Flow-Dependent Uptake of <sup>123</sup>I-CMICE-013, a Novel SPECT Perfusion Agent, Compared with Standard Tracers
Bibliographic record
Abstract
UNLABELLED: Rotenone derivatives have shown promise in myocardial perfusion imaging (MPI). CMICE-013 is a novel (123)I-labeled rotenone derivative developed for SPECT MPI. The objective of this study was to assess the image quality of CMICE-013 and compare its uptake with tetrofosmin, sestamibi, and (201)Tl in vivo in a porcine model of stress-induced myocardial ischemia. METHODS: Microspheres were injected simultaneously with the radiotracer injections at rest and stress to measure blood flow. Mimicking a 1-d tetrofosmin protocol, stress imaging used 3 times as much activity and occurred 1 h after the rest injection. SPECT images were obtained at both rest and stress. After imaging, the heart was sectioned into 44-50 pieces. In each heart sample, the tracer uptake was measured in a γ counter. The images were aligned, and the decay-corrected ratio of the signals at rest and stress was used to separate the well-counter signal into rest and stress components. The uptake at rest and stress was compared with microsphere flow measurements. RESULTS: The CMICE-013 images showed good contrast between the heart and surrounding organs, with heart-to-liver and heart-to-lung uptake ratios similar to those of the standard tracers. Uptake of CMICE-013 was 1.5% of the injected dose at rest and increased more rapidly with increased blood flow than did the standard SPECT tracers. The percentage injected dose of CMICE-013 taken up by the heart was greater (P < 0.05) than (201)Tl, tetrofosmin, or sestamibi at flows greater than 1.5 mL/min/g. CONCLUSION: CMICE-013 is a promising new SPECT MPI agent.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".