Optimal timing of preoperative indocyanine green administration for fluorescent cholangiography during laparoscopic cholecystectomy using the PINPOINT® Endoscopic Fluorescence Imaging System
Bibliographic record
Abstract
INTRODUCTION: The PINPOINT® Endoscopic Fluorescence Imaging System (Novadaq, Mississauga, Canada) allows surgeons to visualize the bile ducts during laparoscopic cholecystectomy. Surgeons can continue operation while confirming the bile ducts' fluorescence with a bright-field/color image. However, strong fluorescence of the liver can interfere with the surgery. Here, we investigated the optimal timing of indocyanine green administration to allow fluorescent cholangiography to be performed without interference from the liver fluorescence. METHODS: A total of 72 patients who underwent laparoscopic cholecystectomy were included in this study. The timing of indocyanine green administration was set immediately before surgery and at 3, 6, 9, 12, 15, 18, and 24 h before surgery. The luminance intensity ratios of gallbladder/liver, cystic duct/liver, and common bile duct/liver were measured using the ImageJ software (National Institutes of Health, Bethesda, USA). Visibility of the gallbladder and bile ducts was classified into three categories (grades A, B, and C) based on the degree of visibility in contrast to the liver. RESULTS: The luminance intensity ratio for the gallbladder/liver, cystic duct/liver, and common bile duct/liver was ≥1 in the 15-, 18-, and 24-h groups. The proportion of cases in which evaluators classified the visibility of the gallbladder and bile ducts as grade A (best visibility) reached a peak in the 15-h group and decreased thereafter. CONCLUSIONS: In the present study, the optimal timing of indocyanine green administration for fluorescent cholangiography during laparoscopic cholecystectomy using the PINPOINT Endoscopic Fluorescence Imaging System was 15 h before surgery.
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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 | 0.002 |
| 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 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".