Cancer of the Pancreas: The Best Image for Early Detection – CT, MRI, PET or US?
Bibliographic record
Abstract
Pancreatic cancer has a poor prognosis, and the best chance for survival is to diagnose the tumour at an early stage. Abdominal ultrasound, computed tomography, magnetic resonance imaging and endoscopic retrograde cholangiopancreatography are the most commonly used radiological techniques for imaging the pancreas. The diagnostic evaluation should be tailored to the individual patient. Dual-phase helical computed tomography and magnetic resonance imaging have similar accuracies for detecting and staging pancreatic adenocarcinoma. Sonography results are highly dependent on the skill and persistence of the operator. No radiological examination is very sensitive at visualizing small metastases in the lymph nodes and peritoneum, or on the surface of the liver. Thus, it is difficult to establish with certainty whether a tumour is resectable. Another major challenge is to differentiate cancer from an inflammatory mass in chronic pancreatitis. Functional imaging (using positron emission tomography with fluorodeoxyglucose) may be helpful, especially if the images are fused with those of computed tomography or magnetic resonance imaging. The diagnostic accuracies, applications and limitations of the various modalities are discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".