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In neurodegenerative disorders, including Alzheimer's disease and progressive supranuclear palsy, abnormal accumulation of tau protein occurs in the brain. Identifying the location and extent of tau accumulation in vivo is crucial for understanding disease mechanisms and progression.

PET imaging with florzolotau (18F), a radiotracer that binds to tau aggregates, can visualize tau pathology. The cerebellum is often used as a reference region; however, abnormal tau accumulation also affects the cerebellum in some non-Alzheimer's tauopathies.

Therefore, previous studies have proposed estimating reference values from the distribution of PET signal intensity in gray matter. However, image analysis typically relies on laboratory-specific programs or commercial software, hindering analytical reproducibility and cross-study comparisons.

In this study, the researchers developed and released TAME-Q, software that implements an established semiquantitative analysis method. It automatically processes PET and structural MRI data, estimates reference values, generates standardized uptake value ratio (SUVR) images and calculates regional SUVRs as semiquantitative measures of tracer uptake.

The software was evaluated using imaging data from 133 participants: 37 individuals on the Alzheimer's disease continuum, 46 patients with progressive supranuclear palsy–Richardson syndrome and 50 healthy controls. The automated pipeline successfully processed all data sets, and its measurements were consistent with findings from previous studies of Alzheimer's disease and progressive supranuclear palsy. Additionally, machine learning–derived tau scores calculated from regional SUVRs obtained using TAME-Q correlated with benchmark scores reported in the previous study.

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