A Semiautomated Method for Quantification of F 18 Florbetapir PET Images
Bibliographic record
Abstract
UNLABELLED: PET amyloid imaging is increasingly used in research trials related to Alzheimer disease and has potential as a quantitative biomarker. This study had 3 objectives: first, to describe a semiautomated quantitative method that does not require subject-specific MR imaging scans for estimating F 18 Florbetapir plaque binding using 10-min PET images; second, to evaluate the method's accuracy for identifying positive and negative scans; and third, to correlate derived standardized uptake value ratios to neuropathologic measures of amyloid. METHODS: The F 18 Florbetapir PET images are initially converted to Montreal Neurologic Institute brain atlas space using an internally developed PET target F 18 Florbetapir template. Subsequently, a single mean cortical standardized uptake value ratio (mcSUVr) is calculated from the mean standardized uptake value of 6 cortical regions normalized to a reference region. Four reference regions were explored: whole cerebellum, cerebellar gray matter, pons, and centrum semiovale. The performance of the resultant mcSUVrs were evaluated in 74 young cognitively normal subjects (age < 50 y) with a negligible likelihood of amyloid β pathology, and in 59 deceased subjects with autopsy-based amyloid β neuritic plaque measure who underwent F 18 Florbetapir PET imaging before death. RESULTS: Significant correlations were obtained between mcSUVrs and 3 different pathologic measures of amyloid deposition at autopsy using all 4 reference regions, with the whole-cerebellum mcSUVr correlating most strongly across pathologic measures (r = 0.71-0.75, P < 0.0001). Using the whole-cerebellum mcSUVr and a threshold mcSUVr of less than 1.10, 100% of young cognitively normal subjects were correctly classified as amyloid-negative (mcSUVr range, 0.87-1.08). Similarly, 20 of 20 autopsy-negative subjects showed mcSUVrs of 1.10 or less, whereas 38 of 39 pathology-verified amyloid-positive subjects had mcSUVrs of more than 1.10. CONCLUSION: This semiautomated F 18 Florbetapir PET quantification method yielded mcSUVrs that significantly correlated with measures of amyloid pathology at autopsy. The method also effectively discriminated autopsy-identified amyloid-positive and -negative cases using a whole-cerebellum mcSUVr threshold of 1.10.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".