Differentiating pancreatic ductal adenocarcinoma from pancreatic serous cystadenoma, mucinous cystadenoma, and a pseudocyst with detailed analysis of cystic features on CT scans: a preliminary study

Misdiagnosis of pancreatic tuberculosis as a pancreatic cystic neoplasm - A case report

Pancreatic tuberculosis is an extremely rare condition. Its non-specific clinical and radiological findings resemble pancreatic malignancy. Here, we report a case of pancreatic tuberculosis that presented with abdominal pain and dyspeptic symptoms for 2 months and was misdiagnosed as a pancreatic cystic neoplasm. Abdominal magnetic resonance imaging showed a well-demarcated exophytic lesion with multiple T2 high signals small cystic areas in the anterior superior part of the head of the pancreas measuring 23 × 20 × 28 mm. This patient has undergone laparotomy and excision of the pancreatic mass. Histological examination revealed granulomatous inflammation of a lymph node with caseation, which was pathognomonic of tuberculosis. She was treated for tuberculosis for 6 months and has become symptom free. The diagnosis of pancreatic tuberculosis could be misleading and should be considered when dealing with pancreatic masses in countries with high incidence.

Liver metastasis or a pseudocyst? A rare presentation of leiomyosarcoma's metastasis in the liver

Gastrointestinal neoplasms most commonly metastasize to the liver, where they are typically found as solid and hypervascular lesions. Here, we describe a case of a 44-year-old man with a leiomyosarcoma of the rectum, who at the time of diagnosis presented with a small (5 mm in diameter) cyst-like lesion in the liver. Positron emission tomography demonstrated no increased metabolism in the area of the cyst, suggesting a benign character of the lesion. However, after 3 years, CT scans revealed enlargement of the cyst, and local surgical excision was performed. The results of histopathological examination of the resected material were consistent with metastatic leiomyosarcoma. Subsequently, the patient developed lung metastases and died within 2 years. Our case describes a very rare presentation of leiomyosarcoma's metastasis that led to an ill-fated misdiagnosis and dismal disease outcome.

Incidental Pancreatic Cysts on Cross-Sectional Imaging

Incidental pancreatic cysts are commonly encountered in radiology practice. Although some of these are benign, mucinous varieties have a potential to undergo malignant transformation. Characterization of some incidental pancreatic cysts based on imaging alone is limited, and given that some pancreatic cysts have a malignant potential, various societies have created guidelines for the management and follow-up of incidental pancreatic cysts. This article reviews the imaging findings and work-up of pancreatic cysts and gives an overview of the societal guidelines for the management and follow-up of incidental pancreatic cysts.

Management of Incidental Pancreatic Cystic Lesions: Integrating Novel Diagnostic and Prognostic Factors With Current Clinical Guidelines

Owing to increased detection rates, the diagnosis and management of incidental pancreatic cysts has become a common predicament. Up to 13% of patients undergoing cross-sectional imaging studies for other indications are found to have pancreatic cystic lesions. Although most cystic lesions are benign, the malignant potential of several types of pancreatic cysts makes accurate classification vital to directing therapy. To this end, advances in the last decade led to better characterization of pancreatic cyst morphology and hence enhanced the ability to predict underlying histopathology, and biological behavior. Although accurate classification remains a challenge, the utilization of complementary diagnostic tools is the optimal approach to dictate management. The following review includes a description of pancreatic cysts, a critical review of current and emerging diagnostic techniques and a review of recent guidelines in the management of incidental pancreatic cysts.

Pancreatic Ductal Adenocarcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis For Prediction Of Histopathological Grade

Purpose

To assess the performance of combining computed tomography (CT) texture analysis with machine learning for discriminating different histopathological grades of pancreatic ductal adenocarcinoma (PDAC).

Methods

From July 2012 to August 2017, this retrospective study comprised 56 patients with confirmed histopathological PDAC (32 men, 24 women, mean age 64.04±7.82 years) who had undergone preoperative contrast-enhanced CT imaging within 1 month before surgery. Two radiologists blinded to the histopathological outcome independently segmented lesions for quantitative texture analysis. Histogram features, co-occurrence, and run-length texture were calculated. A support-vector machine was constructed to predict the pathological grade of PDAC based on preoperative texture features.

Results

Pathological analysis confirmed 37 low-grade PDAC (five well-differentiated/grade I and 32 moderately differentiated/grade II) and 19 high-grade PDAC (19 poorly differentiated/grade III) tumors. There were no significant differences in clinical or biological characteristics between patients with high-grade and low-grade tumors (P>0.05). There were significant differences between low-grade PDAC and high-grade PDAC on nine histogram features, seven run-length features, and two co-occurrence features. Cluster shade was the most important predictor (sensitivity 0.315). Using these texture features, the support-vector machine achieved 86% accuracy, 78% sensitivity, 95% and specificity.

Conclusion

Machine learning-based CT texture analysis accurately predicted histopathological differentiation grade of PDAC based on preoperative texture features, leading to maximization patient survival and achievement of personalized precision treatment.

[Feasibility analysis of predicting expression of Ki67 in pancreatic cystic neoplasm based on radiomics]

This study aims to predict expression of Ki67 molecular marker in pancreatic cystic neoplasm using radiomics. We firstly manually segmented tumor area in multi-detector computed tomography (MDCT) images. Then 409 high-throughput features were automatically extracted and the least absolute shrinkage selection operator (LASSO) regression model was used for feature selection. After 200 bootstrapping repetitions of LASSO, 20 most frequently selected features made up the optimal feature set. Then 200 bootstrapping repetitions of support vector machine (SVM) classifier with 10-fold cross-validation were used to avoid overfitting and accurately predict the Ki67 expression. The highest prediction accuracy could achieve 85.29% and the highest area under the receiver operating characteristic curve (AUC) was 91.54% with a sensitivity (SENS) of 81.88% and a specificity (SPEC) of 86.75%. According to the results of experiment, the feasibility of predicting expression of Ki67 in pancreatic cystic neoplasm based on radiomics was verified.

Computer-Aided Diagnosis of Pancreas Serous Cystic Neoplasms: A Radiomics Method on Preoperative MDCT Images

OBJECTIVE

Our aim was to propose a preoperative computer-aided diagnosis scheme to differentiate pancreatic serous cystic neoplasms from other pancreatic cystic neoplasms, providing supportive opinions for clinicians and avoiding overtreatment.

MATERIALS AND METHODS

In this retrospective study, 260 patients with pancreatic cystic neoplasm were included. Each patient underwent a multidetector row computed tomography scan and pancreatic resection. In all, 200 patients constituted a cross-validation cohort, and 60 patients formed an independent validation cohort. Demographic information, clinical information, and multidetector row computed tomography images were obtained from Picture Archiving and Communication Systems. The peripheral margin of each neoplasm was manually outlined by experienced radiologists. A radiomics system containing 24 guideline-based features and 385 radiomics high-throughput features was designed. After the feature extraction, least absolute shrinkage selection operator regression was used to select the most important features. A support vector machine classifier with 5-fold cross-validation was applied to build the diagnostic model. The independent validation cohort was used to validate the performance.

RESULTS

Only 31 of 102 serous cystic neoplasm cases in this study were recognized correctly by clinicians before the surgery. Twenty-two features were selected from the radiomics system after 100 bootstrapping repetitions of the least absolute shrinkage selection operator regression. The diagnostic scheme performed accurately and robustly, showing the area under the receiver operating characteristic curve = 0.767, sensitivity = 0.686, and specificity = 0.709. In the independent validation cohort, we acquired similar results with receiver operating characteristic curve = 0.837, sensitivity = 0.667, and specificity = 0.818.

CONCLUSION

The proposed radiomics-based computer-aided diagnosis scheme could increase preoperative diagnostic accuracy and assist clinicians in making accurate management decisions.

Mucinous cystadenoma of pancreas with honeycombing appearance: Radiological-Pathological correlation

Most mucinous cystadenomas of pancreas are solitary and multilocular with a few large compartments. Serous cystadenomas usually have a polycystic or microcystic (honeycomb) pattern consisting of collection of cysts (usually >6) that range from few millimetres up to 2 cm in size. Here we present a case of mucinous cystadenoma of pancreas showing an unusual appearance of honeycombing (which has not been described so far) using imaging studies such as endoscopic ultrasound and computed tomography with histopathological confirmation of the diagnosis.

Calcified peripancreatic lymph nodes in pancreatic and hepatic tuberculosis mimicking pancreatic malignancy: A case report and review of literature

RATIONALE

Tuberculosis remains a serious menace to the health of people. Isolated hepatic tuberculosis is rare and pancreatic tuberculosis is extremely rare. The preoperative diagnosis of pancreatic tuberculosis remains a great challenge.

PATIENT CONCERNS

A 58-year-old Asian woman was referred to our hospital for evaluation of low back pain for 4 years and abdominal pain for 1 month.

DIAGNOSES

Computed tomography (CT) of the abdomen showed a hypodense mass in the pancreatic head and neck with abundant calcifications, a hypodense lesion in the liver without calcification, peripancreatic lymphadenopathy, calcifications in some lymph nodes. CT-guided fine needle aspiration biopsy of the hepatic lesion was carried out and the cytological examination revealed hepatic tuberculosis.

INTERVENTIONS

The patient was treated with antituberculous therapy for 1 year.

OUTCOMES

Low back pain and abdominal pain disappeared 3 months after initial treatment and after 2 year of follow-up, the patient was asymptomatic.

LESSONS

Our data hint that calcifications in both pancreatic lesions and peripancreatic lymph nodes may suggest pancreatic tuberculosis rather than pancreatic malignancy.

Current concepts in molecular genetics and management guidelines for pancreatic cystic neoplasms: an essential update for radiologists

Cystic neoplasms in the pancreas are encountered frequently on imaging, often detected incidentally during evaluation for other conditions. They can have a variety of clinical and imaging presentations, and similarly, wide-ranging prognostic and treatment implications. In the majority, imaging helps in diagnosis of pancreatic cystic neoplasms (PCNs) and guides management decisions. But, a significant minority of the PCNs remain indeterminate. There have been multiple recent advances in biomarkers and molecular genetics which will likely prove helpful in risk stratification of PCNs. Several prominent national and international societies, as well as consensus groups have put forth recommendations to help guide management of PCNs. The purpose of this article is to discuss the role of imaging in evaluation of PCNs, review the recent advances in molecular genetics and pancreatic cyst fluid analysis, and analyze the pros and cons of major evidence-based and consensus guidelines for management of PCNs.

Usefulness of positron emission tomography (PET)/contrast-enhanced computed tomography (CE-CT) in discriminating between malignant and benign intraductal papillary mucinous neoplasms (IPMNs)

BACKGROUND/OBJECTIVES

We evaluated the usefulness of positron emission tomography (PET)/contrast-enhanced computed tomography (CE-CT) in discriminating between malignant and benign intraductal papillary mucinous neoplasms (IPMNs).

METHODS

PET/CE-CT imaging was conducted on 29 IPMN lesions, which subsequently underwent surgery. Preoperative findings on PET/CE-CT imaging were compared with the histological findings of the resected specimens to determine the diagnostic accuracy of PET/CE-CT imaging for evaluation of the differential diagnosis between benign and malignant IPMNs.

RESULTS

The final diagnoses of the 29 IPMN lesions were 9 benign and 20 malignant. Overall, 18 of the 20 malignant cases were positive for FDG uptake, while 7 of 9 benign cases were negative. The sensitivity, specificity, and diagnostic accuracy for benign/malignant differentiation using FDG uptake as a marker were 90.0%, 77.8%, and 86.2%, respectively. When guideline-based high-risk findings were used as markers, sensitivity, specificity, and diagnostic accuracy for mural nodules were 50.0%, 66.7%, and 55.2%, while they were 40.0%, 56%, and 48.3% for main duct dilatation, respectively.

CONCLUSIONS

FDG uptake on PET is a useful new marker for malignancy in benign/malignant differentiation. Because PET/CE-CT imaging is a noninvasive imaging modality that can evaluate FDG uptake in addition to the conventional high-risk findings, we believe it should be the first-line method for determining therapeutic approaches to IPMN.

Imaging Pancreatic Cysts with CT and MRI

CT and MRI are the imaging modalities of choice to guide the clinical management of incidentally discovered pancreatic cysts. Most of these lesions are mucinous cysts with varying degrees of malignant potential. This article reviews the CT and MRI findings that help differentiate a potentially aggressive lesion that requires EUS or surgery from a lesion of low malignant potential that is appropriate for imaging surveillance. The imaging-based societal guidelines for these cysts are reviewed.

Diabetic ketoacidosis as the presenting manifestation of pancreatic adenocarcinoma with cystic features

The common presenting symptoms of pancreatic cancer are abdominal pain, weight loss, and jaundice. Pancreatic adenocarcinoma presenting with diabetic ketoacidosis is a very rare emergent clinical condition. However, pancreatic ductal cystadenocarcinoma presenting with diabetic ketoacidosis was not reported. We describe a 60-year-old man with pancreatic cystadenocarcinoma presenting with diabetic ketoacidosis as the initial manifestation. It must be kept in mind that in diabetic ketoacidosis cases, the precipitating factor may be pancreatic ductal cystadenocarcinoma.

Does the Reporting Quality of Diagnostic Test Accuracy Studies, as Defined by STARD 2015, Affect Citation?

Objective

To determine the rate with which diagnostic test accuracy studies that are published in a general radiology journal adhere to the Standards for Reporting of Diagnostic Accuracy Studies (STARD) 2015, and to explore the relationship between adherence rate and citation rate while avoiding confounding by journal factors.

Materials and Methods

All eligible diagnostic test accuracy studies that were published in the Korean Journal of Radiology in 2011–2015 were identified. Five reviewers assessed each article for yes/no compliance with 27 of the 30 STARD 2015 checklist items (items 28, 29, and 30 were excluded). The total STARD score (number of fulfilled STARD items) was calculated. The score of the 15 STARD items that related directly to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 was also calculated. The number of times each article was cited (as indicated by the Web of Science) after publication until March 2016 and the article exposure time (time in months between publication and March 2016) were extracted.

Results

Sixty-three articles were analyzed. The mean (range) total and QUADAS-2-related STARD scores were 20.0 (14.5–25) and 11.4 (7–15), respectively. The mean citation number was 4 (0–21). Citation number did not associate significantly with either STARD score after accounting for exposure time (total score: correlation coefficient = 0.154, p = 0.232; QUADAS-2-related score: correlation coefficient = 0.143, p = 0.266).

Conclusion

The degree of adherence to STARD 2015 was moderate for this journal, indicating that there is room for improvement. When adjusted for exposure time, the degree of adherence did not affect the citation rate.

Computer-Aided Diagnosis for Distinguishing Pancreatic Mucinous Cystic Neoplasms From Serous Oligocystic Adenomas in Spectral CT Images

OBJECTIVE

This preliminary study aims to verify the effectiveness of the additional information provided by spectral computed tomography (CT) with the proposed computer-aided diagnosis (CAD) scheme to differentiate pancreatic serous oligocystic adenomas (SOAs) from mucinous cystic neoplasms of pancreas cystic lesions.

MATERIALS AND METHODS

This study was conducted from January 2010 to October 2013. Twenty-three patients (5 men and 18 women; mean age, 43.96 years old) with SOA and 19 patients (3 men and 16 women; mean age, 41.74 years old) with MCN were included in this retrospective study. Two types of features were collected by dual-energy spectral CT imaging as follows: conventional and additional quantitative spectral CT features. Classification results of the CAD scheme were compared using the conventional features and full feature data set. Important features were selected using support vector machine classification method combined with feature-selection technique. The optimal cutoff values of selected features were determined through receiver-operating characteristic curve analyses.

RESULTS

Combining conventional features with additional spectral CT features improved the overall accuracy from 88.37% to 93.02%. The selected features of the proposed CAD scheme were tumor size, contour, location, and low-energy CT values (43 keV). Iodine-water basis material pair densities in both arterial phase (AP) and portal venous phase (PP) were important factors for differential diagnosis of SOA and MCN. The optimal cutoff values of long axis, short axis, 40 keV monochromatic CT value in AP, iodine (water) density in AP, 43 keV monochromatic CT value in PP, and iodine (water) density in PP were 3.4 mm, 3.1 mm, 35.7 Hu, 0.32533 mg/mL, 39.4 Hu, and 0.348 mg/mL, respectively.

CONCLUSION

The combination of conventional features and additional information provided by dual-energy spectral CT shows a high accuracy in the CAD scheme. The quantitative information of spectral CT may prove useful in the diagnosis and classification of SOAs and MCNs with machine learning algorithms.

Italian consensus guidelines for the diagnostic work-up and follow-up of cystic pancreatic neoplasms

This report contains clinically oriented guidelines for the diagnostic work-up and follow-up of cystic pancreatic neoplasms in patients fit for treatment. The statements were elaborated by working groups of experts by searching and analysing the literature, and then underwent a consensus process using a modified Delphi procedure. The statements report recommendations regarding the most appropriate use and timing of various imaging techniques and of endoscopic ultrasound, the role of circulating and intracystic markers and the pathologic evaluation for the diagnosis and follow-up of cystic pancreatic neoplasms.

Characterization of pancreatic serous cystadenoma on dual-phase multidetector computed tomography

OBJECTIVE

The objective of the study was to characterize pancreatic serous cystadenomas on dual-phase multidetector computed tomography in a surgical series.

MATERIALS AND METHODS

This is a retrospective review of preoperative dual-phase multidetector computed tomographic scans from 68 patients with surgically resected and pathologically confirmed pancreatic serous cystadenomas.

RESULTS

Pancreatic serous cystadenomas were most commonly found in the tail (39%). The mean (SD) axial dimension was 4.5 (2.7) cm. A total of 36% contained internal calcifications. Dilatation of the main pancreatic duct (14%) and pancreatic parenchymal atrophy (11%) were uncommon. The mean (SD) attenuation of components with the highest attenuation was 49.1 (35.0) Hounsfield units on the arterial phase and 48.5 (33.4) Hounsfield units on the portal venous phase. Only 20% of neoplasms demonstrated "classic" morphology, as defined by multiple thin nonenhancing septations, calcifications, as well as the absence of main pancreatic duct dilatation and vascular involvement.

CONCLUSIONS

Only 20% of surgically resected serous cystadenomas fulfilled classic morphology. Attenuation was helpful in differentiating serous cystadenomas from insulinomas and other cystic pancreatic masses, but it was not helpful in differentiation from pancreatic adenocarcinomas. Morphologic features were more helpful in differentiating serous cystadenomas from malignant masses.