Uncommon presentations of common pancreatic neoplasms: a pictorial essay

Pancreatic neuroendocrine tumor: prediction of tumor grades by radiomics models based on ultrasound images

OBJECTIVE

We aimed to investigate whether the radiomics analysis based on B-mode ultrasound (BMUS) images could predict histopathological tumor grades in pancreatic neuroendocrine tumors (pNETs).

METHODS

A total of 64 patients with surgery and histopathologically confirmed pNETs were retrospectively included (34 male and 30 female, mean age 52.4 ± 12.2 years). Patients were divided into training cohort (n = 44) and validation cohort (n = 20). All pNETs were classified into Grade 1 (G1), Grade 2 (G2), and Grade 3 (G3) tumors based on the Ki-67 proliferation index and the mitotic activity according to WHO 2017 criteria. Maximum relevance minimum redundancy, least absolute shrinkage and selection operator were used for feature selection. Receiver operating characteristic curve analysis was used to evaluate the model performance.

RESULTS

Finally, 18 G1 pNETs, 35 G2 pNETs, and 11 G3 pNETs patients were included. The radiomic score derived from BMUS images to predict G2/G3 from G1 displayed a good performance with an area under the receiver operating characteristic curve of 0.844 in the training cohort, and 0.833 in the testing cohort. The radiomic score achieved an accuracy of 81.8% in the training cohort and 80.0% in the testing cohort, a sensitivity of 0.750 and 0.786, a specificity of 0.833 and 0.833 in the training/testing cohorts. Clinical benefit of the score also exhibited superior usefulness of the radiomic score, as shown by the decision curve analysis.

CONCLUSIONS

Radiomic data constructed from BMUS images have the potential for predicting histopathological tumor grades in patients with pNETs.

ADVANCES IN KNOWLEDGE

The radiomic model constructed from BMUS images has the potential for predicting histopathological tumor grades and Ki-67 proliferation indexes in patients with pNETs.

Pancreatic Cystic Lesions: Imaging Techniques and Diagnostic Features

The detection of incidental pancreatic cystic lesions has increased over time. It is crucial to separate benign from potentially malignant or malignant lesions to guide management and reduce morbidity and mortality. The key imaging features used to fully characterize cystic lesions are optimally assessed by contrast-enhanced magnetic resonance imaging/magnetic resonance cholangiopancreatography, with pancreas protocol computed tomography offering a complementary role. While some imaging features have high specificity for a particular diagnosis, overlapping imaging features between diagnoses may require further investigation with follow-up diagnostic imaging or tissue sampling.

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.

Multimodel magnetic resonance imaging of mass-forming autoimmune pancreatitis: differential diagnosis with pancreatic ductal adenocarcinoma

PURPOSE

To assess the value of the multimodel magnetic resonance imaging (MRI), including unenhanced images, dynamic contrast-enhanced MRI (DCE-MRI), MR-cholangiopancreatography (MRCP), and diffusion-weighted imaging (DWI), in differentiation of mass-forming autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).

METHODS

Twelve patients with mass-forming AIP and 30 with PDAC were included. All patients underwent unenhanced MRI, DCE-MRI, DWI, and MRCP. Relevant values including sensitivity and specificity of the imaging features and their diagnostic performance for predicting mass-forming AIP were analyzed.

RESULTS

Several statistically significant MR findings and quantitative indexes differentiating mass-forming AIP from PDAC, including multiplicity, irregularity or conformation, capsule-like rim enhancement, absence of internal cystic or necrotic portion, homogeneous enhancement during pancreatic, venous, and delayed phases, skipped stricture or stricture of MPD, absence of side branch dilation, maximum upstream MPD diameter < 2.4 mm, ContrastUP > 0.739, ContrastAP > 0.710, ContrastPP > 0.879, and ContrastVP or ContrastDP > 0.949, indicated mass-forming AIP (P < 0.05). The apparent diffusion coefficient (ADC) value was also significantly lower in mass-forming AIP compared to that in PDAC (P = 0.006). The cutoff value of ADC for distinguishing mass-forming AIP from PDAC was 1.099 × 10-3 mm2/s.

CONCLUSION

Multimodel MRI, including unenhanced MRI, DCE-MRI with DWI and MRCP can provide qualitative and quantitative information about mass-forming AIP characterization. Multimodel MRI are valuable for differentiating mass-forming AIP from PDAC.

Imaging of Pancreatic Neuroendocrine Neoplasms

Pancreatic neuroendocrine neoplasms (panNENs) represent the second most common pancreatic tumors. They are a heterogeneous group of neoplasms with varying clinical expression and biological behavior, from indolent to aggressive ones. PanNENs can be functioning or non-functioning in accordance with their ability or not to produce metabolically active hormones. They are histopathologically classified according to the 2017 World Health Organization (WHO) classification system. Although the final diagnosis of neuroendocrine tumor relies on histologic examination of biopsy or surgical specimens, both morphologic and functional imaging are crucial for patient care. Morphologic imaging with ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) is used for initial evaluation and staging of disease, as well as surveillance and therapy monitoring. Functional imaging techniques with somatostatin receptor scintigraphy (SRS) and positron emission tomography (PET) are used for functional and metabolic assessment that is helpful for therapy management and post-therapeutic re-staging. This article reviews the morphological and functional imaging modalities now available and the imaging features of panNENs. Finally, future imaging challenges, such as radiomics analysis, are illustrated.

Imaging neuroendocrine tumors: Characterizing the spectrum of radiographic findings

Neuroendocrine tumors (NET) are a group of neoplasms with neuroendocrine differentiation affecting a wide range of organs. Functional NETs present with symptoms due to the particular hormone produced. Functional NETs are usually small at diagnosis and therefore can be challenging to diagnose. In contrast, non-functioning NETs are generally larger and present with mass effect. Imaging plays an indispensable role in diagnosis, staging and management of patients with NETs. The optimal modality and technique for imaging of NETs depend on the location of primary and metastatic lesions. Regardless of the imaging modality, dynamic contrast-enhanced imaging is essential for evaluation of NETs. In general, CT scan is typically the primary imaging modality for evaluating NETs. MRI is used as a complementary modality, being superior to other modalities to assess liver metastasis. Nuclear medicine imaging is also widely used in NET assessment.

Pearls and pitfalls of imaging features of pancreatic cystic lesions: a case-based approach with imaging-pathologic correlation

A variety of neoplastic and non-neoplastic lesions of the pancreas can present with a predominantly cystic architecture. These lesions are increasingly being detected as incidental findings on routine cross-sectional imaging following technological advances in these techniques and their widespread use. The different histopathological behaviors show various common and uncommon imaging findings, and some cases show similar appearance in spite of different histopathology. Each lesion requires specific management because of the differing risk of progression to malignancy, and an accurate imaging diagnosis is crucial. The typical imaging characteristics that differentiate pancreatic cystic lesions have been well described and fully summarized. However, in addition to a small percentage of cases that shows uncommon imaging findings, a substantial percentage of cystic lesions shows overlapping imaging findings that can lead to radiological misdiagnosis. For appropriate diagnosis and optimal treatment strategy, it is important to know the uncommon and overlapping imaging findings of these lesions, in addition to familiarity with the typical aspects. In this article, we reconfirm the well-known characteristic imaging features of pancreatic cystic lesions and present several diagnostically challenging cases, focusing on the uncommon and overlapping imaging findings.

MRI of mucinous pancreatic cystic lesions: a new updated morphological approach for the differential diagnosis

Pancreatic cystic lesions (PCLs) have been increasingly identified over the past 2 decades due to the widespread use of high-resolution non-invasive abdominal imaging. They cover a vast spectrum, from benign to malignant and invasive lesions, thus they constitute a significant clinical entity. Among PCLs, mucin-producing lesions are those at risk of progression to malignancy. They include mucinous cystic neoplasms (MCN) and intraductal papillary mucinous neoplasms (IPMN). The diagnosis and management of these cystic lesions are a dilemma since there is a significant overlap in the morphology of benign and premalignant lesions. At the moment, there is no single test that will allow a correct diagnosis in all cases. Magnetic resonance (MR) and endoscopic ultrasound (EUS) morphology, with cyst fluid analysis and cytohistology done with EUS-guided procedure are the best techniques that can narrow the differential diagnosis and identify potentially malignant lesions requiring resection from those requiring follow-up only. The purpose of this paper is to present an updated review of MR imaging findings of mucinous PCLs and to provide a new morphological approach that can serve as a practical guide for the diagnosis of these lesions, allowing a more confident characterization and avoiding relevant misdiagnosis. Furthermore, we provide some information about EUS and cystic fluid analysis and cytohistology, since they are diagnostic modalities that radiologists and surgeons should be familiar with.

Two-dimensional Texture Analysis Based on CT Images to Differentiate Pancreatic Lymphoma and Pancreatic Adenocarcinoma: A Preliminary Study

OBJECTIVE

To retrospectively assess the diagnostic performance of texture analysis and characteristics of CT images for the discrimination of pancreatic lymphoma (PL) from pancreatic adenocarcinoma (PA).

METHODS

Fifteen patients with pathologically proved PL were compared with 30 age-matched controls with PA in a 1:2 ratio. Patients underwent a CT scan with three phases including the precontrast phase, the arterial phase, and the portal vein phase. The regions of interest of PA and PL were drawn and analyzed to derive texture parameters with MaZda software. Texture features and CT characteristics were selected for the discrimination of PA and PL by the least absolute shrinkage and selection operator and logistic regression analysis. Receiver operating characteristic analysis was performed to assess the diagnostic performance of texture analysis and characteristics of CT images.

RESULTS

Sixty texture features were obtained by MaZda. Of these, four texture features were selected by least absolute shrinkage and selection operator. Following this, three texture features and nine CT characteristics were excluded by logistic regression analysis. Finally, "S(5, -5)SumAverg" (texture feature) and "Size" (CT characteristic) were selected for the receiver operating characteristic analysis. The AUC of "S(5, -5)SumAverg" and "Size" were to be 0.704 and 0.821, respectively, with no significance between them (p = 0.3064).

CONCLUSION

Two-dimensional texture analysis is a quantitative method for differential diagnosis of PL from PA. The diagnostic performance of both texture analysis and CT characteristics was similar.

Imaging presentation of pancreatic neuroendocrine neoplasms

Abstract

Pancreatic neuroendocrine neoplasms (P-NENs) are the second most common solid pancreatic neoplasms. P-NENs have a wide range of imaging features presentations and they can be detected with typical and atypical imaging presentations. Typical and atypical appearances can be explained by pathologic correlations. P-NENs are generally hypervascular lesions, showing a typical enhancement behavior after contrast media injection during imaging methods, but they could also have different imaging features, creating some difficulty in differential diagnosis. For this reason, radiologists should be aware of different imaging presentations of these neoplasms. Radiological evaluation has a critical role in P-NENs identification, characterization, and staging of these neoplasms, especially in those cases in which surgery is the treatment of choice. The present paper shows, indicating the underlying pathologic correlations, typical and atypical presentations of NENs.

Key Points

• P-NENs have a wide range of imaging features presentations, typical and atypical.

• Pathology could help in better understanding the typical P-NENs appearance at imaging.

• P-NENs are generally hypervascular lesions.

• Radiological evaluation has a critical role in P-NENs identification and management.

• Radiologists should know every type of different imaging presentation of P-NENs to better diagnose these kinds of lesions.

Radiological Workup of Cystic Neoplasms of the Pancreas

Pancreatic cystic lesions are being detected with increasing frequency because of increased use and improved quality of cross-sectional imaging techniques. Pancreatic cystic lesions encompass non-neoplastic lesions (such as pancreatitis-related collections) and neoplastic tumors. Common cystic pancreatic neoplasms include serous cystadenomas, mucinous cystic neoplasms, intraductal papillary mucinous neoplasms, and solid pseudopapillary tumors. These cystic pancreatic neoplasms may have typical morphology, but at times show overlapping imaging features on cross-sectional examinations. This article reviews the classical and atypical imaging features of commonly encountered cystic pancreatic neoplasms and presents the limitations of current cross-sectional imaging techniques in accurately classifying pancreatic cystic lesions.

Imaging and Screening of Pancreatic Cancer

Given the low disease prevalence of both exocrine and endocrine cancers in the general population, screening is not recommended. However, in as many as 25% of cases there is a precursor lesion or an identifiable genetic predisposition. For these patients at increased risk, screening with imaging is recommended. Multidetector computed tomography, MR imaging or magnetic resonance cholangiopancreatography, and endoscopic ultrasound examination can be used as screening modalities. Recent advances in dual energy CT and total body MR imaging have increased the suitability of these noninvasive modalities as first-line imaging screening options.

Enhancing pancreatic mass with normal serum CA19-9: key MDCT features to characterize pancreatic neuroendocrine tumours from its mimics

OBJECTIVES

To determine key MDCT features for characterizing pancreatic neuroendocrine tumours (PNET) from their mimics, which manifest as enhancing pancreatic mass with normal serum CA19-9 level.

METHODS

This retrospective study had institutional review board approval and informed consent was waived. Preoperative multiphase MDCT of 74 patients with enhancing pancreatic masses and normal serum CA19-9 levels were included. Surgical pathologies were PNET (n = 42), microcystic serous cystadenomas (m-SCN, n = 12) and solid pseudopapillary epithelial neoplasms (SPEN, n = 20). Two radiologists independently evaluated CT images with a checklist of findings. Frequencies of findings with each disease entity were compared. Diagnostic accuracy was assessed using the key MDCT features alone and in combination. Inter-observer agreement was evaluated.

RESULTS

The most common findings for PNET were mosaic morphological pattern (33/42, 78.6%) and enhancement peak in pancreatic arterial phase (PAP, 32/42, 76.2%), for m-SCN were honeycomb pattern (9/12, 75.0%) and enhancement peak in PAP (10/12, 83.3%) and for SPEN were melting icecream pattern (16/20, 80.0%) and hypo-enhancement in all phases (18/20, 90.0). Using a combination of morphological patterns and enhancement features, PNET was identified with 88% sensitivity and 81% specificity, m-SCN was identified with 83% sensitivity and 94% specificity, and SPEN was identified with 90% sensitivity and 91% specificity. Inter-observer agreement concerning CT findings was good to excellent (κ = 0.68 to 0.81, all p < 0.01).

CONCLUSIONS

Morphological features and enhancement patterns on MDCT are key features for characterizing enhancing pancreatic mass with normal serum CA19-9. PNET could be differentiated from its mimics with high accuracy.

Morphological differentiation and follow-up of pancreatic cystic neoplasms using endoscopic ultrasound

Endoscopic ultrasound (EUS) is a key modality for the evaluation of suspected pancreatic cystic neoplasms (PCNs), as the entire pancreatic gland can be demonstrated with high spatial resolution from the stomach and duodenum. Detailed information can be acquired about the internal contents of the cyst(s) [septum, capsule, mural nodules (MNs)], its relation with the main pancreatic duct (MPD), and any parenchymal changes in the underlying gland. PCNs comprise true cysts and pseudocysts. True cysts can be neoplastic or nonneoplastic. Here, we describe serous cystic neoplasm (SCN), mucinous cystic neoplasm (MCN), and intraductal papillary mucinous neoplasm (IPMN) as prototype neoplastic cysts, along with nonneoplastic lymphoepithelial cysts (LECs).