Myocardial viability imaging using Gd‐DTPA: Physiological modeling of infarcted myocardium, and impact on injection strategy and imaging time
Bibliographic record
Abstract
Results of simulations are shown which illustrate how the concentration-time curves of an extravascular extracellular (EVEC) contrast agent, such as Gd-DTPA, vary in myocardial tissue. The simulations show that the variable permeability of dead myocytes within a recent myocardial infarction will significantly alter delayed enhancement patterns following a bolus injection, invariably reducing the sensitivity of this technique for the detection of permanently damaged tissue. It is further predicted that if the bolus injection is followed by a suitably selected constant infusion, the infarct size and infarct volume of distribution may be more accurately determined, even though the degree of enhancement of an infarcted region (with normal flow) above normal tissue is slightly higher for the bolus technique within the first 30 min following the injection. The degree of enhancement of an infarcted region (with normal flow) above normal tissue was comparable between the two techniques at the point in the constant infusion at which the volume of contrast injected was the same as in the bolus case, i.e., at approximately 30 min after the bolus injection. The constant infusion approach became superior thereafter as overall tissue concentrations became greater in both normal and infarcted tissue, and these concentrations remained more stable with the constant infusion approach. Preliminary experimental results in a canine model of infarction/reperfusion illustrated a delayed wash-in of contrast agent in infarcted tissue, which may be explained by a physiological model in which dead myocytes in infarcted myocardium have non-infinite permeability.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".