Advances in the cytologic diagnosis of gastroenteropancreatic neuroendocrine neoplasms

Tumour Heterogeneity and the Consequent Practical Challenges in the Management of Gastroenteropancreatic Neuroendocrine Neoplasms

Tumour heterogeneity is a common phenomenon in neuroendocrine neoplasms (NENs) and a significant cause of treatment failure and disease progression. Genetic and epigenetic instability, along with proliferation of cancer stem cells and alterations in the tumour microenvironment, manifest as intra-tumoural variability in tumour biology in primary tumours and metastases. This may change over time, especially under selective pressure during treatment. The gastroenteropancreatic (GEP) tract is the most common site for NENs, and their diagnosis and treatment depends on the specific characteristics of the disease, in particular proliferation activity, expression of somatostatin receptors and grading. Somatostatin receptor expression has a major role in the diagnosis and treatment of GEP-NENs, while Ki-67 is also a valuable prognostic marker. Intra- and inter-tumour heterogeneity in GEP-NENS, however, may lead to inaccurate assessment of the disease and affect the reliability of the available diagnostic, prognostic and predictive tests. In this review, we summarise the current available evidence of the impact of tumour heterogeneity on tumour diagnosis and treatment of GEP-NENs. Understanding and accurately measuring tumour heterogeneity could better inform clinical decision making in NENs.

Cytology as the guiding light: Prompt cytomorphologic diagnosis of cystic metastases from a jejunal neuroendocrine tumor masquerading as hepatic abscesses

Hepatic cystic lesions are commonly seen in radiology and can occur due to infective or neoplastic causes. It is imperative to determine the precise nature of these hepatic cysts owing to significant therapeutic and prognostic differences. Hepatic metastases from gastrointestinal neuroendocrine tumors (NETs) mostly present as solid hypervascular lesions. Cystic presentation of the metastatic NETs is extremely rare. A 64-year-old woman presented with an abdominal lump of 3 months duration and high-grade fever from the last 2 days. An ultrasound abdomen revealed multiple hypoechoic liver lesions suggestive of liver abscesses. An ultrasound-guided fine-needle aspiration (FNA) from the cystic liver lesions revealed a NET confirmed by immunocytochemistry. The Ki-67 index was 5%; hence, a final diagnosis of metastatic NET, grade 2, was given with advice to work up for localizing the primary tumor. Subsequently, a contrast-enhanced computerized tomography of the abdomen revealed a polypoidal lesion in the proximal jejunum, which showed intense expression on the whole-body DOTANOC scan (SUVmax-76.5), indicating it to be the likely primary tumor along with somatostatin receptor-expressing multiple lymph nodes and hypodense liver lesions. Thus, a final diagnosis of a jejunal NET with abdominal lymph node and liver metastases was made. The present report highlights the importance of FNA as a reliable modality in diagnosing metastatic NETs presenting as unusual cystic hepatic metastases masquerading as liver abscesses. Additionally, the cell block helps confirm the cytologic diagnosis and enables upfront tumor grading, thereby helping in prognostication and therapeutic decision-making.

Cystic hepatic metastases in treatment naïve neuroendocrine tumor: Cytomorphology clubbed with cell block immunocytochemistry clinches the diagnosis

Cystic hepatic lesions encompass a vast spectrum of infectious, non-neoplastic, and neoplastic entities. Most hepatic cysts are benign and asymptomatic, requiring no active intervention. However, symptomatic and malignant cysts need proper evaluation and specific treatment. An accurate preoperative diagnosis is pivotal for patient management. At times, these lesions may mimic, especially symptomatology and radiology, leading to a diagnostic ordeal. We herein present a case of a patient with cystic liver lesions in a treatment naïve neuroendocrine tumor that was a diagnostic dilemma on radiology. Low cellularity of cytology smears made the diagnosis challenging, and cell block immunocytochemistry finally clinched the diagnosis. A timely diagnosis provided on cytology fuelled further work-up, the discovery of primary tumor, and initiation of appropriate therapy.

Pancreatic Neuroendocrine Neoplasms: Updates on Genomic Changes in Inherited Tumour Syndromes and Sporadic Tumours Based on WHO Classification

Pancreatic neuroendocrine neoplasms (PanNENs) are the neuroendocrine neoplasms with greatest rate of increase in incidence. Approximately 10% of PanNENs arise as inherited tumour syndromes which include multiple endocrine neoplasia type 1, multiple endocrine neoplasia type 4, von Hippel-Lindau syndrome, neurofibromatosis type1, tuberous sclerosis complex 1/2, Cowden syndrome, and Glucagon cell hyperplasia and neoplasia as well as familial insulinomatosis. In sporadic PanNENs, driver mutations in MEN1, DAXX/ATRX and mTOR pathway genes are associated with development and progression in pancreatic neuroendocrine tumours. The other changes are in VEGF pathway, Notch pathway, germline mutations in MUTYH, CHEK2, BRCA2, PHLDA3 as well as other genetic alterations. On the other hand, pancreatic neuroendocrine carcinomas share similar genetic alterations with ductal adenocarcinomas, e.g., TP53, RB1 or KRAS. In addition, microRNA and changes in immune microenvironment were noted in PanNENs. Updates on these genetic knowledges contribute to the development of management strategies for patients with PanNENs.

Nomogram for preoperative estimation of histologic grade in gastrointestinal neuroendocrine tumors

BACKGROUND

The treatment strategies and prognosis for gastroenteropancreatic neuroendocrine tumors were associated with tumor grade. Preoperative predictive grading could be of great benefit in the selection of treatment options for patients. However, there is still a lack of effective non-invasive strategies to detect gastrointestinal neuroendocrine tumors (GI-NETs) grading preoperatively.

METHODS

The data on 147 consecutive GI-NETs patients was retrospectively collected from January 1, 2012, to December 31, 2019. Logistic regression was used to construct a predictive model of gastrointestinal neuroendocrine tumor grading using preoperative laboratory and imaging parameters.The validity of the model was assessed by area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).

RESULTS

The factors associated with GI-NETs grading were age, tumor size, lymph nodes, neuron-specific enolase (NSE), hemoglobin (HGB) and sex, and two models were constructed by logistic regression for prediction. Combining these 6 factors, the nomogram was constructed for model 1 to distinguish between G3 and G1/2, achieving a good AUC of 0.921 (95% CI: 0.884-0.965), and the sensitivity, specificity, accuracy were 0.9167, 0.8256, 0.8630, respectively. The model 2 was to distinguish between G1 and G2/3, and the variables were age, tumor size, lymph nodes, NSE, with an AUC of 0.847 (95% CI: 0.799-0.915), and the sensitivity, specificity, accuracy were 0.7882, 0.8710, 0.8231, respectively. Two online web servers were established on the basis of the proposed nomogram to facilitate clinical use. Both models showed an excellent calibration curve through 1000 times bootstrapped dataset and the clinical usefulness were confirmed using decision curve analysis.

CONCLUSION

The model served as a valuable non-invasive tool for differentiating between different grades of GI-NETs, personalizing the calculation which can lead to a rational treatment choice.

Differentiation between non-hypervascular pancreatic neuroendocrine tumors and mass-forming pancreatitis using contrast-enhanced computed tomography

BACKGROUND

Non-hypervascular pancreatic neuroendocrine tumors (PNETs) showed slight or iso-enhancement in contrast-enhanced computed tomography (CE-CT), which shared similar imaging findings with mass-forming pancreatitis (MFPs).

PURPOSE

To explore the value of CT imaging features in differentiating the two diseases.

MATERIAL AND METHODS

Fifty-one patients with histologically proved MFPs (n = 27) or non-hypervascular PNETs (n = 24) were included. Two radiologists reviewed CT imaging findings and clinical features. Logistic regression analysis was performed to identify relevant features in differentiating non-hypervascular PNETs and MFPs. Receiver operating characteristic (ROC) curve analysis was used to show the performance of the optimal parameters in differentiating non-hypervascular PNETs and MFPs.

RESULTS

A well-defined margin was more common in non-hypervascular PNETs (P < 0.05) than that in MFPs. MFPs often occurred in older people (P < 0.01) and the head-neck of the pancreas compared with non-hypervascular PNETs (P < 0.05). Metastases only presented in non-hypervascular PNETs (P < 0.05). CT values at venous phase and delay phase of MFPs were higher (P = 0.010 and P = 0.029) than those in non-hypervascular PNETs. Logistic analysis showed gender, tumor margin, CT values at venous phase, and tumor components were independent predictors in differentiating the two lesions. The area under the curve (AUC) was 0.938 with a sensitivity of 87.5% and specificity of 92.6% for combined predicators.

CONCLUSION

Gender, tumor margin, CT values at venous phase, and tumor components were useful predicators in differentiating non-hypervascular PNETs and MFPs.

Ki-67 proliferation index in neuroendocrine tumors: Can augmented reality microscopy with image analysis improve scoring?

BACKGROUND

The Ki-67 index is important for grading neuroendocrine tumors (NETs) in cytology. However, different counting methods exist. Recently, augmented reality microscopy (ARM) has enabled real-time image analysis using glass slides. The objective of the current study was to compare different traditional Ki-67 scoring methods in cell block material with newer methods such as ARM.

METHODS

Ki-67 immunostained slides from 50 NETs of varying grades were retrieved (39 from the pancreas and 11 metastases). Methods with which to quantify the Ki-67 index in up to 3 hot spots included: 1) "eyeball" estimation (EE); 2) printed image manual counting (PIMC); 3) ARM with live image analysis; and 4) image analysis using whole-slide images (WSI) (field of view [FOV] and the entire slide).

RESULTS

The Ki-67 index obtained using the different methods varied. The pairwise kappa results varied from no agreement for image analysis using digital image analysis WSI (FOV) and histology to near-perfect agreement for ARM and PIMC. Using surgical pathology as the gold standard, the EE method was found to have the highest concordance rate (84.2%), followed by WSI analysis of the entire slide (73.7%) and then both the ARM and PIMC methods (63.2% for both). The PIMC method was the most time-consuming whereas image analysis using WSI (FOV) was the fastest method followed by ARM.

CONCLUSIONS

The Ki-67 index for NETs in cell block material varied by the method used for scoring, which may affect grade. PIMC was the most time-consuming method, and EE had the highest concordance rate. Although real-time automated counting using image analysis demonstrated inaccuracies, ARM streamlined and hastened the task of Ki-67 quantification in NETs.

Fibrous Extracellular Spheroids in an Endoscopic Ultrasound-Guided Pancreatic Fine Needle Aspiration Correlating to a Gyriform Pancreatic Endocrine Tumor with a Unique Cobblestone Pavement Growth Pattern

Pancreatic neuroendocrine neoplasms (PanNENs) are uncommon tumors. Fine needle aspiration (FNA) samples from PanNENs are typically of high cellularity and lack necrosis. In cytology slides from these tumors, dyscohesive cells are usually reported with variably round to oval to plasmacytoid forms exhibiting coarsely granular chromatin and showing immunoreactivity for synaptophysin. We present an unusual, and to our knowledge not previously described, example of an FNA of a PanNEN with large extracellular fibrous spheroids containing intrinsic fibroblasts and rimmed by small to intermediate sized neoplastic epithelial cells with high nuclear cytoplasmic ratios. The cytomorphology of the PanNEN in this case was in some ways reminiscent of that expected in adenoid cystic carcinomas of the salivary glands that most often contain large extracellular globules of basement membrane material and a somewhat biphasic population of lesional cells. The cytomorphology in this case was found to correlate well with the resection specimen histomorphology of an exaggerated gyriform pattern of growth resulting in a unique cobblestone-pavement like microscopic appearance. Knowledge of this potential cytomorphology will aid the cytology community through recognition and reporting of this previously undescribed pattern in an uncommon disease.