P2‐460: Amyloid imaging with [<sup>11</sup>C]SB‐13 PET: A test‐retest reliability study
Bibliographic record
Abstract
The purpose of this study is to assess the reliability of in-vivo beta-amyloid imaging with [C]SB-13 positron emission tomography (PET). The validity had been previously assessed by comparison with [C]PIB PET (Am J Geriatr Psychiatry 2004;12:584-595). Ten mild AD patients (7 males, 3 females; age 72±13 years; MMSE scores 22.3±2.9) and 10 matched healthy controls ((7 males, 3 females; age 70±15 years; MMSE scores 29.6±0.7; MOCA scores 27.4±2.4) each underwent a magnetic resonance imaging (MRI) scan and two 90-minute PET scans following about 10 mCi intravenous administration of [C]SB-13. The test-retest intervals for the PET scans were 42±17 days for the mild AD patients and 32±26 days for the controls. Regions of interest were created using a semi-automated brain region extraction from the MRI images, which were then coregistered with the PET images. Standardized uptake values (SUVs) were calculated by normalizing tissue concentration (nCi/mL) by injected dose per body mass (nCi/g) 40-90 minutes post injection. Standardized uptake value ratios (SUVRs) of the region of interest divided by the cerebellum (reference region) were calculated. Coefficients of variation (COVs: [standard deviation / average] * 100%) for the SUVs and SUVRs were calculated. One 88-year-old male outlier control (average SUV 3.04, SUVR 1.67) was omitted from the comparison. Average ± standard deviation of the [C]SB-13 PET SUVs for all brain regions combined were 1.99±0.42 for the 10 mild AD patients and 1.35±0.22 for the 9 controls (effect size 1.98). The SUVRs for all brain regions combined were 1.26±0.21 for the 10 mild AD patients and 0.99±0.06 for the 9 controls (effect size 2.01). The COVs for the SUVs in all regions combined were 8.49±5.61% for the 10 mild AD patients and 8.76±5.46% for the 10 controls. The COVs for the SUVRs in all regions combined were 1.37±1.12% for the 10 mild AD patients and 1.81±0.82% for the 10 controls. Our preliminary data suggest that [C]SB-13 PET SUVRs and SUVs are reliable in mild AD patients and controls. Additional semi-quantification methods, such as binding potential estimates, could provide superior effect sizes reflecting the ability to distinguish AD patients from controls.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".