Pancreatic Solid and Cystic Neoplasms: Diagnostic Evaluation and Intervention

Diffuse Involvement of Pancreas is not Always Autoimmune Pancreatitis

RATIONALE AND OBJECTIVES

To determine the prevalence of diffuse involvement of pancreas and to identify the findings of malignancies using enhancement computed tomography (CT).

MATERIALS AND METHODS

A total of 1,0249 patients performed enhancement CT in our hospital over 62 months were investigated and the final study cohort includes 245 patients (170 males, 75 females; mean age, 56.94 ± 12.17 years). The reference standard is the final clinical/pathological diagnosis. The lesion-to-aorta enhancement ratio (LAR) on the pancreatic arterial phase, portal phase and delayed phase (DP) and the traditional CT findings were evaluated. Intergroup comparisons between malignancies and non-malignancies lesions were performed. Univariate and multivariate analyses were conducted to identify findings predicting malignancies.

RESULTS

The prevalence of malignancy was 45.3% (111/245) of diffuse enlargement of pancreas. All benign lesions were autoimmune pancreatitis 54.7% (n = 134). The most common malignant lesion was pancreatic ductal adenocarcinoma (n = 88, 35.9%). Other rare lesions with malignant potential included pancreatic neuroendocrine tumor (n = 11, 4.5%), lymphoma (n = 4, 1.6%), metastasis (n = 4, 1.6%), solid pseudopapillary neoplasm (n = 3, 1.2%) and acinar cell carcinoma (n = 1, 0.4%). Residual normal pancreas parenchyma, heterogeneity, short axis (cut-off value, 3.15 cm) and LARDP (cut-off value, 0.75) were independent predictors of malignancies. When the above predictors were combined, a sensitivity of 94.2%, a specificity of 90.8% were attained.

CONCLUSION

Diffuse involvement of the pancreas is rare and is not a specific sign of autoimmune pancreatitis, and it is associated with a wide spectrum of malignant conditions. Dynamic enhancement CT is helpful to identifying malignancies.

Contrast-enhanced ultrasound of pancreatic melanoma: A case report and literature review

Melanoma is a malignant tumor that originates from melanocytes, most of which are of cutaneous origin. Most melanomas identified in the pancreas are metastatic, and primary pancreatic melanoma is extremely rare and has rarely been discussed. The correct preoperative diagnosis of pancreatic metastatic melanoma, especially primary melanoma, is challenging. Herein, we report a 43-year-old man who presented to our hospital due to unexplained left abdominal distension and pain. Abdominal ultrasound examination demonstrated multiple space-occupying lesions of the pancreas, and hypoechoic masses partially filled the splenic vein behind the pancreatic body. In the contrast-enhanced ultrasound (CEUS), all of these lesions showed iso-enhancement to slight hypo-enhancement in the arterial phase and hypo-enhancement in the venous phase. Masses in the splenic vein also showed hypo-enhancement. Imaging features suggested that the pancreatic lesions were malignant tumors. The tumor markers carcinoembryonic antigen, carbohydrate antigen 125 and carbohydrate antigen 19-9 were within normal limits. Based on clinical symptoms, imaging findings and incidence of pancreatic tumors, the patient’s clinical diagnosis was pancreatic carcinoma. Surgery was performed for the patient, while postoperative pathology confirmed malignant melanoma of the pancreas. Therefore, it is significant to identify the clinical and imaging manifestations of pancreatic melanoma in order to better manage the disease. Herein, we reported this case and reviewed the literature from 2000 to 2021 on the clinical and imaging features of 26 patients with pancreatic melanoma. It may improve clinicians’ awareness of the clinical and imaging performance of pancreatic melanoma, resulting in improved diagnosis, differential diagnosis, treatment, and outcomes.

Application of CT-Based Radiomics in Discriminating Pancreatic Cystadenomas From Pancreatic Neuroendocrine Tumors Using Machine Learning Methods

Objectives

The purpose of this study aimed at investigating the reliability of radiomics features extracted from contrast-enhanced CT in differentiating pancreatic cystadenomas from pancreatic neuroendocrine tumors (PNETs) using machine-learning methods.

Methods

In this study, a total number of 120 patients, including 66 pancreatic cystadenomas patients and 54 PNETs patients were enrolled. Forty-eight radiomic features were extracted from contrast-enhanced CT images using LIFEx software. Five feature selection methods were adopted to determine the appropriate features for classifiers. Then, nine machine learning classifiers were employed to build predictive models. The performance of the forty-five models was evaluated with area under the curve (AUC), accuracy, sensitivity, specificity, and F1 score in the testing group.

Results

The predictive models exhibited reliable ability of differentiating pancreatic cystadenomas from PNETs when combined with suitable selection methods. A combination of DC as the selection method and RF as the classifier, as well as Xgboost+RF, demonstrated the best discriminative ability, with the highest AUC of 0.997 in the testing group.

Conclusions

Radiomics-based machine learning methods might be a noninvasive tool to assist in differentiating pancreatic cystadenomas and PNETs.

Pancreatic sarcomatoid carcinoma: CT, MRI, and 18F-FDG PET/CT features

AIM

To investigate computed tomography (CT), magnetic resonance imaging (MRI), and combined 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (¹⁸F-FDG) positron-emission tomography (PET)/CT features of pancreatic sarcomatoid carcinoma (PSC).

MATERIALS AND METHODS

The hospital database was searched retrospectively for the patients with PSC confirmed at histopathology after surgery. Ten patients who underwent unenhanced and enhanced CT (n=4), unenhanced and enhanced MRI (n=2), ¹⁸F-FDG PET/CT (n=2), and both enhanced CT and ¹⁸F-FDG PET/CT (n=2) were enrolled. Two patients underwent additional delayed PET/CT. The maximum standardised uptake value (SUVmax) was measured on PET/CT images.

RESULTS

Eleven lesions were detected in 10 patients. Solid and cystic components (n=6), intratumoural haemorrhage (n=1), nodular calcification (n=2), main pancreatic duct dilatation resulted from lesion obstruction (n=5) or compression (n=3), cholangiectasis (n=5), vascular and peripheral organ invasion (n=5 and 6, respectively), hepatic and lymphatic metastases (n=4 and 2, respectively) were detected. All five lesions in four patients who underwent PET/CT showed intense FDG uptake on PET/CT with SUVmax (16, range 10.9-21.1). Increase of FDG uptake (SUVmax = 18.9, 20.1, and 27.3, respectively) was revealed on the delayed scan of three lesions in two patients.

CONCLUSIONS

PSCs were more commonly ill-defined solid cystic masses, which caused pancreatic duct obstruction/compression without pancreatic parenchymal atrophy, and these masses on PET/CT showed high FDG uptake on both initial and delayed PET/CT.

Imaging findings for mucinous tumors of the abdomen and pelvis

This article aims to describe the imaging findings for mucinous tumors of the abdomen and pelvis, which have a similar appearance on imaging tests regardless of the organ in which they develop. Due to the high water content of mucus, the appearance of these tumors is generally similar to that of water on ultrasonography, computed tomography, and magnetic resonance imaging. Another common feature of mucin-producing tumors is that calcifications are often present. The rupture of these lesions and accumulation of mucinous material in the peritoneal cavity gives rise to pseudomyxoma peritonei. It is important to identify mucinous tumors because they have a different prognosis and clinical course than non-mucinous tumors and require different management. Depending on their anatomic location and their imaging characteristics, the treatment approach varies from follow-up to radical surgery together with chemotherapy or radiotherapy or both.

Differentiation of atypical pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas: Using whole-tumor CT texture analysis as quantitative biomarkers

Background

To explore the application value of computed tomography (CT) texture analysis in differentiating atypical pancreatic neuroendocrine tumors (pNET) from pancreatic ductal adenocarcinomas (PDAC).

Materials and methods

This single‐center retrospective study was approved by local institutional review board, and the requirement for informed consent was waived. We retrospectively analyzed 127 patients with 50 PDACs and 77 pNETs in pathology database between January 2012 and May 2017.These patients successfully finished preoperative contrast‐enhanced CT test. Texture parameters (mean, median, 5th, 10th, 25th, 75th, 90th percentiles, skewness, kurtosis and entropy) were extracted from portal images and compared between PDAC and 77 pNET groups using proper statistical method. The optimal parameters for differentiating PDACs and atypical pNETs were gained through receiver operating characteristic (ROC) curves.

Results

On the basis of arterial enhancement, 52 pNETs (67%, 52/77) were typical hypervascular and 25 pNETs (32%, 25/77) were atypical hypovascular. Compared with PDACs, atypical pNETs had statistically higher mean, median, 5th, 10th, and 25th percentiles (P = 0.006, 0.024, 0.000, 0.001, 0.021, respectively) and statistically lower skewness (P = 0.017). However, there were no difference for 75th, 90th percentiles, kurtosis and entropy between these two tumors (P = 0.232, 0.415, 0.143, 0.291, respectively). For differentiating PDACs and atypical pNETs, 5th percentile and 5th+skewness were optimal parameters for alone and combined diagnosis, respectively.

Conclusion

Volumetric CT texture features, especially combined diagnosis of 5th+skewness can be used as a quantitative tool to distinguish atypical pNETs from PDACs.

Differentiation of benign and malignant solid pancreatic masses using magnetic resonance elastography with spin-echo echo planar imaging and three-dimensional inversion reconstruction: a prospective study

OBJECTIVES

To determine the diagnostic performance of MR elastography (MRE) and compare it with serum CA19-9 in differentiating malignant from benign pancreatic masses, with emphasis on differentiating between pancreatic ductal adenocarcinoma (PDAC) and mass-forming pancreatitis (MFP).

METHODS

We performed a prospective, consecutive, 24-month study in 85 patients with solid pancreatic masses confirmed by histopathologic examinations. The mass stiffness and stiffness ratio (calculated as the ratio of mass stiffness to the parenchymal stiffness) were assessed. The diagnostic accuracy was analysed by calculating the area under the ROC curve (AUROC).

RESULTS

The final diagnosis included 54 malignant tumours (43 patients with PDAC) and 31 benign masses (24 patients with MFP). The stiffness ratio showed better diagnostic performance than the mass stiffness and serum CA19-9 for the differentiation between malignant and benign masses (AUC: 0.912 vs. 0.845 vs. 0.702; P = 0.026, P < 0.001) and, specifically, between PDAC and MFP (AUC: 0.955 vs. 0.882 vs. 0.745; P = 0.026, P = 0.003). The sensitivity, specificity, and accuracy of stiffness ratio for the differentiation of PDAC and MFP were all higher than 0.9.

CONCLUSIONS

MRE presents an effective and quantitative strategy for non-invasive differentiation between PDAC and MFP based on their mechanical properties.

KEY POINTS

• 3D MRE is useful for calculating stiffness of solid pancreatic tumours. • Stiffness ratio outperformed stiffness and CA19-9 for differentiating PDAC from MFP. • Incorporation of 3D MRE into a standard MRI protocol is recommended.

Primary Leiomyosarcoma of the Pancreas-a Case Report and a Comprehensive Review

Purpose

Primary mesenchymal tumors of the pancreas are rare, with leiomyosarcomas the most encountered entities among the pancreatic sarcomas. With few exceptions, single case reports published over the last six decades constitute the entire scientific literature on this topic. Thus, evidence regarding clinical decision-making is scant.

Methods

Based on a case report and an extensive literature search in PubMed, we discuss the clinical aspects and current management of this rare malignancy.

Results

We identified only two papers with more than a single case presentation; these institutional patient series were limited to five and nine patients. Additionally, a few papers sought to summarize the individual case reports published in the English and/or Chinese language. The clinical presentation is rather non-specific. Moreover, modern imaging modalities are insufficiently accurate to diagnose leiomyosarcoma of the pancreas. Treatment goals include a complete resection with free margins. Proper morphologic examination using immunohistochemistry and the application of a grading system are clinically important for prognostication. The efficacy of adjuvant treatments has not been established.

Conclusion

Primary pancreatic leiomyosarcoma is extremely rare, and the scientific literature is primarily based on single case reports. Conclusions on management and prognosis should be drawn with caution. A multidisciplinary team consultation is warranted to discuss a thorough individual treatment plan based on the available scientific literature, despite its low evidence level.

Imaging in pancreatic disease

Pancreatic diseases, chronic pancreatitis, pancreatic cancer and diabetes mellitus, taken together, occur in >10% of the world population. Pancreatic diseases, as with other diseases, benefit from early intervention and appropriate diagnosis. Although imaging technologies have given clinicians an unprecedented toolbox to aid in clinical decision-making, advances in these technologies and development of molecular-based diagnostic tools could enable physicians to identify diseases at an even earlier stage and, thereby, improve patient outcomes. In this Review, we discuss and identify gaps in the use of imaging techniques for the early detection and appropriate treatment stratification of various pancreatic diseases, including diabetes mellitus, acute and chronic pancreatitis and pancreatic cancer. Imaging techniques discussed are MRI, CT, PET and ultrasonography. Additionally, the identification of new molecular targets for imaging and the development of contrast agents that are able to give molecular information in noninvasive radionuclear imaging and ultrasonography are emerging areas of innovation that could lead to increased diagnostic accuracy and improved patient outcomes.

Nonhypervascular Pancreatic Neuroendocrine Tumors: Differential Diagnosis from Pancreatic Ductal Adenocarcinomas at MR Imaging-Retrospective Cross-sectional Study

Purpose To determine useful magnetic resonance (MR) imaging features to differentiate nonhypervascular pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs). Materials and Methods The institutional review board approved this retrospective study and waived the informed consent requirement. Seventy-four patients with surgically confirmed PNETs and 82 patients with PDACs who underwent gadobutrol-enhanced MR imaging were included. Two radiologists independently evaluated the morphologic characteristics and temporal enhancement patterns of each tumor. Quantitative analysis, including measurement of tumor size, maximal upstream parenchymal thickness (MUPT), contrast-to-noise ratio, and apparent diffusion coefficient values, was performed. Uni- and multivariate logistic regression analyses were performed to identify relevant features to differentiate between PNETs and PDACs. Results On the basis of arterial enhancement, 38 PNETs (51%, 38 of 74) were hypervascular and 36 PNETs (49%, 36 of 74) were nonhypervascular. At MR imaging, nonhypervascular PNETs showed significantly higher frequencies of a well-defined margin, portal hyper- or isoenhancement, and MUPT of 10 mm or greater but lower frequencies of ductal dilatation, vascular invasion, and peripancreatic infiltration when compared with PDACs (P < .05 for all). At multivariate analysis, a well-defined margin and portal hyper- or isoenhancement were independent significant differentiators of PNETs from PDACs (odds ratio, 20.3 and 16.1, respectively). When applying the criteria of a well-defined margin and portal hyper- or isoenhancement, 64% of sensitivity and 99% of specificity were observed for the differential diagnosis of PNETs from PDACs. Conclusion A well-defined margin and hyper- or isoenhancement in the portal venous phase are useful MR imaging features that are more common in nonhypervascular PNETs and may help discriminate nonhypervascular PNETs from PDACs. ^© RSNA, 2017 Online supplemental material is available for this article.

PANCREATIC INCIDENTALOMAS: IS IT NET OR NOT?

ABBREVIATIONS

FNA = fine-needle aspirate IPAS = intrapancreatic accessory spleen PNET = pancreatic neuroendocrine tumor.