Can the Inflammatory Response Be Evaluated Using <sup>18</sup>F-FDG Within Zones of Microvascular Obstruction After Myocardial Infarction?
Bibliographic record
Abstract
UNLABELLED: Inflammation that occurs after acute myocardial infarction plays a pivotal role in healing by facilitating the creation of a supportive scar. (18)F-FDG, which is taken up avidly by macrophages, has been proposed as a marker of cell-based inflammation. However, its reliability as an accurate indicator of inflammation has not been established, particularly in the early postinfarction period when regional myocardial perfusion is often severely compromised. METHODS: Nine adult dogs underwent left anterior descending coronary occlusion with or without reperfusion. Animals were imaged between 7 and 21 d after infarction with PET/MR imaging after bolus injection of gadolinium-diethylenetriaminepentaacetic acid (DTPA), bolus injection of (18)F-FDG, bolus injection of (99)Tc-DTPA to simulate the distribution of gadolinium-DTPA (which represents its partition coefficient in well-perfused tissue), and injection of (111)In-labeled white blood cells 24 h earlier. After sacrifice, myocardial tissue concentrations of (18)F, (111)In, and (99)Tc were determined in a well counter. Linear regression analysis evaluated the relationships between the concentrations of (111)In and (18)F and the dependence of the ratio of (111)In/(18)F to the apparent distribution volume of (99m)Tc-DTPA. RESULTS: In 7 of 9 animals, (111)In increased as (18)F increased with the other 2 animals, showing weak negative slopes. With respect to the dependence of (111)In/(18)F with partition coefficient, 4 animals showed no dependence and 4 showed a weak positive slope, with 1 animal showing a negative slope. Further, in regions of extensive microvascular obstruction, (18)F significantly underestimated the extent of the presence of (111)In. CONCLUSION: In the early post-myocardial infarction period, (18)F-FDG PET imaging after a single bolus administration may underestimate the extent and degree of inflammation within regions of microvascular obstruction.
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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 | 0.004 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".