Characterizing Myocardial Edema and Hemorrhage Using Quantitative T2 and T2* Mapping at Multiple Time Intervals Post ST-Segment Elevation Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: Accurate characterization of the longitudinal trends of myocardial edema and hemorrhage has been previously limited by subjective qualitative methods. We aimed to prospectively characterize the evolution of myocardial edema and hemorrhage post acute myocardial infarction using quantitative measures. METHODS AND RESULTS: Sixty-two patients were enrolled post primary percutaneous coronary intervention and underwent cardiovascular magnetic resonance on a 1.5-T scanner at 48 hours, 3 weeks, and 6 months. Myocardial edema and hemorrhage were assessed by T2 and T2* mapping, respectively, in both infarct segment (IS) and remote segment (RS). At 48 hours, T2 is higher in IS compared with RS (56.7 ms versus 43.4 ms; P<0.01). At 3 weeks T2 remains higher in IS compared with RS (51.8 ms versus 39.5 ms; P<0.01), and subsequently equalizes by 6 months (39.8 ms versus 39.5 ms; P=nonsignificant). T2 is also increased in RS at day 2 versus 3 weeks (43.4 ms versus 39.5 ms; P<0.01). At 48 hours T2* was reduced in IS compared with RS (32.4 ms versus 37.4 ms; P<0.01). At 3 weeks (IS, 37.7 ms versus RS, 38.4 ms; P=nonsignificant) and 6 months (IS, 37.3 ms versus RS, 38.2 ms; P=nonsignificant), T2* values were equal in both segments. CONCLUSIONS: Quantification of myocardial edema and hemorrhage by T2 and T2* mapping is feasible post acute myocardial infarction and demonstrates that hemorrhage resolves faster than edema. Noninfarcted segments can also demonstrate edema in the acute phase possibly due to global hyperemia.
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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 | 0.000 | 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) | 0.001 | 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".