[<sup>18</sup>F]PI‐2620 PET in four‐repeat tauopathies: a preliminary study
Bibliographic record
Abstract
Abstract Background There is a critical need for tau PET radiotracers that accurately detect non‐Alzheimer’s disease (AD) tau pathology. We aim to evaluate [18F]PI‐2620 PET tracer retention in patients with non‐AD, 4R tau‐related clinical syndromes, including progressive supranuclear palsy (PSP) with Richardson’s syndrome (PSP‐RS) and with predominant parkinsonism (PSP‐P), corticobasal syndrome (CBS), and nonfluent/agrammatic variant of primary progressive aphasia (nfvPPA). Method 38 participants underwent amyloid and [18F]PI‐2620 PET (Table 1). 5 mCi ± 10% of [18F]PI‐2620 was administered. [18F]PI‐2620 PET SUVR images were generated using an inferior cerebellar gray matter reference from PET data acquired 30‐60 minutes post‐injection. Mean SUVR values were extracted from each participant in neuroanatomical structures that have elevated tau burden in PSP and CBS due to corticobasal degeneration (regions of interest in Table 2). Comparison between each diagnostic group and healthy controls (HCs) was performed using a one‐tailed, independent‐samples t‐test. Spearman correlation was used to evaluate the relationship between tracer binding (SUVR) and disease severity (PSP rating scale) in patients with PSP‐RS. Result Patients with PSP‐RS had increased tracer retention in the left globus pallidus internus and externus, left subthalamic nucleus, and left dorsolateral prefrontal cortex compared to HCs (all p < 0.05). CBS and nfvPPA patients did not have increased tracer retention at any ROIs compared to HCs, but there were low numbers of patients in these groups (Table 2, Figures 1‐3). PSP rating scale values did not correlate with tracer binding in PSP‐RS (no correlations in any regions, rs < 0.44, p > 0.05 uncorrected). Conclusion [18F]PI‐2620 PET 30‐60 minute SUVR images may have limited ability to distinguish PSP from HCs, especially on visual read, and tracer uptake did not correlate with PSP disease severity. Other post‐injection PET acquisition windows (e.g., 30‐40 minute SUVR, 0‐60 minute DVR) will be evaluated to determine if they can maximize differences between PSP and HCs. A limitation of this preliminary study is the modest number of patients and controls, with most controls provided from a different study. Additional participants are being scanned in the multicenter 4RTNI study to understand the utility of this tracer as a neuroimaging biomarker for 4R tauopathies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".