Longitudinal [18F]LW223 PET imaging of macrophage-driven inflammation following myocardial infarction in a rat model: implications for left ventricular remodelling
Bibliographic record
Abstract
Abstract Purpose Inflammation affects cardiac remodelling following myocardial infarction (MI), and can be imaged using Positron Emission Tomography (PET) targeting the 18 kDa translocator protein (TSPO). We utilised a rat reperfusion MI model to assess whether longitudinal [ 18 F]LW223 could accurately measure macrophage-driven inflammation using outcome measures amenable to clinical translation, in addition to assessing the prognostic potential of [ 18 F]LW223 for cardiac dysfunction. Methods Adult male Sprague–Dawley rats underwent coronary artery ligation and reperfusion to induce MI. [ 18 F]LW223 PET/Computed Tomography was performed longitudinally on day 2, 7, 14 and 28 post-MI. On day 28, cardiac function was assessed by ultrasound. Naïve and sham rat controls were compared to the MI cohort. A separate cohort of rats were produced for histological validation and proteomic analysis. Results [ 18 F]LW223 standard uptake value corrected for myocardial blood flow ( SUV MBF ) was highest within the MI cohort and localised to the infarct. This peaked at day 2 and remained elevated versus naïve and sham controls out to day 28. These patterns were validated by histology, revealing that the majority of TSPO expressing cells within the infarct at day 2 were also CD68 + (55.2%). Proteomics confirmed upregulation of several proinflammatory processes at day 2, and a commonality in upregulated inflammatory response proteins at both day 2 and day 28, indicting ongoing inflammation. Infarct [ 18 F]LW223 uptake at day 2 correlated with infarct size ( p = 0.0016, R 2 = 0.73) and cardiac dysfunction at day 28 ( p = 0.0020, R 2 = 0.82). Conclusion [ 18 F]LW223 identifies a persistent and predominantly macrophage-driven inflammatory response with early [ 18 F]LW223 infarct binding associated with later cardiac dysfunction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| 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".