Detectability of Choledocholithiasis on CT: The Effect of Positive Intraduodenal Enteric Contrast on Portovenous Contrast-enhanced Studies
Bibliographic record
Abstract
BACKGROUND/AIM: To retrospectively assess the accuracy of intravenous (IV) contrast-enhanced multidetector CT (MDCT) in choledocholithiasis detectability, in the presence and absence of positive intraduodenal contrast. PATIENTS AND METHODS: Over a 3-year period, patients in whom endoscopic retrograde cholangiopancreatography (ERCP) was performed within a week from a portovenous (PV)-enhanced abdominal CT were identified. The final cohort consisted of 48 CT studies in which the entire common bile duct (CBD) length was visualized (19 males, 29 females; mean age, 68 years). We identified two groups according to the absence (n = 31) or presence (n = 17) of positive intraduodenal contrast. CT section thickness ranged from 1.25 to 5 mm. Two radiologists, blinded to clinical information and ERCP results, independently evaluated the CT images. Direct CBD stone visualization was assessed according to previously predefined criteria, correlating with original electronic CT reports and using ERCP findings as the reference standard. A third reader retrospectively reviewed all discordant results. The diagnostic performances of both observers and interobserver agreement were calculated for both groups. RESULTS: 77%-88% sensitivity, 50%-71% specificity, and 71%-74% accuracy were obtained in the group without positive intraduodenal contrast, versus 50%-80% sensitivity, 57%-71% specificity, and 59%-71% accuracy in the group with positive intraduodenal contrast. With the exception of the positive predictive value (PPV), all diagnostic performance parameters decreased in the positive intraduodenal contrast group, mostly affecting the negative predictive value (NPV) (71%-78% vs 50%-67%). CONCLUSION: PV-enhanced MDCT has moderate diagnostic performance in choledocholithiasis detection. A trend of decreasing accuracy was noted in the presence of positive intraduodenal contrast.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".