Quantitative tracking of edema, hemorrhage, and microvascular obstruction in subacute myocardial infarction in a porcine model by MRI
Bibliographic record
Abstract
Pathophysiological responses after acute myocardial infarction include edema, hemorrhage, and microvascular obstruction along with cellular damage. The in vivo evolution of these processes simultaneously throughout infarct healing has not been well characterized. The purpose of our study was to quantitatively monitor the time course of these mechanisms by MRI in a porcine model of myocardial infarction. Ten pigs underwent MRI before coronary occlusion with subgroups studied at day 2 and weeks 1, 2, 4, and 6 post-infarction. Tissue characterization was performed using quantitative T2 and T2* maps to identify edema and hemorrhage, respectively. Contrast-enhanced MRI was used for infarct/ microvascular obstruction delineation. Inflammation was reflected by T2 fluctuations, however at day 2, edema and hemorrhage had counter-acting effects on T2. Hemorrhage (all forms) and mineralization (calcium) could be identified by T2* in the presence of edema. Simultaneous resolution of microvascular obstruction and T2* abnormality suggested that the two phenomenon were closely associated during the healing process. Our study demonstrates that quantitative T2 and T2* mapping techniques allow regional, longitudinal, and cross-subject comparisons and give insights into histological and tissue remodeling processes. Such in vivo characterization will be important in grading severity and evaluating treatment strategies for myocardial infarction, potentially improving clinical outcomes.
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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 | 0.000 |
| 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) | 0.001 | 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".