A243 A RETROSPECTIVE REVIEW OF THE RADIOGRAPHIC DIAGNOSIS AND SURGICAL RESECTION RATES OF PANCREATIC SEROUS CYSTS
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».