Neuroendocrine Tumor Grade Research Articles

Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma

PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC). Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared. ResultsThirty-seven patients (21 men, 16 women; mean age, 56±13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60±46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70±51 [SD] mm [range: 18 - 196mm] vs. 42±24 [SD] mm [range: 8 - 94mm], respectively; P=0.039), with more tumor necrosis (75% vs. 33%, respectively; P=0.030) and lower attenuation on precontrast (30±4 [SD] HU [range: 25-39 HU] vs. 37±6 [SD] [range: 25-45 HU], respectively; P=0.002) and on portal venous phase CT images (75±18 [SD] HU [range: 43 - 108 HU] vs. 92±19 [SD] HU [range: 46 - 117 HU], respectively; P=0.014). Hemorrhagic content on MRI was only observed in NEC (P=0.007). The mean ADC value was lower in NEC ([1.1±0.1 (SD)]×10−3 mm2/s [range: (0.91 - 1.3)×10−3 mm2/s] vs. [1.4±0.2 (SD)]×10−3 mm2/s [range: (1.1 - 1.6)×10−3 mm2/s]; P=0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7±0.2 [SD] [range: 4.2-5.1] vs. 4.5±0.4 [SD] [range: 3.7-4.9]; P=0.023). ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI.

Improving the accuracy of gastrointestinal neuroendocrine tumor grading with\xa0deep learning

The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue single-immunostained (SS) for Ki-67 and counting the number of Ki-67-positive and Ki-67-negative tumor cells within a subjectively picked hot-spot. Intraobserver variability in this procedure as well as difficulty in distinguishing tumor from non-tumor cells can lead to inaccurate Ki-67 indices and possibly incorrect tumor grades. We introduce two computational tools that utilize Ki-67 and synaptophysin double-immunostained (DS) slides to improve the accuracy of Ki-67 index quantitation in GI-NETs: (1) Synaptophysin-KI-Estimator (SKIE), a pipeline automating Ki-67 index quantitation via whole-slide image (WSI) analysis and (2) deep-SKIE, a deep learner-based approach where a Ki-67 index heatmap is generated throughout the tumor. Ki-67 indices for 50 GI-NETs were quantitated using SKIE and compared with DS slide assessments by three pathologists using a microscope and a fourth pathologist via manually ticking off each cell, the latter of which was deemed the gold standard (GS). Compared to the GS, SKIE achieved a grading accuracy of 90% and substantial agreement (linear-weighted Cohen’s kappa 0.62). Using DS WSIs, deep-SKIE displayed a training, validation, and testing accuracy of 98.4%, 90.9%, and 91.0%, respectively, significantly higher than using SS WSIs. Since DS slides are not standard clinical practice, we also integrated a cycle generative adversarial network into our pipeline to transform SS into DS WSIs. The proposed methods can improve accuracy and potentially save a significant amount of time if implemented into clinical practice.

The Efficacy of 17 Cases of Pancreaticoduodenectomy Combined with Vascular Resection and Reconstruction by Using Robotic Operation System (with Video)

To explore the clinical efficacy of pancreaticoduodenectomy (PD) combined with vascular resection and reconstruction under robotic surgery system in the treatment of borderline resectable pancreatic cancer. The clinical data of 17 patients with borderline resectable pancreatic cancer who underwent PD combined with vascular resection and reconstruction (see the Video 1 in Supplemental Contents, http://ykxb.scu.edu.cn/article/doi/10.12182/20200760202) under robotic surgery system between August 2011 and September 2018 was analyzed retrospectively. There were 4 cases required conversion because of serious tumor invasion and soft pancreas texture, the other 13 cases were successfully completed. 16 cases (94%) achieved margin-negative resection (R0 resection), 14 cases combined with vein resection, and 3 cases combined with arterial resection. The mean operation time was (401±170) min, the mean blood loss was (647±345) mL, the mean postoperative length of hospital stay was (20±8) d. There was no perioperative death. Postoperative pathology findings and follow-up outcomes were as follows: 1 patient was diagnosed as intraductal papillary mucinous neoplasm (IPMN) and 1 patient was diagnosed as pancreatic neuroendocrine tumors (PNET) (Grade 1), 8 patients with pancreatic ductal adenocarcinoma (PDAC). 1 patient with pancreatic neuroendocrine carcinoma (PNEC) died because of tumor recurrence and metastasis during the follow-up period, the median (Min-Max) survival time was 12 (8-26) months. 5 patients with PDAC and 1 patient with malignant IPMN were currently in the follow-up period. It is safe and feasible to perform RPD with vascular resection and reconstruction. The patient's condition should be fully evaluated before surgery to select the most appropriate treatment.

PD-12 Clinical, pathological and molecular profiles of G3 neuroendocrine tumors and neuroendocrine carcinomas

In 2019, WHO subclassified grade 3 (G3) gastroenteropancreatic (GEP) neuroendocrine neoplasms (NEN) into neuroendocrine carcinoma (NEC) or tumors (G3 NET). Yet, few data exist on clinical and molecular profiles for G3 NEN. We aimed to compare the clinicopathological and molecular characteristics of G3 GEP NET and GEP NEC. We retrospectively collected data of all G3 GEP NEN patients (pts) diagnosed and treated at our cancer center from 2000 to 2019. Cases with available tumor tissues were reviewed and reclassified according to the WHO 2019 classification. Formalin-fixed, paraffin-embedded NEN tissues had DNA extracted for genomic profiling through next-generation sequencing (NGS), which evaluated mutations profiles, tumor mutation burden (TMB) and the presence of microsatellite instability. Survival from treatment start was the primary endpoint. Seventy-seven pts were included: median age at the diagnosis was 56 (26-91) years and 62% (48/77) were males. The most common primary sites were gastric (27%, 21/77), pancreas (23%, 18/77) and unknown primary NEN (23%, 18/77). Metastatic disease was present in 69% at diagnosis and 91% developed metastasis. Out of 77, 43 (56%) had pathology revision: 29 cases were NEC (67%) and 14 were reclassified as G3 NET (33%), with a change in diagnosis of 23%. In a median follow-up of 44 months, median OS in non-pancreatic digestive G3 NET, pancreatic G3 NET, and GEP NEC were 23.7, 55.6 and 10.8 months, respectively (non-pancreatic G3 NET vs NEC, p=0.01). Median OS in G3 NET with ki67 > 55%, NEC 55% was 19, 25 and 8 months, respectively. In Cox regression multivariate analysis, only cell differentiation sustained as a risk of death (HR 3.14 NEC vs G3 NET; P = 0.025). NGS was performed in 42% (32/77) cases: 21 NEC and 11 G3 NET. Median tumour mutational burden was 5.67 (0 – 66.82) mutations per megabase among NEC and 4.52 (0 – 8.83) among G3 NET. Tumors were microsatellite unstable in 3 (14.3%) NEC cases but zero among G3 NET pts. The most commonly mutated genes in G3 NET were TP53 (N=3; 27.3%), CDKN2A (N=3; 27.3%) and KRAS (2/11, 18.2%) and TP53 (N=15; 71.4%), Rb1 (N=7; 33.3%), PTEN (N=6; 28.6%) and APC (N=4; 19%) among NEC. Non-pancreatic digestive G3 NET is associated with increased survival compared to NEC. Pathology revision is essential to estimate prognosis and consequently therapeutic plan, as some of G3 NET can be treated as G2 NET. While G3 GEP NEN generally harbours low TMB and fewer actionable mutations, 14% of NEC cases were microsatellite unstable and could benefit from immune checkpoint inhibitors.

Candidate protein biomarkers in pancreatic neuroendocrine neoplasms grade 3

Pancreatic neuroendocrine neoplasms (PanNENs) are rare tumours that compose 1–2% of all pancreatic tumours.Patients with metastatic grade 3 neoplasia are usually treated with chemotherapy but have a poor progression-free and overall survival. According to the WHO 2017 classification, they are divided into neuroendocrine tumours (NETs) G3 and neuroendocrine carcinomas (NECs). Despite the new classification, new diagnostic and prognostic biomarkers are needed to sub-categorise the patients and to help guide therapy decisions. Blood from 42 patients and 42 healthy controls were screened for the presence of 92 proteins with the Immuno-Oncology panel using the Proximity Extension Assay provided by Olink Biosciences. Immunohistochemical staining of FAS ligand (FASLG) was performed on 16 patient tumour specimens using a commercial antibody. Fifty-four out of 87 evaluable proteins differed significantly in concentration between blood from patients and blood from healthy controls. FASLG was the only protein for which the concentration in blood was significantly lower in patients compared to controls and the levels correlated negatively to Ki-67 index. Seven of 14 evaluable PanNEN G3 specimens showed FASLG immunoreactivity in the tumour cells while there was scattered immunoreactivity in immune cells. Positive FASLG immunoreactivity correlated to well-differentiated morphology.FASLG concentration in blood was significantly lower in patients with pancreatic NENs G3 compared to controls, and the expression in tumour tissue was variable. Furthermore, FASLG was negatively correlated to Ki-67 and was more frequently expressed in well-differentiated tumours. Taken together, these results may suggest a role of FASLG in PanNENs.

Endoscopic ultrasound-guided fine-needle aspiration for the diagnosis and grading of pancreatic neuroendocrine tumors: a retrospective analysis of 110 cases.

Data on the reliability of the Ki-67 index and grading calculations from endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) of pancreatic neuroendocrine tumors (PanNETs) are controversial. We aimed to assess the accuracy of these data compared with histology. Cytological analysis from EUS-FNA in patients with suspected PanNETs (n = 110) were compared with resection samples at a single institution. A minimum of 2000 cells were considered to be adequate for grading. Correlation and agreement between cytology and histology in grading and Ki-67 values, respectively, were investigated. Secondary outcomes included the diagnostic performance of EUS-FNA. EUS-FNA samples were adequate for PanNET diagnosis and PanNET grading in 98/110 (89.1 %) and 77/110 (70.0 %) patients, respectively; thus, 77 samples were adequate for comparing cytology vs. histology. There were 67 (62.0 %), 40 (36.4 %), and 1 (0.9 %) patients with a final diagnosis of G1, G2, and G3 tumors, respectively. EUS-FNA grading was concordant with surgical pathology in 81.8 % of patients; under- and overgrading occurred in 15.6 % and 2.6 %, respectively. The overall level of agreement for grading was moderate (Cohen's κ = 0.59, 95 % confidence interval [CI] 0.34 - 0.78). Spearman's rho for Ki-67 in tumors ≤ 20 mm and > 20 mm was strong and moderate, respectively (rho = 0.68, 95 %CI 0.47 - 0.83; rho = 0.59, 95 %CI 0.35 - 0.75). The Bland - Altman plot showed that the Ki-67 values were comparable and reproducible between the two measurements. Although they were not available for a significant number of patients, grading and Ki-67 values from cytology correlated with histology moderately to strongly.

HPG80 (Progastrin), a novel blood-based biomarker for detection of neuroendocrine neoplasms.

e15038 Background: Neuroendocrine neoplasms (NENs) are heterogeneous tumors which originate from various organs and are of variable aggressiveness based on grade and morphology. Current biomarkers for NENs lack sensitivity and specificity, especially for high-grade NENs (small and large cell neuroendocrine carcinomas). hPG80, progastrin, is a novel bio-marker which is easily measured in plasma using an ELISA test. Physiologically, hPG80, an 80 amino acid protein, is the precursor of the gastrointestinal hormone gastrin. It is synthetized by gastric antrum G cells, and then processed into gastrin by multiple enzymatic processes. In pathological conditions, the GAST gene, which encodes hPG80, was shown to be over-expressed in human solid tumors from various primary sites. hPG80 is unprocessed and released from the tumor cells and becomes detectable in the blood. This study is the first to explore hPG80 in NENs. Methods: hPG80 was quantified in the plasma from 31 NEN patients using DxPG80 technology (ECS-Progastrin, Switzerland). Additional 69 samples are currently undergoing analysis. Progastrin concentrations in 18-70 YO (n = 557) and 18-25 YO (n = 137) healthy blood donors were compared to 31 stage IV NENs patients. The study was IRB approved. Results: Current data are for 31 patients. Data on total 100 patients will be presented at ASCO 2020. Mean age of study cohort at the time of blood collection was 60.9 years. 21 patients had grade 1 and 2 well differentiated NET. 10 patients had high grade NEN (Small cell, large cell and poorly differentiated NEC). High grade sub cohort also included two well differentiated grade 3 NET patients. Mean hPG80 in NENs was 14.17 pM as compared to 2.04 pM and 0.99 pM in 18-70 and 18-25 YO control groups (p < 0.0001), respectively. Subgroup analysis of NENs revealed mean hPG80 of 24.61 pM in high-grade NENs (n = 10) vs 10.88 pM in G1/2 NETs (n = 21). Conclusions: This first-ever study of plasma hPG80 in NENs suggests hPG80 may be a diagnostic blood-based biomarker in both low and high-grade NENs and further study is warranted. A prospective trial is ongoing in high-grade NEN to evaluate its role in monitoring of disease (NCT03958045) and further studies in low-grade NETs are underway. This research was supported by Cancer Center Support Grant (CCSG) from the National Cancer Institute (P30 CA177558) and ECS Progastrin.

SAT-115 A Rare Case of Metastatic Insulinoma in a Patient with Huntington’s Disease

A 49-year-old female with past medical history of Huntington’s disease presents to the ED after being found unresponsive at her assisted-living facility. She was noted to be hypoglycemic with a glucose of 21 and responded to dextrose. For the past several months, patient had symptoms of dizziness, tremors. She has no history of diabetes, and only home medication is Zyprexa. Patient required D10 drip to maintain glucose levels. Given patient’s psychiatric history, there was concern for surreptitious use of diabetic medications. Labwork showed an insulin level of 163 and an elevated C-peptide of 7.0 consistent with endogenous insulin secretion. Patient underwent a 72-hour fasting protocol which revealed a glucose of 23, C-peptide of 4.1 and insulin of 101, undetectable beta-hydroxybutyrate levels and pro-insulin level of 782 which is consistent with a diagnosis of insulinoma. She was started on diazoxide, which diminishes insulin secretion, to treat the hypoglycemia. Patient underwent a pancreas CT protocol which showed multiple hypervascular hepatic masses up to 9 cm and one 4 cm mass in pancreatic tail concerning for metastasis. Pathology revealed metastatic well-differentiated neuroendocrine tumor grade 3. She was not a candidate for surgical resection of tumors and she was started on Octreotide 200 mcg TID. Patient underwent two Y90 radioembolization treatments, 2 months apart with improvement of hypoglycemia and discontinuation of diazoxide. Patient remains on Octreotide LAR injection every 4 weeks. Insulinoma, although rare, occurs in 1-4% of the population and is the most common type of functional neuroendocrine tumor of the pancreas. It secretes insulin which results in hyperinsulinemic hypoglycemia. Diagnosis involves persistent hypoglycemia with glucose <50 mg/dL, neuroglycopenic symptoms and prompt relief after glucose administration. Gold standard diagnosis is a 72-hour fast and measurement of plasma insulin, C-peptide and pro-insulin, which detects 99% of insulinomas. After lab confirmation, imaging is necessary with either CT, MRI or EUS. Surgical resection is curative in most patients. Other treatment modalities include injection of octreotide, EUS-aided alcohol ablation, radio-frequency ablation or embolization of insulinoma, as well as targeted therapy with everolimus or sunitinib. Malignant insulinomas are extremely rare and often invade into surrounding soft tissue or have lymph node or liver metastasis. They are usually unresectable and require targeted therapy. We present the case of a 49 YO patient with Huntington’s disease who presented with severe persistent hypoglycemia secondary to metastatic insulinoma. Diagnosis of insulinoma is often delayed or missed as symptoms may be attributed to psychiatric, cardiac or neurological disorders or medication misuse. Clinicians should be aware of insulinoma as a cause of life-threatening hypoglycemia.

Clinicopathological Study of 100 Cases of Neuroendocrine Neoplasms of the Gastroenteropancreatic System: A Tertiary Cancer Center Experience

Abstract Background: The incidence of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) is on the rise. Although the clinicopathologic characteristics of NENs have been previously reviewed in the literature, the data published in the Indian literature so far are sparse. This study aims to review the clinicopathological features of GEP-NENs, diagnosed at our institution, and that were classified and graded according to the World Health Organization 2010 classification system. Materials and Methods: One hundred patients with GEP-NENs presenting to our institute from August 2012 to May 2016 were analyzed retrospectively. Demographic data and tumor characteristics were expressed as number, percentage, and mean value. Tumor grade was correlated to metastasis through the Chi-square test. p &lt; 0.05 was considered statistically significant. Results: Of the 100 cases studied, 58 were male and 42 were female. The most common primary site was the pancreas (n = 36), followed by the small intestine (n = 19), esophagus (n = 17), stomach (n = 15), colon (n = 6), rectum (n = 4), and appendix (n = 3). The incidence of neuroendocrine tumor (NET) Grade 1 (NET G1) was higher (n = 40) compared to NET Grade 2 (NET G2) (n = 25) and neuroendocrine carcinoma Grade 3 (NEC G3) (n = 35). Overall in these 100 cases, NET G1 tumors and NET G2 tumors were most common in the pancreas (n = 18/36) and (n = 13/36), respectively. NEC G3 tumors were most common in the esophagus (n = 16/17). The most common site of distant metastasis was the liver (n = 23/26). Conclusion: We elucidated the epidemiological and clinicopathological features of patients presenting to our institute with GEP-NENs.

Noncontrast Radiomics Approach for Predicting Grades of Nonfunctional Pancreatic Neuroendocrine Tumors.

Endoscopic ultrasound-guided fine-needle aspiration is associated with the accurate determination of tumor grade. However, because it is an invasive procedure there is a need to explore alternative noninvasive procedures. To develop and validate a noncontrast radiomics model for the preoperative prediction of nonfunctional pancreatic neuroendocrine tumor (NF-pNET) grade (G). Retrospective, single-center study. Patients with pathologically confirmed PNETs (139) were included. 3T/breath-hold single-shot fast-spin echo T2 -weighted sequence and unenhanced and dynamic contrast-enhanced T1 -weighted fat-suppressed sequences. Tumor features on contrast MR images were evaluated by three board-certified abdominal radiologists. Multivariable logistic regression analysis was used to develop the clinical model. The least absolute shrinkage and selection operator method and linear discriminative analysis (LDA) were used to select the features and to construct a radiomics model. The performance of the models was assessed using the training cohort (97 patients) and the validation cohort (42 patients), and decision curve analysis (DCA) was applied for clinical use. The clinical model included 14 imaging features, and the corresponding area under the curve (AUC) was 0.769 (95% confidence interval [CI], 0.675-0.863) in the training cohort and 0.729 (95% CI, 0.568-0.890) in the validation cohort. The LDA included 14 selected radiomics features that showed good discrimination-in the training cohort (AUC, 0.851; 95% CI, 0.758-0.916) and the validation cohort (AUC, 0.736; 95% CI, 0.518-0.874). In the decision curves, if the threshold probability was 0.17-0.84, using the radiomics score to distinguish NF-pNET G1 and G2/3, offered more benefit than did the use of a treat-all-patients or treat-none scheme. The developed radiomics model using noncontrast MRI could help differentiate G1 and G2/3 tumors, to make the clinical decision, and screen pNETs grade. 4 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1124-1136.

Dual-color immunocytochemistry (Ki-67 with LCA) for precise grading of pancreatic neuroendocrine tumors with applicability to small biopsies and cell blocks.

Ki-67 (MIB-1) immunostaining to quantify the proliferative index of neuroendocrine tumors (NETs) has been recommended (especially for small biopsies). However, this has a number of challenges with nonrepresentative Ki-67 index due to interference by Ki-67 immunoreactive proliferating lymphocytes infiltrating the tumor and also some proliferating stromal cells including endothelial cells in the background. Our pilot project showed that dual-color immunostaining with inclusion of leukocyte common antigen (LCA) (Ki-67: nuclear brown; LCA: cytoplasmic red) can facilitate the weeding out of lymphocyte interference. We analyzed the results with 23 surgical cases of pancreatic NETs. This was followed by poststudy examination of 11 cases of endoscopic ultrasound-guided fine-needle aspiration of the pancreatic NETs (PanNETs) to evaluate the findings of the study. Dual-color immunostaining for Ki-67 with LCA increased the precision of quantifying Ki-67 index, due to ability to exclude LCA immunoreactive lymphocytes. Other nontumor Ki-67 immunoreactive cells such as endothelial and stromal cells could be distinguished morphologically. Digital methods were also attempted, but this approach could not distinguish infiltrating lymphocytes and other cells in sections resulting in erroneous results. This study demonstrated that grading of PanNET can be performed with increased precision with dual-color Ki-67 immunostaining protocol standardized in this study. As evaluated on a few cytopathology cases, this protocol is especially useful for the evaluation of small biopsies and cell block sections of fine-needle aspiration biopsy material where 50 high-power fields cannot be evaluated but have >500 tumor cell nuclei.

Accuracy of Grading in Pancreatic Neuroendocrine Neoplasms and Effect on Survival Estimates: An Institutional Experience.

Accurate grading of neuroendocrine neoplasms (NENs) is crucial for proper assessment of prognosis. Estimation of the proliferative indices, if not performed properly, is largely erroneous due to significant intratumoral heterogeneity. We sought to establish the degree of error in the grading of a cohort of curatively resected pancreatic NENs (PanNENs) and the theoretical impact of that in a larger cohort of Surveillance, Epidemiology, and End Results (SEER) patients. A retrospective query of an institutional surgical database was performed from 2000 to 2018 to identify optimally resected PanNENs, which were reviewed by two gastrointestinal pathologists and regraded according to the WHO 2017 classification. Overall survival and recurrence-free survival were estimated using the Kaplan-Meier method for original and new grading systems, respectively and Cox proportional hazards models were used to evaluate the effect of the interested variables, including new grading systems. A total of 176 cases were identified. After regrading, 17/64 (26.6%) G1 neoplasms were classified as G2 and 12/95 (12.6%) G2 neoplasms were classified as G1, while 1/11 (9.1%) G3 neoplasms were classified as G2. Our expert gastrointestinal pathologists agreed on 97% of reclassified cases by blind review. Application of the G1/G2 misclassification errors on various groups, including PanNENs, in a SEER database of 1385 patients rendered the reported survival differences nonsignificant (1000 repetitions; p = 0.063, 95% confidence interval 0.056-0.070). Mischaracterization of grade is common in optimally resected PanNENs but is eliminated with proper training and adherence to guidelines. The discrepancy rates can cast doubt on the generally accepted survival differences between G1 and G2 patients, as surmised by large database analyses.

Can CT Histogram Analysis Predict the World Health Organization Grade of Rectal Neuroendocrine Tumors?

Background: It is essential to discriminate low-grade (G1), intermediate-grade (G2) and high-grade (G3) rectal neuroendocrine tumors (R-NETs) due to the treatment decisions and postoperative management are totally different. CT histogram analysis, which is a novel method to provide objectively quantified assessment of tumor, may be helpful for differentiating the grade of R-NETs. Methods: A total of 61 (35 G1, 12 G2 and 14 G3) patients who underwent preoperative contrast-enhanced CT and treated with surgery to be confirmed as R-NETs were included in this study from January 2014 and May 2019. We accurately depicted the region of interest (ROI) and measured the CT texture parameters (mean, median, 10th, 25th, 75th, 90th percentiles, skewness, kurtosis and entropy) from arterial phase image by two radiologists. We calculated and compared these parameters between low-grade (G1), intermediate-grade (G2) and high-grade (G3) tumors by applying appropriate statistical method. We obtained the optimal parameters to identify G1 and G2/G3 by using receiver operating characteristic (ROC) curves. Findings: Histogram analysis of CT arterial phase imaging demonstrated significant differences between G1 and G2 or G3 group in several histogram parameters (mean, median, 10th, 25th, 75th and 90th percentiles) (all P 0.05). Skewness, kurtosis and entropy showed no significant differences among three groups ( P =0.449, 0.285, 0.057, respectively). ROC analysis showed a good predictive performance between G1 and G2/G3 and the mean generated the highest area under the curve (AUC = 0.832), followed by the median (AUC = 0.827). Interpretation: CT histogram parameters, especially mean and median, can be used as excellent indicators for predicting the grade (G1 and G2/G3) of rectal neuroendocrine tumors. Funding Statement: This study has received funding by the National Natural Science Foundation of China (Grant No.81771801,81801695, 81701657 and 81873623). Declaration of Interests: The authors declare no conflict of interest. Ethics Approval Statement: The Institutional Review Board of our hospital (Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology) approved this retrospective study and the requirement for patient informed consent was waived.

CT-Radiomic Approach to Predict G1/2 Nonfunctional Pancreatic Neuroendocrine Tumor

Tumor grading of nonfunctional pancreatic neuroendocrine tumors (NF-pNETs) determines the choice of clinical treatment and management. The pathological grade of pancreatic neuroendocrine tumors is usually assessed on postoperative specimens. The goal of our study is to establish a tumor grade (G) prediction model for preoperative G1/2 NF-pNETs using radiomics for multislice spiral CT image analysis. This retrospective study included a primary cohort of 59 patients and an independent validation cohort of 40 consecutive patients; their multislice spiral CT images were collected from October 2012 to October 2016 and October 2016 to June 2018, respectively. All 99 patients were diagnosed with clinicopathologically confirmed NF-pNETs. Most significant radiomic features were selected using the minimum redundancy and maximum relevance algorithm. Support vector machine classifier with a radial basis function-based predictive model was subsequently developed for clinical use. A total of 585 radiomics features were extracted from every phase for each patient. Six of these radiomics features were identified as most discriminant features for G1 and G2 tumors and used to construct the tumor grade prediction model. The prediction model resulted in the area under the curve values of 0.968 (95% CI: 0.900-0.991) and 0.876 (95% CI: 0.700-0.963) for the training cohort and validation cohort, respectively. Sensitivity and specificity were 96.4% and 83.9%, and 90.9% and 88.9% for the training and validation cohorts, respectively. The decision curves indicated that if the threshold probability is above 0.1, using the rad-score in the current study on G1/2 NF-pNETs is more beneficial than the treat-all-patients scheme or the treat-none scheme. Radiomics developed with a combination of nonenhanced and portal venous phases can achieve favorable predictive accuracy for histological grade for G1/G2 NF-pNETs.

Efficacy of somatostatin analog (SSA) monotherapy for well-differentiated grade 3 (G3) gastroenteropancreatic neuroendocrine tumors (NETs).

617 Background: Currently, there is no published data on the efficacy of SSAs for well-differentiated G3 NETs. Randomized trials have demonstrated a progression-free survival (PFS) benefit and limited tumor response for lower grade 1-2 NETs, but the optimal systemic therapy for metastatic/unresectable G3 NETs is unknown. We sought to evaluate the efficacy of SSAs in G3 NETs. Methods: We performed a retrospective analysis of Mayo Clinic patients treated with SSAs for metastatic/unresectable G3 NETs, querying data from 1992 - present. Inclusion criteria were: centrally reviewed pathology confirming well-differentiated morphology, G3 based on WHO classification, SSA monotherapy, and radiological data available to assess response. Patients who had prior lines of treatment were included as long they subsequently were treated with single-agent SSA. Poorly-differentiated tumors were excluded. The primary endpoint was PFS. Best overall response was determined by radiographic regression, stabilization, or progression of tumor size. Results: Ninety patient records were reviewed, with 14 meeting inclusion criteria (diagnosed 2014 – 2018). Median Ki-67 proliferative index was 25%. Two patients (14%) had a partial response to SSA therapy, five (36%) had stable disease, and seven (50%) had progressive disease. The estimated median PFS was 4.4 months (95% CI 2.9 – 24). Of the 7 patients with stable disease or partial response, the median time to progression was 8.7 months. Three patients had stable disease for greater than 9 months (24, 29 and 42 months, respectively). Overall survival was not estimable. There was no association of Ki-67 index with PFS based on a proportional hazards model. Conclusions: This is the first report on the efficacy of SSAs for G3 NETs. Although half of the patients in our series had at least stable disease, the PFS was modest at only 4.4 months. Given their favorable side-effect profile compared to cytotoxic chemotherapy, SSAs may present an attractive option to be further explored in a prospective fashion. We are presently updating this data by reassessing response using RECIST criteria.

HPG80 (Progastrin), a novel blood-based biomarker for detection of neuroendocrine neoplasms.

628 Background: Neuroendocrine neoplasms (NENs) are heterogeneous tumors which originate from various organs and are of variable aggressiveness based on grade and morphology. Current biomarkers for NENs lack sensitivity and specificity, especially for high-grade NENs (small and large cell neuroendocrine carcinomas). hPG80, progastrin, is a novel bio-marker which is easily measured in plasma using an ELISA test. Physiologically, hPG80, an 80 amino acid protein, is the precursor of the gastrointestinal hormone gastrin. It is synthetized by gastric antrum G cells, and then processed into gastrin by multiple enzymatic processes. In pathological conditions, the GAST gene, which encodes hPG80, was shown to be over-expressed in human solid tumors from various primary sites. hPG80 is unprocessed and released from the tumor cells and becomes detectable in the blood. This study is the first to explore hPG80 in NENs. Methods: hPG80 was quantified in the plasma from 31 NEN patients using DxPG80 technology (ECS-Progastrin, Switzerland). Progastrin concentrations in 18-70 YO (n = 557) and 18-25 YO (n = 137) healthy blood donors were compared to 31 stage IV NENs patients. The study was IRB approved. Results: Mean age of study cohort at the time of blood collection was 60.9 years. 21 patients had grade 1 and 2 well differentiated NET. 10 patients had high grade NEN (Small cell, large cell and poorly differentiated NEC). High grade sub cohort also included two well differentiated grade 3 NET patients. Mean hPG80 in NENs was 14.17 pM as compared to 2.04 pM and 0.99 pM in 18-70 and 18-25 YO control groups (p &lt; 0.0001), respectively. Subgroup analysis of NENs revealed mean hPG80 of 24.61 pM in high-grade NENs (n = 10) vs 10.88 pM in G1/2 NETs (n = 21). Conclusions: This first-ever study of plasma hPG80 in NENs suggests hPG80 may be a diagnostic and/prognostic blood-based biomarker in both low and high-grade NENs and further study is warranted. A prospective trial is ongoing in high-grade NEN to evaluate its role in monitoring of disease (NCT03958045) and further studies in low-grade NETs are underway. This research was supported by Cancer Center Support Grant (CCSG) from the National Cancer Institute (P30 CA177558) and ECS Progastrin.

A rare case of pancreatic neuroendocrine tumor

Pancreatic neuroendocrine tumors (PNETs) are a group of endocrine neoplasms that exhibit neuroendocrine phenotypes. These include the production of neuropeptides, large dense-core secretory vesicles, and a lack of neural structures. They arise in the pancreas and are among the most common neuroendocrine tumors. A case of 38 years old female presented with a painless progressive swelling in the right upper abdomen since one month which is insidious in onset, gradually increasing in size with a history of significant weight loss and patient is not a known diabetic. On Examination, a swelling of size 5x7cm noted involving epigastric and right hypochondrium, which is not moving with respiration and dull on percussion. Plane of swelling is Intra-abdominal& retroperitoneal. Computed tomography abdomen (CECT) showed well defined rounded iso dense lesion showing heterogeneous enhancement in arterial and venous phase. Magnetic resonance cholangiopancreatography (MRCP) showed well defined lobulated heterogeneous solid lesion with central areas of necrosis seen in the pancreaticoduodenal groove (PDG) involving main pancreatic duct (MPD) and loss of fat planes with surrounding structures most likely malignant etiology. The patient underwent pancreaticoduodenectomy surgery (Whipple procedure) and had an uneventful recovery. Post-operative biopsy report confirmed pancreatic neuroendocrine tumor grade II (well-differentiated type), stage II a – pT3 N0 Mx.

The Prognostic Value of Circulating Tumor Cells in Asian Neuroendocrine Tumors

Circulating tumor cells (CTC) play important roles in various cancers; however, few studies have assessed their clinical utility in neuroendocrine tumors. This study aimed to prospectively evaluate the prognostic value of CTC counts in Asian patients with neuroendocrine tumors before and during anti-cancer therapy. Patients who were diagnosed with unresectable histological neuroendocrine tumors between September 2011 and September 2017 were enrolled. CTC testing was performed before and during anti-cancer therapy using a negative selection protocol. Chromogranin A levels were also assessed. Univariate and multivariate Cox’s proportional hazard model with forward LR model was performed to investigate the impact of independent factors on overall survival and progression-free survival. Kaplan–Meier method with log-rank tests were used to determine the difference among different clinicopathological signatures and CTC cutoff. The baseline CTC detection rate was 94.3% (33/35). CTC counts were associated with cancer stages (I-III vs. IV, P = 0.015), liver metastasis (P = 0.026), and neuroendocrine tumor grading (P = 0.03). The median progression-free survival and overall survivals were 12.3 and 30.4 months, respectively. In multivariate Cox regression model, neuroendocrine tumors grading and baseline CTC counts were both independent prognostic factors for progression-free survival (PFS, P = 0.005 and 0.015, respectively) and overall survival (OS, P = 0.018 and 0.023, respectively). In Kaplan-Meier analysis, lower baseline chromogranin A levels were associated with longer PFS (P = 0.024). Baseline CTC counts are associated with the clinicopathologic features of neuroendocrine tumors and are an independent prognostic factor for this malignancy.

Potential Pitfalls in Diagnostic Digital Image Analysis: Experience with Ki-67 and PHH3 in Gastrointestinal Neuroendocrine Tumors

Gastrointestinal neuroendocrine tumors, or GI-NETs are a highly diverse group of tumors derived from neuroendocrine cells of the GI tract. In GI-NET, a spectrum of histological and molecular parameters exists to predict prognosis and survival. Immunohistochemistry for Ki67, a nuclear antigen that is present in all but the G0 phase of the cell cycle with specificity for proliferating cells, can be used to determine a tumors proliferation index. With this in mind, grading of gastrointestinal neuroendocrine tumors is critical for prognosis and can impact clinical decision making. Recently, digital image analysis (DIA) has been shown in studies to be a superior and less time-consuming alternative to the manual scoring of Ki-67 in breast cancer, secondary to its theoretical diagnostic reproducibility. In DIA, the correct identification of tumor cells and non-tumor is paramount to avoid over or under calculation of biomarker expression. Additionally, DIA requires a pathologist to manually outline a tumor in large tissue areas of hematoxylin and eosin (H&E) sections, which is impractical. The findings in our study showed that ventana virtuoso software computer analyzed Ki-67 only correlated well with Neuroendocrine carcinomas while manual analysis of mitotic index and Ki67 were found to be gold standard. The performance of DIA in our study was plagued by software issues. In future, the advent of new digital imaging technologies such as virtual dual staining will hopefully improve diagnostic accuracy and reproducibility across different DIA platforms. Ultimately, determination of therapeutic strategies should be guided by an amalgamation of clinicopathologic characteristics not limited to mitotic index and Ki-67. As well, A visual check of the results should always be performed and correlated with other findings.

Well-differentiated grade 3 neuroendocrine tumors (G3NET) - single centre experience from the UK

Well-differentiated grade 3 neuroendocrine tumors (G3NET) - single centre experience from the UK