A243 A RETROSPECTIVE REVIEW OF THE RADIOGRAPHIC DIAGNOSIS AND SURGICAL RESECTION RATES OF PANCREATIC SEROUS CYSTS
Bibliographic record
Abstract
Abstract Background Pancreatic cystic lesions are increasingly identified in persons undergoing abdominal imaging. Serous cystic neoplasms (SCNs) have a very low risk of malignant transformation. Resection of SCNs is not recommended in the absence of related symptoms. The accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) to identify SCNs is not known and may impact clinical care. Aims To evaluate the accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) for the diagnosis of SCN. To see how this can impact the decision to resect suspected SCNs. Methods Retrospective cohort study of patients from the University Health Network with suspected SCNs from 2017–2020 who underwent either a CT or MRI of the abdomen. Reports noting pancreatic cystic lesions were identified and reviewed. Only cases with suspected SCNs were included. Clinical (age, sex, symptoms, treatment) and radiographic (type of imaging, reported cyst characteristics) data was collected. Pathology was reviewed for all cases where the cysts was biopsied or resected during follow-up. The gold standard for the diagnosis for SCN was pathology of resected specimen or EUS-guided biopsy cytopathology showing no evidence of a mucinous lesion, CEA level below 10ug per L and amylase level below 50 U/L. Results 163 patients were included in the study. 99 (61%) were female and 98 (60%) underwent CT scan. EUS-guided biopsy was performed in 24 (15%) of patients and 8 (5%) had surgical resection. Multidisciplinary review was performed in 6 of the 8 cases that went to surgery. Of the resected specimens, 5 (63%) were SCN, 1 was a mucinous cystic lesion, 1 was a neuroendocrine tumor and 1 was a carcinoma. Two patients underwent EUS evaluation prior to surgical resection. In one case SCN was resected when EUS reported an undetermined cyst type. Reasons for surgical resection were: the diagnosis of serous cyst was not definitive (n=5), symptoms (n=2), and high-risk mucinous cystic neoplasm identified on EUS (n=1). Of 30 patients with pathology available, 15 (50%) were confirmed to have a SCN. CT and MRI had a sensitivity, specificity, positive predictive value and negative predictive value of 93%, 25%, 52% and 80%, respectively. Conclusions Surgical resection for SCN lesions is driven by diagnostic uncertainty after cross-sectional imaging. Multidisciplinary review and EUS evaluation may improve diagnostic accuracy and should be considered prior to surgical resection of possible SCN lesions. Funding Agencies None
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".