Comparison between 1-compartmental and 2-compartmental model in calculation of myocardium blood flow in 82Rb PET imaging
Bibliographic record
Abstract
Objective: To the best of our knowledge, no comparison between 1-compartmental (1cm) and 2-compartmental (2cm) models in calculation of myocardium blood flow (MBF) and coronary flow reserve (CFR) in 82 Rb PET imaging has been performed. We present our results of comparing 1cm and 2CM in 82 Rb myocardial PET imaging. Methods: Twenty nine patients, mean age 58±9.5 years (mean±standard deviation), were imaged at rest and pharmaco- logical stress, following an i.v. injection of 1850 MBq of 82 Rb each. A GE DLS PET-CT+16 scanner was used in this study. All images were acquired in 2D mode. For each study, 50 frames were acquired. The time per frame was 5sec between 0-3 min, 15sec between 3-5 min and 30 sec between 5-8 min. MBF was calculated by using 1cm and 2cm. The results for global and regional left circumflex artery (LCX), left anterior artery (LAD) and right coronary artery (RCA), rest and stress MBF, and CFR values obtained by 1cm and 2cm were compared by using Bland and Altman method. The reproducibility coefficient was calculated as 1.96 times the standard deviation (SD) of the differences between 1cm and 2cm values. Results: The global rest MBF values, expressed as mean± SD, for both 1cm and 2cm were very similar (0.74 ± 0.17 vs. 0.73 ± 0.17 mL/min/g), and reproducibility was good, 0.12 mL/min/g (16.3% of the mean). The same held true for the 1CM and 2CM stress global MBF values (1.71 ± 0.54 and 1.73 ± 0.50 mL/min/g) with good reproducibility of 0.25 mL/min/g (14.4% of the mean). The regional, LCX, LAD and RCA rest and stress MBF values, obtained by 1cm and 2cm, were marginally reproducible, i.e., 50% or more of the mean. The global CFR values for both 1cm and 2cm were very similar (2.44 ± 0.84 vs. 0.2.44 ± 0.89), and reproducibility was good 0.34 (14.1% of the mean). Conclusions: The MBF and CFR global rest and stress values obtained by 1cm and 2cm were close and reproducible. However, the regional LAD, RCA and LCX rest and stress MBF values showed marginal reproducibility. Limited regional MBF reproducibility may be caused by sampling error and/or cardiac and breathing motion. We believe that the reproducibility of regional values can be improved by data smoothing and motion gating.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".