Comparing Off‐Target Meningeal and Skull Signal in Head‐to‐Head MK‐6240 and AV‐1451 Tau PET
Bibliographic record
Abstract
BACKGROUND: Tau tangle deposition is associated with Alzheimer disease (AD) clinical symptomology and cognitive decline. Such deposition can be measured in vivo using positron emission tomography (PET). Off-target signal from extra-cerebral sources, such as skull or meninges, may bias quantification but the impact is currently unknown. Here, we investigate off-target sources in individuals with crossover 18F-AV-1451 and 18F-MK-6240 tau PET scans within the HEAD study. METHOD: T1-weighted magnetic resonance imaging (MRI), Pittsburgh Compound B (PiB) amyloid PET, and tau PET were acquired for 42 participants. Tau PET scans were quantified using body-weighted standardized uptake values (SUV) and SUV ratios (SUVRs) with cerebellar grey as the reference region. To isolate skull bone, CT scans from each participant were aligned to their own T1 image and threshold using a Hounsfield units cutoff derived from applying Gaussian mixture modeling on the average of all CT images to identify a skull bone compartment. For meninges, MNI-152 aligned 18F-MK-6240 SUVR images were averaged and thresholded to identify voxels that potentially were meninges. This template was then transformed back into participant space and masked using the skull bone image and a brain mask to isolate those voxels that were neither bone nor brain but fell in-between, producing a subject-specific meningeal mask (Figure 1). Group average SUV images were created between amyloid negative and positive individuals. RESULT: Average age of participants was 66 (21-88) years. 25 were biologically female and 15 were amyloid positive. Group average SUV images show extra-cerebral off-target signal was more pronounced in 18F-MK-6240 for both amyloid negative and positive individuals compared to 18F-AV-1451 (Figure 2). The extra-cerebral 18F-MK-6240 signal appeared across the entire cortical surface and posterior cerebellum, potentially impacting a cerebellar reference for tau PET SUVR quantification. CONCLUSION: While off-target extra-cerebral signal appears in both tau PET tracers, it was more pronounced and wide-spread in 18F-MK-6240. Subject-specific skull and meningeal masks can parse this signal to aid in cause determination. Additional work is needed to explore factors contributing to this signal, such as demographic, health, and genetic.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".