A new and simplified method for coronary and graft imaging during CABG.
Bibliographic record
Abstract
BACKGROUND: Improvements in percutaneous catheter interventions and new technical demands in the practice of coronary surgery have increased the need for an accurate and easy-to-use imaging modality for validating the quality of bypass grafts in the operating room. This report examines the initial clinical use of fluorescent cardiac imaging, a technology that uses indocyanine green (ICG) with a portable imaging device to visualize coronary anatomy and grafts intraoperatively. METHODS: The modality was evaluated at two institutions in 20 patients undergoing non-emergent CABG or MIDCAB with respect to safety, feasibility of use, and image quality. Images were generated and acquired with a portable laser diode/infrared camera device after injection of 0.5 ml of ICG (0.5-5.0 mg/ml) either intravenously, via the antegrade cardioplegia cannula, or via the cardiopulmonary bypass circuit. RESULTS: There were no ICG- or imaging device-related complications. The technology was easy-to-use during conventional CABG as well as MIDCAB and adequately demonstrated coronary anatomy, filling of the grafts, and graft patency in all but two patients. In one patient, the use of the modality resulted in the intraoperative recognition and revision of a non-functioning graft. CONCLUSION: This technology is user-friendly in the operating room, appears to be safe, provides good-quality images of coronary anatomy and grafts, and holds promise as an intraoperative graft validation tool for conventional and minimally invasive CABG.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".