Multicenter F-18-PI-2620 PET for in vivo staging of tau pathology in progressive supranuclear palsy
Bibliographic record
Abstract
Ziel/Aim Progressive supranuclear palsy (PSP) is a primary 4R tauopathy. Post mortem studies identified six tau pathological stages. In PSP, tau aggregates start accumulating in the subthalamic nucleus (STN), with subsequent involvement of the globus pallidus (GP), striatum (ST), cerebellum with dentate nucleus (DN), frontal (FC) and occipital cortices (OC) [ 1 ]. We aimed to test whether this staging system is replicable by in vivo F-18-PI-2620 tau PET imaging. Methodik/Methods We analyzed data of 85 patients with the clinical diagnosis of PSP including 44 Richardson syndrome (RS)-PSP (19♀; age: 72±7yrs; PSPRS: 38±14; SEADL: 54±20; disease duration: 47±28months), 41 nonRS-PSP (17♀; age: 71±8yrs; PSPRS: 29±12; SEADL: 60±18; disease duration: 38±34months) patients and of 26 healthy controls (13♀; age: 67±11yrs). Dynamic F-18-PI-2620 PET imaging in a multicenter setting (sites in Germany, USA and Australia) was performed over 60min. After kinetic modeling (MRTM2, reference region=lower cerebellum), parametric distribution volume ratio images were analyzed and classified into six PSP stages according to the above hierarchical scheme [ 1 ]. The data of the controls defined the normal range (mean+2.5 SD) for each tau-in-PSP VOI. Ergebnisse/Results Tau-in-PSP VOI positivity varied regionally with 16% for STN, 18% for GP, 33% for ST, 19% for DN, 1% for FC and 5% for OC. 64% of RS-PSP patients were PET-positive, with 41% hierarchically staged as stage 1, 16% as stage 2, and 7% as stage 3. In the nonRS-PSP group, the frequencies were lower (46%, 36%, 5%, and 5%, respectively). In nonRS-PSP patients we found a correlation between highest PSP stage and age (r=0.37, p=0.02). In vivo tau PET staging was not associated with scores of clinical disease duration (PSPRS, SEADL or disease duration). Schlussfolgerungen/Conclusions In conclusion, F-18-PI-2620 PET seems to be able to perform in vivo PSP tau staging in vivo. Our data, however, challenge the concept of only one hierarchical system. More data are necessary to also elucidate the relation between the F-18-PI-2620 PET signal and the severity of the clinical phenotype. Publication History Article published online: 14 April 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".