Near-Infrared Fluorescent Cholangiography
Bibliographic record
Abstract
Background: Intraoperative cholangiography facilitates identification of biliary anatomy and may help prevent main duct injury during laparoscopic cholecystectomy. Despite this potential benefit, the added operative time and the need to inject contrast directly into the biliary system have prevented it from becoming routine.1–3 Fluorescent cholangiography using an intravenous fluorophore and near-infrared (NIR) imaging provides similar anatomical detail without the drawbacks of radiographic cholangiography. Methods: The Pinpoint system (Novadaq, Canada) is a laparoscopic NIR imaging system that takes advantage of the biochemical and fluorescent properties of indocyanine green (ICG). After being injected intravenously, ICG is rapidly taken up by the liver and excreted in the bile. ICG fluoresces at a peak wavelength of ∼830 nm when exposed to NIR light and can then be visualized in the biliary tree. The pinpoint was used in 19 cases as a part of a randomized controlled study. In all cases, 1 mL (2.5 mg reconstituted) of ICG was injected via a peripheral IV catheter as a bolus just before induction of anesthesia. In contrast to other NIR imaging systems that can operate only in white light or excitation modes,4,5 the Pinpoint system mates these two imaging modalities to produce a continuous fluorescent cholangiographic overlay superimposed on the white-light image. This video is illustrative of the images rendered by the Pinpoint system. Results: The Pinpoint system consistently produced high-definition cholangiographic images of the biliary system. Conclusion: The Pinpoint system provides real-time contextualized cholangiographic images without being obtrusive or interrupting the operative flow. It may be especially helpful for surgeons early in the learning curve to help in identifying anatomy. Drs. Sherwinter, Gallagher, and Donkar have no disclosures, financial or otherwise, related to this article. Runtime of video: 56 secs
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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 | 0.000 | 0.000 |
| 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 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".