scholarly journals The differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma: the values of CT imaging features and texture analysis

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Chuangen Guo ◽  
Xiaoling Zhuge ◽  
Qidong Wang ◽  
Wenbo Xiao ◽  
Zhonglan Wang ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Texture Analysis ◽  
Neuroendocrine Carcinoma ◽  
Ct Imaging ◽  
Ductal Adenocarcinoma ◽  
Imaging Features ◽  
Pancreatic Neuroendocrine Carcinoma

scholarly journals Molecular drivers and cells of origin in pancreatic ductal adenocarcinoma and pancreatic neuroendocrine carcinoma

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
He-Li Gao ◽  
Wen-Quan Wang ◽  
Xian-Jun Yu ◽  
Liang Liu
Keyword(s):  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Neuroendocrine Carcinoma ◽  
Pancreatic Neuroendocrine Tumor ◽  
Ductal Adenocarcinoma ◽  
Neuroendocrine Neoplasm ◽  
Cell Of Origin ◽  
Cells Of Origin ◽  
Pancreatic Neuroendocrine Neoplasm ◽  
Pancreatic Neuroendocrine Carcinoma

Abstract Pancreatic cancer is one of the most common causes of cancer-related deaths worldwide. The two major histological subtypes of pancreatic cancer are pancreatic ductal adenocarcinoma (PDAC), accounting for 90% of all cases, and pancreatic neuroendocrine neoplasm (PanNEN), which makes up 3–5% of all cases. PanNEN is classified into well-differentiated pancreatic neuroendocrine tumor and poorly-differentiated pancreatic neuroendocrine carcinoma (PanNEC). Although PDAC and PanNEN are commonly thought to be different diseases with distinct biology, cell of origin, and genomic abnormalities, the idea that PDAC and PanNEC share common cells of origin has been gaining support. This is substantiated by evidence that the molecular profiling of PanNEC is genetically and phenotypically related to PDAC. In the current review, we summarize published studies pointing to common potential cells of origin and speculate about how the distinct paths of differentiation are determined by the genomic patterns of each disease. We also discuss the overlap between PDAC and PanNEC, which has been noted in clinical observations.

Characterization of undiagnosed pancreatic ductal adenocarcinoma on CT scans.

2021 ◽  
Vol 39 (3_suppl) ◽  
pp. 380-380
Author(s):  
John Chang ◽  
Madelyn Bartels ◽  
Kelsey Beyer ◽  
Ashley Maitland ◽  
Richard Taft Peterson ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
The Body ◽  
Ct Scans ◽  
Ductal Adenocarcinoma ◽  
Imaging Features ◽  
Cognitive Errors ◽  
Radiologic Findings ◽  
Stage 1 ◽  
Improved Technology ◽  
Radiologic Features

380 Background: Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths. At present, the best 5-year survival is 25% for resectable PDAC. For small (1 cm) stage 1 PDAC, resection has resulted in much better survival. The goal of this study was to evaluate the appearance and location of early undiagnosed PDAC on computed tomography scans (CT) prior to diagnosis with the goal of minimizing missing early PDAC. We also categorize the errors as either perceptive or cognitive. Methods: PDAC cases were retrospectively reviewed from 1/1/2012 through 12/31/2018 from our tumor registry, identifying 81 cases with paired CT scans both at the time of and prior to diagnosis. Among these, 31 contained imaging features considered diagnostic or suspicious for early PDAC(38%). These “errors” were classified by radiologic features and as well as by location. In addition, errors were classified into “perceptive errors" when the first study was read as normal, and as “cognitive errors” when the report noted an abnormality but failed to note suspicion for malignancy. Results: Among the 31 undiagnosed PDAC, 18 had features of an identifiable mass (58%), 9 had pancreatic ductal dilatation (29%), and 4 had evidence of perivascular soft tissue (13%). 44% of undiagnosed tumors were located in the head-neck, 39% in the body, and 17% in the tail. Perceptive errors were found in 58% and 42% were cognitive. No significant differences were seen between perceptive and cognitive errors based on suspicious features. Conclusions: Radiologic findings of early PDAC was retrospectively evident in more than one third of cases in which prior imaging was performed. These findings are most often masses or ductal dilatation. Location of these undiagnosed tumors were distributed throughout the gland. This study identifies the radiologic features of undiagnosed PDAC which may provide an opportunity for future prospective studies and improved technology which may improve early detection of pancreatic cancer.

Differentiating hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinoma based on CT texture analysis

2019 ◽  
Vol 61 (5) ◽  
pp. 595-604 ◽  
Author(s):  
Zhonglan Wang ◽  
Xiao Chen ◽  
Jianhua Wang ◽  
Wenjing Cui ◽  
Shuai Ren ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Texture Analysis ◽  
Neuroendocrine Tumors ◽  
Texture Features ◽  
Ct Images ◽  
Ductal Adenocarcinoma ◽  
Pancreatic Neuroendocrine Tumors ◽  
Portal Phase ◽  
Contrast Enhanced ◽  
Ct Texture Analysis

Background Hypovascular pancreatic neuroendocrine tumor is usually misdiagnosed as pancreatic ductal adenocarcinoma. Purpose To investigate the value of texture analysis in differentiating hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinoma on contrast-enhanced computed tomography (CT) images. Material and Methods Twenty-one patients with hypovascular pancreatic neuroendocrine tumors and 63 patients with pancreatic ductal adenocarcinomas were included in this study. All patients underwent preoperative unenhanced and dynamic contrast-enhanced CT examinations. Two radiologists independently and manually contoured the region of interest of each lesion using texture analysis software on pancreatic parenchymal and portal phase CT images. Multivariate logistic regression analysis was performed to identify significant features to differentiate hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. Receiver operating characteristic curve analysis was performed to ascertain diagnostic ability. Results The following CT texture features were obtained to differentiate hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas: RMS (root mean square) (odds ratio [OR] = 0.50, P<0.001), Quantile50 (OR = 1.83, P<0.001), and sumAverage (OR = 0.92, P=0.007) in parenchymal images and “contrast” in portal phase images (OR = 6.08, P<0.001). The areas under the curves were 0.76 for RMS (sensitivity = 0.75, specificity = 0.67), 0.73 for Quantile50 (sensitivity = 0.60, specificity = 0.77), 0.70 for sumAverage (sensitivity = 0.65, specificity = 0.82), 0.85 for the combined texture features (sensitivity = 0.77, specificity = 0.85). Conclusion CT texture analysis may be helpful to differentiate hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. The three combined texture features showed acceptable diagnostic performance.

Diffuse pancreatic ductal adenocarcinoma: Characteristic imaging features

2008 ◽  
Vol 67 (2) ◽  
pp. 321-328 ◽  
Author(s):  
Young Jun Choi ◽  
Jae Ho Byun ◽  
Ji-Youn Kim ◽  
Myung-Hwan Kim ◽  
Se Jin Jang ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Imaging Features ◽  
Characteristic Imaging
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