Use of ring-enhancement and focal necrosis to differentiate pancreatic adenosquamous carcinoma from pancreatic ductal adenocarcinoma on CT and MRI

Fully automated magnetic resonance imaging-based radiomics analysis for differentiating pancreatic adenosquamous carcinoma from pancreatic ductal adenocarcinoma

PURPOSE

To develop and validate an automated magnetic resonance imaging (MRI)-based model to preoperatively differentiate pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC).

METHODS

This retrospective study included patients with surgically resected, histopathologically confirmed PASC or PDAC who underwent MRI between January 2011 and December 2020. According to time of treatment, they were divided into training and validation sets. Automated deep-learning-based artificial intelligence was used for pancreatic tumor segmentation. Linear discriminant analysis was performed with conventional MRI and radiomic features to develop clinical, radiomics, and mixed models in the training set. The models' performances were determined from their discrimination and clinical utility. Kaplan-Meier and log-rank tests were used for survival analysis.

RESULTS

Overall, 389 and 123 patients with PDAC (age, 61.37 ± 9.47 years; 251 men) and PASC (age, 61.99 ± 9.82 years; 78 men) were included, respectively; they were split into the training (n = 358) and validation (n = 154) sets. The mixed model showed good performance in the training and validation sets (area under the curve: 0.94 and 0.96, respectively). The sensitivity, specificity, and accuracy were 76.74%, 93.38%, and 89.39% for the training set, respectively, and 67.57%, 97.44%, and 90.26% for the validation set, respectively. The mixed model outperformed the clinical (p = 0.001) and radiomics (p = 0.04) models in the validation set. Log-rank test revealed significantly longer survival in the predicted PDAC group than in the predicted PASC group (p = 0.003), according to the mixed model.

CONCLUSION

Our mixed model, which combined MRI and radiomic features, can be used to differentiate PASC from PDAC.

Research advances and treatment perspectives of pancreatic adenosquamous carcinoma

BACKGROUND

As a malignant tumor, pancreatic cancer has an extremely low overall 5-year survival rate. Pancreatic adenosquamous carcinoma (PASC), a rare pancreatic malignancy, owns clinical presentation similar to pancreatic ductal adenocarcinoma (PDAC), which is the most prevalent pancreatic cancer subtype. PASC is generally defined as a pancreatic tumor consisting mainly of adenocarcinoma tissue and squamous carcinoma tissue. Compared with PDAC, PASC has a higher metastatic potential and worse prognosis, and lacks of effective treatment options to date. However, the pathogenesis and treatment of PASC are not yet clear and are accompanied with difficulties.

CONCLUSION

The present paper systematically summarizes the possible pathogenesis, diagnosis methods, and further suggests potential new treatment directions through reviewing research results of PASC, including the clinical manifestations, pathological manifestation, the original hypothesis of squamous carcinoma and the potential regulatory mechanism. In short, the present paper provides a systematic review of the research progress and new ideas for the development mechanism and treatment of PASC.

Non-enhanced magnetic resonance imaging-based radiomics model for the differentiation of pancreatic adenosquamous carcinoma from pancreatic ductal adenocarcinoma

Purpose

To evaluate the diagnostic performance of radiomics model based on fully automatic segmentation of pancreatic tumors from non-enhanced magnetic resonance imaging (MRI) for differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC).

Materials and methods

In this retrospective study, patients with surgically resected histopathologically confirmed PASC and PDAC who underwent MRI scans between January 2011 and December 2020 were included in the study. Multivariable logistic regression analysis was conducted to develop a clinical and radiomics model based on non-enhanced T1-weighted and T2-weighted images. The model performances were determined based on their discrimination and clinical utility. Kaplan-Meier and log-rank tests were used for survival analysis.

Results

A total of 510 consecutive patients including 387 patients (age: 61 ± 9 years; range: 28-86 years; 250 males) with PDAC and 123 patients (age: 62 ± 10 years; range: 36-84 years; 78 males) with PASC were included in the study. All patients were split into training (n=382) and validation (n=128) sets according to time. The radiomics model showed good discrimination in the validation (AUC, 0.87) set and outperformed the MRI model (validation set AUC, 0.80) and the ring-enhancement (validation set AUC, 0.74).

Conclusions

The radiomics model based on non-enhanced MRI outperformed the MRI model and ring-enhancement to differentiate PASC from PDAC; it can, thus, provide important information for decision-making towards precise management and treatment of PASC.

Pancreatic Adenosquamous Carcinoma: A Rare Pathological Subtype of Pancreatic Cancer

Pancreatic adenosquamous carcinoma (PASC) is a rare pathological subtype of pancreatic cancer (PC), with a worse prognosis than pancreatic ductal adenocarcinoma (PDAC). Due to its rarity, our knowledge of PASC and its biological characteristics are limited. In this review, we provide an overview of the histogenesis, genetic features, diagnosis, treatment, and prognosis of PASC, as well as pancreatic squamous cell carcinoma (PSCC). The information provided here may help to clarify our understanding of PASC and provide useful avenues for further research on this disease.

Endosonography-Guided Tissue Acquisition for Diagnosis of Squamous Carcinoma of the Pancreas: A Report of Three Cases

While approximately 85% of neoplasms are ductal pancreatic adenocarcinomas (DPA), adenosquamous pancreatic carcinoma (APC) is a rare subtype of pancreatic cancer that exhibits aggressive behavior and poor prognosis. The authors report three cases of primary APC diagnosed through endoscopic ultrasound-guided tissue acquisition (EUS-TA) using the new ProCore 20G needle, which had been developed to improve fine-needle aspiration results by providing more tissue for histopathology. Given its ability for microcore retrieval, pancreatic stroma examination, and excellent histopathology results, EUS-TA has exhibited exceptional diagnostic yield among patients with solid pancreatic lesions. All three APC cases presented herein had been accurately diagnosed using immunohistochemistry after microcore acquisition.

Basic pancreatic lesions: Radiologic-pathologic correlation

The basic pancreatic lesions include location, size, shape, number, capsule, calcification/calculi, hemorrhage, cystic degeneration, fibrosis, pancreatic duct alterations, and microvessel. One or more basic lesions form a kind of pancreatic disease. As recognizing the characteristic imaging features of pancreatic basic lesions and their relationships with pathology aids in differentiating the variety of pancreatic diseases. The purpose of this study is to review the pathological and imaging features of the basic pancreatic lesions.