Pancreatic Adenocarcinoma: Diagnostic Errors, Contributing Factors and Solutions

nnU-Net-Based Pancreas Segmentation and Volume Measurement on CT Imaging in Patients with Pancreatic Cancer

RATIONALE AND OBJECTIVES

To develop and validate a deep learning (DL)-based method for pancreas segmentation on CT and automatic measurement of pancreatic volume in pancreatic cancer.

MATERIALS AND METHODS

This retrospective study used 3D nnU-net architecture for fully automated pancreatic segmentation in patients with pancreatic cancer. The study used 851 portal venous phase CT images (499 pancreatic cancer and 352 normal pancreas). This dataset was divided into training (n = 506), internal validation (n = 126), and external test set (n = 219). For the external test set, the pancreas was manually segmented by two abdominal radiologists (R1 and R2) to obtain the ground truth. In addition, the consensus segmentation was obtained using Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm. Segmentation performance was assessed using the Dice similarity coefficient (DSC). Next, the pancreatic volumes determined by automatic segmentation were compared to those determined by manual segmentation by two radiologists.

RESULTS

The DL-based model for pancreatic segmentation showed a mean DSC of 0.764 in the internal validation dataset and DSC of 0.807, 0.805, and 0.803 using R1, R2, and STAPLE as references in the external test dataset. The pancreas parenchymal volume measured by automatic and manual segmentations were similar (DL-based model: 65.5 ± 19.3 cm3 and STAPLE: 65.1 ± 21.4 cm3; p = 0.486). The pancreatic parenchymal volume difference between the DL-based model predictions and the manual segmentation by STAPLE was 0.5 cm3, with correlation coefficients of 0.88.

CONCLUSION

The DL-based model efficiently generates automatic segmentation of the pancreas and measures the pancreatic volume in patients with pancreatic cancer.

Hypoxia-Induced miR-210 Promotes Endothelial Cell Permeability and Angiogenesis via Exosomes in Pancreatic Ductal Adenocarcinoma

BACKGROUND

Exosomes have been proven to play important diagnostic, regulatory, or communication roles in tumorigenesis, tumor progression, or metastasis; in recent studies, lots of molecules, including miRNAs, were found to be aberrantly expressed in tumor exosomes and were correlated with tumor development. However, studies about the expression, relationship, or control mechanisms of miRNAs in exosomes in pancreatic ductal adenocarcinoma (PDAC) are scarce and urgently needed. The aim of this article was to identify and investigate abnormally expressed miRNAs in PDAC exosomes in vivo and in vitro.

METHODS

Microarray studies were used to detect aberrantly expressed miRNAs in PDAC exosomes, and miR-210 expression in cells or exosomes was further analyzed by qRT-PCR. Bioinformatics analyses, dual-luciferase assays, WB, and other assays were utilized to explore the miRNA molecular mechanisms. The living cell coculture model and immunofluorescence analysis were employed to image the communication between PDAC cells and endothelial cells. Other biological experiments in the study include a real-time intravital imaging system, EdU, transwell, xenograft models, and so on.

RESULTS

miR-210 is significantly expressed in PDAC exosomes and malignant cells. High miR-210 significantly facilitated tumor angiogenesis, cell invasion, and proliferation in PDAC cells. Further mechanistic detection revealed that miR-210 negatively regulated EFNA3 expression and participated in the PI3K/AKT/VEGFA or Wnt/Β-catenin/RHOA pathways, thus promoting tumor angiogenesis and cellular permeability. PDAC cells promote endothelial angiogenesis or permeability via miR-210 transmission by tumor exosomes. Exosomal miR-210 promotes PDAC progression in vivo. Further detection of PDAC plasma exosomal miR-210 suggests that exosomal miR-210 expression was high and significantly associated with vascular invasion and TNM stage and was an independent risk factor for PDAC overall survival.

CONCLUSIONS

PDAC cell-secreted exosomes could promote angiogenesis and cellular permeability of neighboring endothelial angiogenesis or permeability via miR-210 transmission. Exosomal miR-210 may play important roles in tumor biology and may be a useful prognostic marker in PDAC.