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Record W4411139137 · doi:10.1007/s00259-025-07396-8

Developing a novel reference region for [18F]PI-2620-PET imaging to facilitate the assessment of 4-repeat tauopathies

2025· article· en· W4411139137 on OpenAlexaff
Lukas Frontzkowski, Johannes Gnörich, Mattes Groß, Amir Dehsarvi, Sebastian Niclas Roemer, Carla Palleis, Sabrina Katzdobler, Anna Dewenter, Anna Steward, Davina Biel, Fabian Hirsch, Zeyu Zhu, Johannes Levin, Andrew Stephens, André Müller, Norman Koglin, Gérard N. Bischof, Gábor G. Kovács, Günter U. Höglinger, Matthias Brendel, Nicolai Franzmeier

Bibliographic record

VenueEuropean Journal of Nuclear Medicine and Molecular Imaging · 2025
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsOntario Brain InstituteOccupational Cancer Research CentreUniversity Health Network
Fundersnot available
KeywordsPositron emission tomographyMedicineNuclear medicineMedical physics

Abstract

fetched live from OpenAlex

PURPOSE: Progressive supranuclear palsy (PSP) is a fatal 4-repeat (4R) tauopathy with progressive movement phenotypes. In-vivo 4R tau biomarkers are therefore crucial for PSP diagnosis, monitoring, and treatment evaluation. The tau-PET tracer [18F]PI-2620 binds to 4R tau and shows increased uptake in PSP-associated regions (e.g., globus pallidus), and is therefore a candidate 4R tau biomarker. However, commonly used cerebellar tau-PET reference regions show regional proximity to cerebellar 4R tau deposits in PSP, confounding semiquantitative [18F]PI-2620 assessments. Therefore, we employed bias-free image-derived input function (IDIF) PET quantification to identify an optimized data-driven reference region for assessing 4R tau in PSP. METHODS: Dynamic [18F]PI-2620 PET (60 min) was acquired in 58 PSP-Richardson Syndrome (PSP-RS) and 18 healthy controls (HC). IDIF-modelling with carotid timeseries derived total distribution volume (VT). Iteratively normalizing VT images to atlas-based white matter (WM), we identified reference candidates maximizing PSP-RS vs. HC pallidum differences. The best-performing WM references were combined to a temporo-orbital WM reference, validated in PSP-nonRS (n = 54), HC (n = 18), and disease controls (α-synucleinopathies, n = 21; Alzheimer’s disease (AD, n = 22) using VT-ratios (VTr) and 20-40min static standardized uptake value ratios (SUVr). RESULTS: Using the data-driven temporo-orbital WM reference, PSP patients showed significantly higher basal ganglia [18F]PI-2620 signal vs. HC compared to cerebellar normalization. Receiver operating curve (ROC) analysis confirmed higher diagnostic accuracy using the temporo-orbital WM reference. Pallidum [18F]PI-2620 showed significant associations with clinical disease severity exclusively when using the novel temporo-orbital WM reference. CONCLUSIONS: A data-driven temporo-orbital WM reference optimizes [18F]PI-2620 PET assessment for PSP diagnosis, outperforming conventional cerebellar references used in tau-PET imaging.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.324
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes1
Has abstractyes

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