Atypical cells in fine needle aspiration biopsies of pancreas: Causes, work-up, and recommendations for management

Preoperative prediction of invasive behavior of pancreatic solid pseudopapillary neoplasm by MRI-based multiparametric radiomics models

OBJECTIVE

A log-combined model was developed to predict the invasive behavior of pancreatic solid pseudopapillary neoplasm (pSPN) based on clinical and radiomic features extracted from multiparametric magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A total of 111 patients with pathologically confirmed pSPN who underwent preoperative plain and contrast-enhanced MRI were included, and divided into an invasive group (n = 34) and non-invasive group (n = 77). Clinical features and laboratory data related to pSPN invasive behavior were analyzed. Regions of interest were delineated based on T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1WI (CE-T1WI) to extract radiomic features. Correlation analysis was performed for these features, followed by L1_based feature selection (C = 0.15). A logistic regression algorithm was used to construct models based on each of the four sequences and a log-combined model was used to integrate the sequences. A receiver operating characteristic (ROC) curve was plotted to evaluate the model performance, and the Brier score was used to assess the overall accuracy of the model predictions.

RESULTS

The area under the ROC curve was 0.68, 0.73, 0.71, and 0.49 for Log-T1WI, Log-T2WI, Log-DWI, and Log-CE models, respectively, and 0.81 for the log-combined model. The accuracy, precision, sensitivity, and specificity of the log-combined model were 0.77, 0.88, 0.75, and 0.78, respectively. The best performance was obtained with the log-combined model with a Brier score of 0.18. Tumor location was identified as a significant clinical feature in comparison between the two groups (p < 0.05), and invasive pSPN was more frequent in the tail of the pancreas.

CONCLUSION

The log-combined model based on multiparametric MRI and clinical features can be used as a non-invasive diagnostic tool for preoperative prediction of pSPN invasive behavior and to facilitate the development of individualized treatment strategies and monitoring management plans.

Diagnostic Performance of Pancreatic Cytology with the Papanicolaou Society of Cytopathology System: A Systematic Review, before Shifting into the Upcoming WHO International System

The Papanicolaou Society of Cytopathology (PSC) reporting system classifies pancreatobiliary samples into six categories (I–VI), providing guidance for personalized management. As the World Health Organization (WHO) has been preparing an updated reporting system for pancreatobiliary cytopathology, this systematic review aimed to evaluate the risk of malignancy (ROM) of each PSC category, also the sensitivity and specificity of pancreatic FNA cytology using the current PSC system. Five databases were investigated with a predefined search algorithm. Inclusion and exclusion criteria were applied to select the eligible studies for subsequent data extraction. A study quality assessment was also performed. Eight studies were included in the qualitative analysis. The ROM of the PSC categories I, II, III, IV, V, VI were in the ranges of 8–50%, 0–40%, 28–100%, 0–31%, 82–100%, and 97–100%, respectively. Notably, the ROM IVB (“neoplastic—benign”) subcategory showed a 0% ROM. Four of the included studies reported separately the ROMs for the IVO subcategory (“neoplastic—other”; its overall ROM ranged from 0 to 34%) with low (LGA) and high-grade atypia (HGA). ROM for LGA ranged from 4.3 to 19%, whereas ROM for HGA from 64 to 95.2%. When the subcategory IVO with HGA was considered as cytologically positive, together with the categories V and VI, there was a higher sensitivity of pancreatic cytology, at minimal expense of the specificity. Evidence suggests the proposed WHO international system changes—shifting the IVB entities into the “benign/negative for malignancy” category and establishing two new categories, the “pancreatic neoplasm, low-risk/grade” and “pancreatic neoplasm, high-risk/grade”—could stratify pancreatic neoplasms more effectively than the current PSC system.