[Preoperative diagnostics of pancreatic neoplasms]

[Challenges of cytopathological pancreas diagnostics]

The cytologic diagnostics of solid and cystic pancreatic lesions with endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is an integral part of the clinical workup and the decision of a surgical versus a conservative approach. Cystic lesions are increasingly being diagnosed due to improved imaging and represent numerous neoplastic as well as non-neoplastic epithelial and non-epithelial entities, which differ in biological behavior and prognosis. In particular, the differentiation of mucinous and non-mucinous cysts is significant for further clinical management. Regressive cellular changes, gastrointestinal contaminants, and overlapping morphologic changes of reactively altered ductal epithelial cells and cells of well-differentiated neoplasms and preneoplasms are special challenges of cytological diagnostics. For a uniform cytological classification of findings, an internationally developed seven-level classification system has been published and co-published by the World Health Organization (WHO). This classification system takes into account both morphological findings and further procedures on cytological material such as next-generation sequencing and immunocytochemistry and is based on the WHO classification for pancreatic tumors. Against this background, important cytologic diagnostic criteria of various solid and cystic lesions relevant in clinical practice are presented in this article, considering diagnostic possibilities and pitfalls as well as differential diagnoses.

Prediction of postoperative liver metastasis in pancreatic ductal adenocarcinoma based on multiparametric magnetic resonance radiomics combined with serological markers: a cohort study of machine learning

OBJECTIVE

To construct and validate a multi-dimensional model based on multiple machine leaning algorithms to predict PCLM using multi-parameter magnetic resonance (MRI) sequences with clinical and imaging parameters.

METHODS

A total of 148 PDAC retrospectively examined patients were classified as metastatic or non-metastatic based on results at 3 months after surgery. The radiomics features of the primary tumor were extracted from T2WI images, followed by dimension reduction. Then, multiple machine learning methods were used to construct models. Independent predictors were also screened using multifactor logistic regression and a nomogram was constructed in combination with the radiomics model. Area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the accuracy and reliability of the nomogram.

RESULTS

The diagnostic efficacy of the radiomics model in the training and test set was 0.822 and 0.803, sensitivity was 0.742 and 0.692, and specificity was 0.792 and 0.875, respectively. The diagnostic efficacy of the nomogram in the training and test set was 0.866 and 0.832.

CONCLUSION

A radiomics nomogram based on machine learning improved the accuracy of predicting PCLM and may be useful for early preoperative diagnosis.

[Pancreatic cystic space-occupying lesions-Diagnostics, treatment and follow-up care : Current recommendations taking the current German S3 guidelines on pancreatic cancer into account]

Due to their increased detection pancreatic cystic space-occupying lesions are becoming increasingly relevant in the clinical routine and represent a morphologically and biologically heterogeneous and thus clinically demanding as well as potentially (pre)malignant entity. As a result, recommendations for the diagnostics and treatment of pancreatic cystic tumors have now been incorporated into the current German S3 guidelines on pancreatic cancer. The diagnostics of pancreatic cystic space-occupying lesions are based on the following three elements: collection of relevant clinical information, performance of high-resolution imaging procedures and if diagnostic uncertainty persists, puncture diagnostics. Differentiated diagnostics are of essential importance as these represent the basis for an adequate treatment decision. Pancreatic cystic lesions with a relevant risk of malignant transformation, e.g., main duct intraductal papillary mucinous neoplasms (IPMN), followed by mucinous cystic neoplasms (MCN), solid pseudopapillary neoplasms (SPN) and generally pancreatic cystic lesions with risk factors independent of the entity, should be resected, whereas a differentiated and individualized approach is necessary, especially for branch-duct IPMNs. The serous cystic neoplasms (SCN) have no malignant potential and do not require any treatment if they are asymptomatic. Important principles in surgery of pancreatic cancer, such as adequate surgical resection taking oncological standards into account and standardized appropriate histopathological processing of the specimens as well as intraoperative frozen section analysis also play an important role in pancreatic cystic space-occupying lesions. An annual follow-up seems to be meaningful, especially for IPMNs.