Determining the extent to which delayed‐enhancement images reflect the partition‐coefficient of Gd‐DTPA in canine studies of reperfused and unreperfused myocardial infarction
Bibliographic record
Abstract
MRI after a constant infusion (CI) of Gd-DTPA has been used to identify the extent of myocardial infarction (MI). However, Gd-DTPA-enhanced "viability" imaging is more commonly performed with a bolus (for "delayed-enhancement" (DE) imaging). This study sought to determine how image delay time and time postinfarction influence the assessment of necrosis by DE. Both infusion and DE imaging was performed in dogs with reperfused (N = 6) or unreperfused (N = 4) MI. Estimates of the partition-coefficient of Gd-DTPA (lambda) with DE were compared with those calculated after 60 min of infusion, and the comparisons were repeated until 4 (reperfused) or 8 (unreperfused) weeks postinfarction. In reperfused animals, the concordance (Rc) between DE and infusion estimates of lambda was > 0.90 for most image delays > 8 min postinjection, for day 0 through week 3, with Rc at day 0 greater than at week 4 (P = 0.022). In unreperfused animals, there was an interaction between image delay time and time postinfarction (P < 0.001): Rc > 0.90 corresponded to longer image delays at week 1 than at weeks 4-8. Therefore, when image delays are selected appropriately, DE images can strongly reflect lambda and identify irreversibly injured myocardium.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".