Pancreatic Cystic Lesions on <scp>MRI</scp>: What Is The Likelihood of a Present or Future Diagnosis of Pancreatic Carcinoma?
Bibliographic record
Abstract
BACKGROUND: Pancreatic cystic lesions (PCLs) are followed for years due to older and likely biased works demonstrating a strong association with pancreatic carcinoma; more recent data are needed clarifying this relationship. PURPOSE: To determine the association between PCLs on MRI and a synchronous or future diagnosis of pancreatic carcinoma. STUDY TYPE: Single-center retrospective cohort. POPULATION: A total of 192 patients (111 female, 58%) with median age 66 years (range 26-87 years) with PCLs on abdominal MRI from 2011 to 2016. FIELD STRENGTH/SEQUENCES: WI. ASSESSMENT: Each PCL was reviewed independently by 2 of 10 fellowship-trained abdominal radiologists. Fukuoka guideline worrisome features and high-risk stigmata were evaluated. Follow-up imaging and clinical notes were reviewed within a system that captures pancreatic carcinoma for the region, for a median follow-up of 67 months (interquartile range: 43-88 months). STATISTICAL TESTS: Pancreatic carcinoma prevalence and incidence rate for future carcinoma with 95% confidence intervals (95% CI). Fisher exact test, logistic regression with odds ratios (OR) and the Wilcoxon rank-sum test were used to assess PCL morphologic features with the Kolmogorov-Smirnov test used to assess for normality. P < 0.05 defined statistical significance. RESULTS: The prevalence of pancreatic carcinoma on initial MRI showing a PCL was 2.4% (95% CI: 0.9%, 5.2%). Thickened/enhancing cyst wall was associated with pancreatic carcinoma, OR 52 (95% CI: 4.5, 1203). Of 189 patients with a PCL but without pancreatic carcinoma at the time of initial MRI, one developed high-grade dysplasia and none developed invasive carcinoma for an incidence rate of 0.97 (95% CI: 0.02, 5.43) and 0 (95% CI: 0, 3.59) cases per 1000 person-years, respectively. DATA CONCLUSION: A low percentage of patients with a PCL on MRI had a pancreatic carcinoma at the time of initial evaluation and none developed carcinoma over a median 67 months of follow-up. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: 5.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".