The aim of this study was to investigate the role of tumor-associated neutrophils (TANs) in the metastasis of pancreatic ductal adenocarcinoma (PDAC), to explore the regulation of TANs, and to determine the mechanisms governing the metastasis of PDAC. The correlation between neutrophils and the patient’s clinical pathological data was first evaluated. Then, the effects of neutrophils on the invasion of PDAC were analyzed using a combination of conditioned media, direct and indirect coculture of human peripheral blood neutrophils, and PDAC cell lines (Panc-1, MiaPaCa-2 and AsPC-1). The cytokines secreted by neutrophils were detected through ELISA. TAN density was significantly correlated with poor metastasis-free survival (P < .05). Through coculture, it was found that the effect of neutrophils on pancreatic cancer cells was dependent on concentration, and a high concentration of neutrophils showed a lethal effect, while a low concentration of neutrophils primarily promoted the migration ability of cancer cells. The results of the wound-healing assay, the Transwell invasion assay, and laser confocal microscopy confirmed the promoting effect and indicated that the effect of neutrophils toward cancer cells may function indirectly by releasing a series of cytokines. The results of ELISA show that this effect may be achieved through the secretion of a large amount of TNF-α and TGF-β1 by neutrophils. Our study indicated that neutrophils may increase the metastasis of PDAC by releasing a series of cell cytokines, such as TNF-α and TGF-β1.

To investigate the features and prognosis of the elderly patients with pancreatic neuroendocrine tumor (pNET). The patients diagnosed with pNETs between 2004 and 2014 were identified from the Surveillance Epidemiology and End Results database. The ethical approval was waived because the present study was analysis of the data from Surveillance Epidemiology and End Results database. A total of 4608 patients with “one primary only” histologically pNETs were confirmed and 653 were older than 75 years. Cancer-specific survival (CSS) and overall survival (OS) were examined. The elderly patients (≥75 years) have disadvantage in CSS and OS compared with younger cohort. Multivariate logistic regression revealed that the elderly patients have increased poorly differentiated composition, and decreased proportion of Black patients, receipt of surgery, married status, and number of removed lymph node. Multivariate Cox regression analysis demonstrated worse differentiation. Patients of T3–4 and M1 stage were associated with poor CSS, while patients of being female, tumor locating at pancreatic body/tail, receipt of surgery, and being married were associated with better CSS in the elderly patients. Meanwhile, patients with higher histological grade and M1 stage have poor OS, while patients with the characteristics of female, being married, tumor location at pancreatic body/tail and tumor surgery have better OS. Distant metastatic elderly patients underwent primary site surgery had better CSS and OS than the patients without surgery. The elderly patients have increased possibility of poorly differentiated tumor, and decreased proportion of Black patients, surgery of primary site, number of removed lymph node and married status. Worse differentiation and tumor metastasis were independent risk factors for both CSS and OS, while primary tumor located in body/tail of pancreas, female patients, surgery of tumor primary site, and being married were protective factors.

Background Preoperative recognition of irreversible bowel necrosis is important, as it provides valuable guidance for surgical strategy selection but also may inform perioperative risk assessment and communication. Few studies have focused on the association between CT signs and bowel necrosis. Purpose To assess the diagnostic accuracy of CT signs to predict bowel necrosis in patients with closed-loop small bowel obstruction (CL-SBO). Materials and Methods This retrospective single-center study included patients who were surgically confirmed to have CL-SBO caused by adhesion or internal hernia between January 2016 and May 2022. Necrosis was determined based on surgical exploration and postoperative pathologic examination. Two radiologists independently reviewed CT signs by both subjective visual assessment and objective measurement. Disagreements were resolved in consensus with a third gastrointestinal radiologist. Univariable and multivariable analyses were used to assess the association between CT signs and bowel necrosis, and Cohen κ was used to assess interobserver agreement. Sensitivity and specificity were calculated for each CT sign. Results This study included 145 patients: 61 (42.1%) in the necrotic group (median age, 62 years [IQR, 51-71.5 years]; 37 [60.7%] women) and 84 (57.9%) in the nonnecrotic group (median age, 61.5 years [IQR, 51-68.8 years]; 51 [60.7%] women). Univariable analysis and multivariable analysis showed that increased attenuation of intestinal contents and increased attenuation of intestinal wall were independent predictors for bowel necrosis (odds ratio = 45.3 and 15.1; P = .001 and P < .001, respectively). Increased attenuation of intestinal contents and increased attenuation of intestinal wall had similar sensitivity (64% and 67%, respectively) and specificity (99% and 92%, respectively) for predicting bowel necrosis. However, interobserver agreement was better for assessing the contents than the wall (κ = 0.84 and 0.59, respectively). Conclusion Increased attenuation of intestinal contents was a highly specific CT sign with good reproducibility to predict bowel necrosis in CL-SBO. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Taourel and Zins in this issue.

Background: Diagnosing and managing follicular thyroid neoplasms (FTNs) remains a significant challenge, as the malignancy risk cannot be determined until after diagnostic surgery. Objective: We aimed to use interpretable machine learning to predict the malignancy risk of FTNs preoperatively in a real-world setting. Methods: We conducted a retrospective cohort study at the Peking University Third Hospital in Beijing, China. Patients with postoperative pathological diagnoses of follicular thyroid adenoma (FTA) or follicular thyroid carcinoma (FTC) were included, excluding those without preoperative thyroid ultrasonography. We used 22 predictors involving demographic characteristics, thyroid sonography, and hormones to train 5 machine learning models: logistic regression, least absolute shrinkage and selection operator regression, random forest, extreme gradient boosting, and support vector machine. The optimal model was selected based on discrimination, calibration, interpretability, and parsimony. To address the highly imbalanced data (FTA:FTC ratio>5:1), model discrimination was assessed using both the area under the receiver operating characteristic curve and the area under the precision-recall curve (AUPRC). To interpret the model, we used Shapley Additive Explanations values and partial dependence and individual conditional expectation plots. Additionally, a systematic review was performed to synthesize existing evidence and validate the discrimination ability of the previously developed Thyroid Imaging Reporting and Data System for Follicular Neoplasm scoring criteria to differentiate between benign and malignant FTNs using our data. Results: The cohort included 1539 patients (mean age 47.98, SD 14.15 years; female: n=1126, 73.16%) with 1672 FTN tumors (FTA: n=1414; FTC: n=258; FTA:FTC ratio=5.5). The random forest model emerged as optimal, identifying mean thyroid-stimulating hormone (TSH) score, mean tumor diameter, mean TSH, TSH instability, and TSH measurement levels as the top 5 predictors in discriminating FTA from FTC, with the area under the receiver operating characteristic curve of 0.79 (95% CI 0.77‐0.81) and AUPRC of 0.40 (95% CI 0.37-0.44). Malignancy risk increased nonlinearly with larger tumor diameters and higher TSH instability but decreased nonlinearly with higher mean TSH scores or mean TSH levels. FTCs with small sizes (mean diameter 2.88, SD 1.38 cm) were more likely to be misclassified as FTAs compared to larger ones (mean diameter 3.71, SD 1.36 cm). The systematic review of the 7 included studies revealed that (1) the FTA:FTC ratio varied from 0.6 to 4.0, lower than the natural distribution of 5.0; (2) no studies assessed prediction performance using AUPRC in unbalanced datasets; and (3) external validations of Thyroid Imaging Reporting and Data System for Follicular Neoplasm scoring criteria underperformed relative to the original study. Conclusions: Tumor size and TSH measurements were important in screening FTN malignancy risk preoperatively, but accurately predicting the risk of small-sized FTNs remains challenging. Future research should address the limitations posed by the extreme imbalance in FTA and FTC distributions in real-world data.