Optimizing Laparoscopic Cholecystectomy in Aberrant Biliary Anatomy: A Case of Cystic Duct Insertion Into the Right Posterior Hepatic Duct
Bibliographic record
Abstract
Anatomic variations of the biliary tree, particularly those involving the cystic duct, pose significant challenges during laparoscopic cholecystectomy and can lead to inadvertent bile duct injury (BDI) if unrecognized. We report a rare variant in which the cystic duct inserts into the right posterior hepatic duct, which itself drains directly into the common bile duct - an aberrant configuration not frequently described in the literature. A 65-year-old man with grade I acute cholecystitis underwent preoperative imaging with computed tomography and magnetic resonance cholangiopancreatography, revealing the unusual biliary anatomy. A laparoscopic cholecystectomy was performed using the critical view of safety (CVS) approach, followed by intraoperative cholangiography (IOC) via gallbladder puncture to delineate the anatomy, ensuring accurate identification of the cystic duct and artery. The procedure was completed safely without complications. This case highlights the importance of preoperative imaging, adherence to CVS, and IOC in achieving safe outcomes in the setting of complex biliary anatomy. Despite increasing interest in indocyanine green (ICG) fluorescence cholangiography, its availability remains limited in some centers; thus, conventional techniques remain valuable. We advocate for a multimodal approach to mitigate the risk of BDI in patients with atypical biliary configurations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".