Comparison of CT Duodeno-Cholangiopancreatography to ERCP for Assessing Biliary Obstruction
Bibliographic record
Abstract
The authors have developed a CT protocol, CT duodeno-cholangiopancreatography (CDCP), which is performed during a single contrast-enhanced phase, proceeding cranially, allowing enhancement of the pancreas during its parenchymal phase followed by enhancement of the liver during its portal-venous phase. This retrospective pilot study evaluates CDCP compared with endoscopic retrograde cholangiopancreatography (ERCP) as a diagnostic tool for assessing the cause and level of biliary obstruction. Forty-one patients with jaundice underwent CDCP and ERCP between October 2002 and May 2004. Pathologic confirmation was obtained in 31 of the 41 (76%) patients. The sensitivity, specificity, and kappa values of CDCP and ERCP compared with pathology were calculated for tumors and stones. Pathology-proven cases included 7 cases of stones, 23 tumors, and 1 other cause of obstruction. The overall level of agreement of diagnoses between CDCP and pathology was 29 of 31 (93.5%); that between CDCP and ERCP was 36 of 41 (88%). Comparing CDCP to pathology for tumors, the sensitivity was 100%, the specificity was 89%, and the kappa was 0.92 (95% CI 0.76-1.0). For stone detection, CDCP had a sensitivity of 86%, a specificity of 100%, and a kappa value of 0.90 (95% CI 0.72-1.0). For level of obstruction of the common bile duct, comparing CDCP to ERCP, observations agreed in 31 of the 36 (86%) cases; for the pancreatic duct, observations agreed in 24 of the 25 (96%) cases. CDCP is a noninvasive diagnostic tool that can be used to assess the cause and level of obstruction. A blinded prospective study would be valuable to further assess the merits of CDCP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".