SUVR and T+/- prediction were characterized with ten-fold cross-validation and in-sample validation techniques. Accuracy of estimated T+ onset ages (ETOA) was characterized in T- to T+ converters. Differences in ETOA were tested between APOE-e4 carriers and non-carriers, as well as differences in time T+ between levels of cognitive impairment. Results: SILA was able to accurately estimate retrospective change in tau SUVR in the meta-temporal region regardless of age, sex, APOE-e4 carriage, tau SUVR, and dementia (p >0.05) whereas dementia was associated with model residuals in entorhinal cortex (p [&le;] 0.05; ADNI). In subsets of observed T- to T+ converters, the difference between "observed" and estimated meta-temporal T+ onset age [95% CI] was 0.12 [-0.27, 0.52] years for ADNI and -0.09 [0.93, 0.74] years for WISC. ETOA was significantly earlier, and odds of SILA-estimated T+ status were higher amongst APOE-e4 carriers (p <0.05) and those with dementia (p <0.05). Conclusions: Our results suggest SILA can be used to accurately model longitudinal tau PET trajectories and retrospectively estimate individual T+ onset ages in the meta-temporal region. The accuracy of SILA time estimates in entorhinal cortex worsened amongst those with dementia in ADNI suggesting entorhinal cortex may only be suitable for studying the temporal progression of tau during the preclinical time frame.