Open-source software standardizes tau PET image analysis for neurodegenerative disease research
· Medical Xpressedited by Swati Mestri, reviewed by Andrew Zinin
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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 research is published in the journal BMC Medical Imaging.
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.
Along with the release of TAME-Q, the researchers made its execution environment publicly available, allowing analyses to be conducted under the same computational conditions. By reducing the burden of software installation and configuration and providing a transparent, standardized workflow, TAME-Q is expected to support reproducible tau PET research and facilitate future studies of neurodegenerative diseases.
More information
Kenjiro Nakayama et al., TAME-Q: an open-source preprocessing pipeline for reproducible semi-quantification of florzolotau (18 F) PET, BMC Medical Imaging (2026). DOI: 10.1186/s12880-026-02775-5
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Swati Mestri
Swati Mestri holds a bachelor's degree in Electronics Engineering and has worked as a content editor since 2019. She has experience editing research documents across technology, health care, and materials science, and has a particular interest in technology and space. Full profile →
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