Development, initial validation, and application of a visual read method for [ <sup>18</sup> F]MK‐6240 tau PET
Bibliographic record
Abstract
Abstract Background The positron emission tomography (PET) radiotracer [ 18 F]MK‐6240 exhibits high specificity for neurofibrillary tangles (NFTs) of tau protein in Alzheimer's disease (AD), high sensitivity to medial temporal and neocortical NFTs, and low within‐brain background. Objectives were to develop and validate a reproducible, clinically relevant visual read method supporting [ 18 F]MK‐6240 use to identify and stage AD subjects versus non‐AD and controls. Methods Five expert readers used their own methods to assess 30 scans of mixed diagnosis (47% cognitively normal, 23% mild cognitive impairment, 20% AD, 10% traumatic brain injury) and provided input regarding regional and global positivity, features influencing assessment, confidence, practicality, and clinical relevance. Inter‐reader agreement and concordance with quantitative values were evaluated to confirm that regions could be read reliably. Guided by input regarding clinical applicability and practicality, read classifications were defined. The readers read the scans using the new classifications, establishing by majority agreement a gold standard read for those scans. Two naïve readers were trained and read the 30‐scan set, providing initial validation. Inter‐rater agreement was further tested by two trained independent readers in 131 scans. One of these readers used the same method to read a full, diverse database of 1842 scans; relationships between read classification, clinical diagnosis, and amyloid status as available were assessed. Results Four visual read classifications were determined: no uptake, medial temporal lobe (MTL) only, MTL and neocortical uptake, and uptake outside MTL. Inter‐rater kappas were 1.0 for the naïve readers gold standard scans read and 0.98 for the independent readers 131‐scan read. All scans in the full database could be classified; classification frequencies were concordant with NFT histopathology literature. Discussion This four‐class [ 18 F]MK‐6240 visual read method captures the presence of medial temporal signal, neocortical expansion associated with disease progression, and atypical distributions that may reflect different phenotypes. The method demonstrates excellent trainability, reproducibility, and clinical relevance supporting clinical use. Highlights A visual read method has been developed for [ 18 F]MK‐6240 tau positron emission tomography. The method is readily trainable and reproducible, with inter‐rater kappas of 0.98. The read method has been applied to a diverse set of 1842 [ 18 F]MK‐6240 scans. All scans from a spectrum of disease states and acquisitions could be classified. Read classifications are consistent with histopathological neurofibrillary tangle staging literature.
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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 | 0.033 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".