Hybrid SPECT/cardiac‐gated first‐pass perfusion CT: locating transplanted cells relative to infarcted myocardial targets
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: A challenge with cardiac cell therapy is determining the location of cells relative to infarct tissue. As cells are viable following ¹¹¹In-labeling, and first-pass CT imaging can identify regions of myocardial infarction, we evaluated the feasibility of a SPECT/CT system to localize cells relative to infarcted myocardium in a canine model. METHODS: Ten canines underwent surgical ligation of the left-anterior-descending artery and endothelial progenitor cells labeled with ¹¹¹In-tropolone were transplanted endocardially or epicardially. SPECT/CT was performed on day of transplantation, 4 and 10 days post-transplantation. For each imaging session first-pass perfusion CT was performed to delineate the area of reduced perfusion. SPECT and first-pass CT images were fused and evaluated. Contrast-to-noise ratios (CNR) were calculated for ¹¹¹In-SPECT images to evaluate cell detection. RESULTS: The zone of reduced perfusion was well delineated on first-pass perfusion CT in all canines. The ¹¹¹In signal was visualized within this zone in all cases. Analysis of the CNRs suggests that cells may be followed for 11 effective half-lives using the images from first-pass perfusion CT to provide the anatomic landmarks. CONCLUSION: In the setting of an acute myocardial infarction SPECT/[first-pass perfusion CT] is an effective hybrid platform for the localization of cells in relation to the area of reduced blood flow.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 0.001 |
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 it