Diagnostic Accuracy of Imaging Modalities in the Evaluation of Vascular Invasion in Pancreatic Adenocarcinoma: A Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The extent of vascular invasion is a key factor determining the resectability of non-metastatic pancreatic adenocarcinoma. The purpose of this study is to determine the diagnostic accuracy of computed tomography (CT), endoscopic ultrasound (EUS), and magnetic resonance imaging (MRI) in the pre-operative evaluation of vascular invasion in pancreatic adenocarcinoma, with surgery as the reference standard. METHODS: A search of the MEDLINE database for relevant articles in the English language published between January 2000 and February 2009 was performed. From each study, 2 × 2 tables were obtained, and pooled sensitivity, specificity, positive likelihood ratios, negative likelihood ratios and diagnostic odds ratios were calculated for each modality, along with a summary receiver operating characteristics (SROC) curve. RESULTS: 16 studies with a total of 797 patients who had surgical assessment of vascular invasion were included in the analysis. Several studies evaluated more than one imaging modality, allowing 24 datasets to be obtained in total. Sensitivity was highest for CT (0.73, 95% CI 0.67 - 0.79), followed by EUS (0.66, 95% CI 0.56 - 0.75) and MRI (0.63, 95% CI 0.48 - 0.77). The specificity for all three imaging modalities was comparable. The diagnostic odds ratios for CT, EUS and MRI were 45.9 (95% CI 18.0 - 117.4), 23.0 (95%CI 9.4 - 56.6), 23.9 (95% CI 5.4 - 105.1) respectively. CONCLUSION: CT was more accurate than EUS and MRI in the evaluation of vascular invasion in pancreatic adenocarcinoma and should be the first line investigation in pre-operative staging.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".