Intraoperative ultrasonography of the biliary tract using saline as a contrast agent: a fast and accurate technique to identify complex biliary anatomy
Bibliographic record
Abstract
BACKGROUND: Intraoperative assessment of biliary tract anatomy is relevant for a number of benign and malignant hepatobiliary diseases. During biliary reconstruction, drainage of all relevant bile ducts is imperative to prevent atrophy of undrained segment, cholangitis and secondary biliary cirrhosis. Intraoperative cholangiography, though widely used for intraoperative imaging of the biliary tract, involves heavy equipment use, radiation risk and has a limited role in the evaluation of isolated segmental bile ducts. METHODS: We evaluated the use of a novel technique of intraoperative ultrasonography of the biliary tract using normal saline as a contrast agent. It involves injecting saline in any part of the biliary system while performing real-time intraoperative 2-dimensional ultrasonography. RESULTS: This procedure was carried out in intraoperative situations to delineate complex biliary anatomy involving segmental bile ducts. Excellent image quality was obtained in the form of opacification and demarcation of the liver segment to which the duct belongs. The flow of saline microbubbles was clearly visible on real-time ultrasound images, leading to accurate identification of the duct. CONCLUSION: Intraoperative ultrasonography with saline as a contrast agent can accurately identify small isolated segmental bile ducts and help in surgery of the biliary tract. It is a simple and inexpensive technique that can be performed with minimal resources.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".