HAI Book 2025 - Flipbook - Page 76
Povala, Guilherme
The Uni�㔏 Ecosystem for tau-PET harmonization and visualization
Guilherme Bauer-Negrini1, Guilherme Povala1, Bruna Bellaver1, Pamela Lukasewicz Ferreira1,
Firoza Z. Lussier1, Livia Amaral1, Dana L. Tudorascu1, Joseph Masdeu2, David SoleimaniMeigooni3, Juan Fortea4, Val Lowe5, Hwamee Oh6, Belen Pascual2, Brian A. Gordon7, Pedro
Rosa-Neto8, Suzanne Baker9, Tharick A. Pascoal1
1
University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, US
Houston Methodist Research Institute, Department of Neurology, Houston, TX, US
3
University of California San Francisco, Memory and Aging Center, San Francisco, CA, US
4
Hospital de la Santa Creu i Sant Pau, Sant Pau Memory Unit, Department of Neurology, Barcelona, ES
5
Mayo Clinic, Department of Radiology, Rochester, MN, US
6
Brown University, Department of Psychiatry and Human Behavior, Providence, RI, US
7
Washington University in St. Louis, Department of Radiology, Saint Louis, MO, US
8
Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research
Institute, Montréal, QC, CA
9
Lawrence Berkeley National Laboratory, Berkeley, CA, US
2
Background: HEAD is a longitudinal, multi-site, non-randomized study aiming to harmonize different tau-PET
tracers onto a common scale. To achieve this, the Uniτ scale is being developed using data from 620 participants
scanned head-to-head with Flortaucipir and MK-6240, with a subset (n=175) also scanned with PI-2620 and RO948. However, access to the Uniτ scale has been limited to the study community and collaborators. To address
this limitation, we have developed the Uniτ Ecosystem4a set of tools to increase Uniτ functionality.
Methods: The Uniτ Ecosystem tools were developed for multiple operating systems (macOS/Windows/Ubuntu)
(Fig.1) and currently include 1) a calculator app for rapid and convenient harmonization. 2) An online region-ofinterest harmonization module to harmonize multiple SUVRs from spreadsheets. 3) A 3D harmonization module
for voxel-wise harmonization. 4) A 3D visual reading package (under development). Researchers can use their own
datasets or test harmonization models using data from a training set of participants. The tools include a feedback
box that allows users to provide input to Uniτ developers, facilitating continuous scale improvement.
Results: The calculator app enables users to harmonize single SUVR values effortlessly. The online ROI
harmonization module extends the calculator's capabilities by allowing users to harmonize SUVRs uploaded from
spreadsheets and offers interactive visualizations such as scatter plots and histograms for tau positivity
thresholds (Fig.2). The desktop application for 3D tau-PET harmonization leverages the functionalities of the
previous modules to harmonize entire 3D images, eliminating the need for predefined ROIs. Additionally, this
module provides visualization tools for the parametric Uniτ images and visual reading ratings (Fig.3). No module
retains any type of data from users.
Conclusions: The Uniτ Ecosystem represents a major convenience in tau-PET use, providing researchers with a
user-friendly platform to harmonize and visualize tau-PET data. Researchers can request free access to the
Ecosystem at www.unitau.app.
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