Surgery management for sporadic small (≤2 cm), non-functioning pancreatic neuroendocrine tumors: A consensus statement by the Chinese Study Group for Neuroendocrine Tumors (CSNET)

Prospective study on stereotactic body radiotherapy for small pancreatic neuroendocrine tumors: tolerance and effectiveness analysis

INTRODUCTION

Surgery is the standard treatment for pancreatic neuroendocrine tumors (pNETs), obtaining favorable results but associating high morbidity and mortality rates. This study assesses stereotactic body radiation therapy (SBRT) as a radical approach for small (< 2 cm) nonfunctioning pNETs.

MATERIALS AND METHODS

From January 2017 to June 2023, 20 patients with small pNETs underwent SBRT in an IRB-approved study. Endpoints included local control, tolerance, progression-free survival, and overall survival (OS). Diagnostic assessments comprised endoscopy, CT scans, OctreScan or PET-Dotatoc, abdominal MRI, and histological confirmatory samples.

RESULTS

In a 30-month follow-up of 20 patients (median age 55.5 years), SBRT was well-tolerated with no grade > 2 toxicity. 40% showed morphological response, 55% remained stable. Metabolically, 50% achieved significant improvement. With a median OS of 41.5 months, all patients were alive without local or distant progression or need for surgical resection.

CONCLUSION

SBRT is a feasible and well-tolerated approach for small neuroendocrine pancreatic tumors, demonstrating effective local control. Further investigations are vital for validation and extension of these findings.

Construction and validation of an endoscopic ultrasonography-based ultrasomics nomogram for differentiating pancreatic neuroendocrine tumors from pancreatic cancer

Objectives

To develop and validate various ultrasomics models based on endoscopic ultrasonography (EUS) for retrospective differentiating pancreatic neuroendocrine tumors (PNET) from pancreatic cancer.

Methods

A total of 231 patients, comprising 127 with pancreatic cancer and 104 with PNET, were retrospectively enrolled. These patients were randomly divided into either a training or test cohort at a ratio of 7:3. Ultrasomics features were extracted from conventional EUS images, focusing on delineating the region of interest (ROI) for pancreatic lesions. Subsequently, dimensionality reduction of the ultrasomics features was performed by applying the Mann-Whitney test and least absolute shrinkage and selection operator (LASSO) algorithm. Eight machine learning algorithms, namely logistic regression (LR), light gradient boosting machine (LightGBM), multilayer perceptron (MLP), random forest (RF), extra trees, k nearest neighbors (KNN), support vector machine (SVM), and extreme gradient boosting (XGBoost), were employed to train prediction models using nonzero coefficient features. The optimal ultrasomics model was determined using a ROC curve and utilized for subsequent analysis. Clinical-ultrasonic features were assessed using both univariate and multivariate logistic regression. An ultrasomics nomogram model, integrating both ultrasomics and clinical-ultrasonic features, was developed.

Results

A total of 107 EUS-based ultrasomics features were extracted, and 6 features with nonzero coefficients were ultimately retained. Among the eight ultrasomics models based on machine learning algorithms, the RF model exhibited superior performance with an AUC= 0.999 (95% CI 0.9977 - 1.0000) in the training cohort and an AUC= 0.649 (95% CI 0.5215 - 0.7760) in the test cohort. A clinical-ultrasonic model was established and evaluated, yielding an AUC of 0.999 (95% CI 0.9961 - 1.0000) in the training cohort and 0.847 (95% CI 0.7543 - 0.9391) in the test cohort. Subsequently, the ultrasomics nomogram demonstrated a significant improvement in prediction accuracy in the test cohort, as evidenced by an AUC of 0.884 (95% CI 0.8047 - 0.9635) and confirmed by the Delong test. The calibration curve and decision curve analysis (DCA) depicted this ultrasomics nomogram demonstrated superior accuracy. They also yielded the highest net benefit for clinical decision-making compared to alternative models.

Conclusions

A novel ultrasomics nomogram was proposed and validated, that integrated clinical-ultrasonic and ultrasomics features obtained through EUS, aiming to accurately and efficiently identify pancreatic cancer and PNET.

Clinical and CT Quantitative Features for Predicting Liver Metastases in Patients with Pancreatic Neuroendocrine Tumors: A Study with Prospective/External Validation

RATIONALE AND OBJECTIVES

We aimed to evaluate clinical characteristics and quantitative CT imaging features for the prediction of liver metastases (LMs) in patients with pancreatic neuroendocrine tumors (PNETs).

METHODS

Patients diagnosed with pathologically confirmed PNETs were included, 133 patients were in the training group, 22 patients in the prospective internal validation group, and 28 patients in the external validation group. Clinical information and quantitative features were collected. The independent variables for predicting LMs were confirmed through the implementation of univariate and multivariate logistic analyses. The diagnostic performance was evaluated by conducting receiver operating characteristic curves for predicting LMs in the training and validation groups.

RESULTS

PNETs with LMs demonstrated significantly larger diameter and lower arterial/portal tumor-parenchymal enhancement ratio, arterial/portal absolute enhancement value (AAE/PAE value) (p < 0.05). After multivariate analyses, A high level of tumor marker (odds ratio (OR): 5.32; 95% CI, 1.54-18.35), maximum diameter larger than 24.6 mm (OR: 7.46; 95% CI, 1.70-32.72), and AAE value ≤ 51 HU (OR: 4.99; 95% CI, 0.93-26.95) were independent positive predictors of LMs in patients with PNETs, with area under curve (AUC) of 0.852 (95%CI, 0.781-0.907). The AUCs for prospective internal and external validation groups were 0.883 (95% CI, 0.686-0.977) and 0.789 (95% CI, 0.602-0.916), respectively.

CONCLUSION

Tumor marker, maximum diameter and absolute enhancement value in arterial phase were independent predictors with good predictive performance for the prediction of LMs in patients with PNETs. Combining clinical and quantitative features may facilitate the attainment of good predictive precision in predicting LMs.

Recurrence and outcomes of non-functional pancreatic neuroendocrine tumours post-resection: an Australian retrospective, multicentre cohort study

INTRODUCTION

Pancreatic neuroendocrine tumours (PNETs) are heterogenous entities with variable clinical outlook. The prevalence of PNETs is increasing in Australia. Despite this, data on peri-operative management and post-operative prognosis for Australian patients is scant in the literature.

METHODS

Patients from two tertiary hospitals in Victoria were recruited. Inclusion criteria included patients who underwent curative surgical resection for primary, non-functioning, PNETs without metastases from January 2011 to December 2021. Patients were identified via histopathological reports, CMBS and ICD-10 codes. Data were sourced from Electronic Medical Records, outpatient notes and letters.

RESULTS

Sixty-three patients (34 Male, 29 Female) underwent surgical resection for PNETs. Fifty-three patients (84.1%) had a post-operative complication, and 21 (33.3%) had severe complications. Two patients had disease recurrence. Head PNETs had higher Ki-67% (5.33 vs. 2.72, P = 0.29), and likelihood of nodal spread (9 (36%) vs. 4 (16%), P = 0.054). Pancreatic Head resections were also associated with more frequent ICU admissions (21 (84%) vs. 18 (54.5), P = 0.024), longer ICU stays (4.05 vs. 2.17 days, P = 0.10) and hospital stays (26.76 vs. 8.27 days, P = <0.001).

CONCLUSION

Within the limitations of this study, it demonstrates that surgical resection of PNET carries a significant morbidity with a low rate of recurrence. Additionally, Pancreatic head NETs may be associated with higher grades and increased likelihood of nodal metastases. Considering this, careful patient selection is paramount.

Management of Small Nonfunctioning Pancreatic Neuroendocrine Neoplasms: Current Opinion and Controversies

The incidence of small and asymptomatic pancreatic neuroendocrine neoplasms (PNENs) has increased due to the widespread use of high-resolution diagnostic imaging in screening programs. Most PNENs are slow-growing indolent neoplasms. However, a local invasion or metastasis can sometimes occur with PNENs, leading to a poor prognosis. The management of small, nonfunctioning PNENs remains under debate. The National Comprehensive Cancer Network guidelines recommend observation in selected cases of small PNENs less than 2 cm. Pancreatic surgery remains a high-risk operation with a 28-30% morbidity and 1% mortality. Therefore, the decision on how to manage small PNENs is challenging. This review focuses on the management of small nonfunctioning PNENs. We also highlight the malignant potential of small PNENs according to tumor size, tumor grade, and tumor biomarker. Endoscopic-ultrasound-guided biopsy is recommended to evaluate the potential risk of malignancy. Furthermore, we discuss the current guidelines and future directions for the management of small PNENs.

Prediction of the characteristics of aggressiveness of pancreatic neuroendocrine neoplasms (PanNENs) based on CT radiomic features

OBJECTIVES

To predict tumor grade (G1 vs. G2/3), presence of distant metastasis (M+), metastatic lymph nodes (N+), and microvascular invasion (VI) of pancreatic neuroendocrine neoplasms (PanNEN) based on preoperative CT radiomic features (RFs), by applying a machine learning approach aimed to limit overfit.

METHODS

This retrospective study included 101 patients who underwent surgery for PanNEN; the entire population was split into training (n = 70) and validation cohort (n = 31). Based on a previously validated methodology, after tumor segmentation on contrast-enhanced CT, RFs were extracted from unenhanced CT images. In addition, conventional radiological and clinical features were combined with RFs into multivariate logistic regression models using minimum redundancy and a bootstrap-based machine learning approach. For each endpoint, models were trained and validated including only RFs (RF_model), and both (radiomic and clinicoradiological) features (COMB_model).

RESULTS

Twenty-five patients had G2/G3 tumor, 37 N+, and 14 M+ and 38 were shown to have VI. From a total of 182 RFs initially extracted, few independent radiomic and clinicoradiological features were identified. For M+ and G, the resulting models showed moderate to high performances: areas under the curve (AUC) for training/validation cohorts were 0.85/0.77 (RF_model) and 0.81/0.81 (COMB_model) for M+ and 0.67/0.72 and 0.68/0.70 for G. Concerning N+ and VI, only the COMB_model could be built, with poorer performance for N+ (AUC = 0.72/0.61) compared to VI (0.82/0.75). For all endpoints, the negative predictive value was good (≥ 0.75).

CONCLUSIONS

Combining few radiomic and clinicoradiological features resulted in presurgical prediction of histological characteristics of PanNENs. Despite the limited risk of overfit, external validations are warranted.

KEY POINTS

• Histology is the only tool currently available allowing characterization of PanNEN biological characteristics important for prognostic assessment; significant limitations to this approach exist. • Based upon preoperative contrast-enhanced CT images, a machine learning approach optimized to favor models' generalizability was successfully applied to train predictive models for tumor grading (G1 vs. G2/3), microvascular invasion, metastatic lymph nodes, and distant metastatic spread. • Moderate to high discriminative models (AUC: 0.67-0.85) based on few parameters (≤ 3) showing high negative predictive value (0.75-0.98) were generated and then successfully validated.

A novel tool to predict nodal metastasis in small pancreatic neuroendocrine tumors: A multicenter study

BACKGROUND

Nonfunctional pancreatic neuroendocrine tumors display a wide range of biological behavior, and nodal disease is associated with metastatic disease and poorer survival. The aim of this study was to develop a tool to predict nodal disease in patients with small (≤2 cm) nonfunctional pancreatic neuroendocrine tumors.

METHODS

A multicenter retrospective study was performed on patients undergoing resection for small nonfunctional pancreatic neuroendocrine tumors. Patients with genetic syndromes, metastatic disease at diagnosis, neoadjuvant therapy, or positive resection margin were excluded. Factors associated with nodal disease were identified to develop a predictive model. Internal validation was performed using bootstrap with 1,000 resamples.

RESULTS

Nodal disease was observed in 39 (11.1%) of the 353 patients included. Presence of nodal disease was significantly associated with lower 5-year disease-free survival (71.6% vs 96.2%, P < .001). Two predictors were strongly associated with nodal disease: G2 grade (odds ratio: 3.51, 95% confidence interval: 1.71-7.22, P = .001) and tumor size (per mm increase, odds ratio: 1.14, 95% confidence interval: 1.03-1.25, P = .009). Adequate discrimination was observed with an area under the curve of 0.71 (95% confidence interval: 0.63-0.80). Based on risk distribution, 3 risk groups of nodal disease were identified; low (<5%), intermediate (≥5% to <20%), and high (≥20%) risk. The observed mean risk of nodal disease was 3.7% in the low-risk patients, 9.6% in the intermediate-risk patients, and 30.4% in the high-risk patients (P < .001). The 10-year disease-free survival in the low, intermediate, and high-risk groups was 100%, 88.8%, and 50.1%, respectively.

CONCLUSION

Our model using tumor grade and size can predict nodal disease in small nonfunctional pancreatic neuroendocrine tumors. Integration of this tool into clinical practice could help guide management of these patients.

Clinicopathological characteristics, survival outcomes and prognostic factors in the cT1N0M0 pancreatic neuroendocrine tumors: A SEER-based study

Small nonfunctional pancreatic neuroendocrine tumors ≤2 cm have different biological features, and there is no gold standard treatment for them. This study aimed to assess the risk of malignancy of small non-functional pancreatic neuroendocrine tumors and their outcomes after radical resection. The optimal management of small, incidentally detected pancreatic neuroendocrine tumors is controversial, with the aim of identifying factors predicting survival in patients with clinical stage T1N0M0 (cT1N0M0) pancreatic neuroendocrine tumors and whether surgical treatment improves survival. Using the Surveillance, Epidemiology, and End Results database, we identified 637 patients with cT1N0M0 pancreatic neuroendocrine tumors from 2010 to 2015, including clinicopathological characteristics, treatment modalities, and outcome data. From the surveillance, epidemiology, and end results database of 637 patients with cT1N0M0 PNENs, 564 were treated surgically. Age (P = .000), sex (P < .001), and surgery (P < .001) were independent risk factors affecting survival. Patients who have undergone surgery, women and young adults have a higher overall survival rate. The following independent prognostic predictors for cT1N0M0 pNENs were identified: age, sex, and surgery. At last, we concluded that Surgery can increase the overall survival of pancreatic neuroendocrine tumors in T1N0M0.

Impact of Surgery on Non-Functional Pancreatic Neuroendocrine Tumors ≤2 cm: Analyses With Propensity Score–Based Inverse Probability of Treatment Weighting

Purpose

The impact of surgery on non-functional pancreatic neuroendocrine tumors (NF-PNETs) ≤2 cm is controversial. This study sought to demonstrate the impact of surgery on the prognosis of NF-PNETs ≤2 cm with different biological behaviors.

Methods

Patients with NF-PNETs ≤2 cm from 2004 to 2015 in the Surveillance, Epidemiology, and End Results database were included in this study. An inverse probability of treatment weighting (IPTW) method was used to reduce the selection bias. Kaplan–Meier survival analysis and Cox proportional hazards regression were used to evaluate the effect of surgery on the prognosis.

Results

In the IPTW-adjusted Cox proportional hazards regression analysis, surgery improved the cancer-specific survival (CSS) in the overall cohort (hazard ratio [HR], 0.187; 95% confidence interval [CI], 0.102–0.343; p < 0.001), patients with poorly differentiated or undifferentiated tumor grades (HR, 0.238; 95% CI, 0.105–0.64; p < 0.001), patients with distant metastasis (HR, 0.102; 95% CI, 0.021–0.496; p = 0.005), and patients with local invasion (HR, 0.059; 95% CI, 0.005–0.683; p = 0.002). Surgery did not improve the CSS in patients with lymph node metastasis only (HR, 0.26; 95% CI, 0.0462–1.461; p = 0.126) or patients with well or moderate differentiation while without distant and lymph node metastasis (HR, 0.387; 95% CI, 0.146–1.028; p = 0.057).

Conclusions

Among patients with NF-PNETs ≤2 cm, different biological behaviors correlate with different prognostic impacts of surgery. As long as distant metastasis does not occur and the grade is well–moderately differentiated, these patients will not benefit from surgery no matter whether lymph node metastasis occurs or not. However, when local invasion appears in this group of patients, surgery should be performed. Moreover, patients with a tumor grade of poorly differentiated or undifferentiated or those with distant metastases may benefit from surgery.

Sporadic nonfunctional pancreatic neuroendocrine tumors: Risk of lymph node metastases and aggressiveness according to tumor size: A multicenter international study

BACKGROUND

Although the correlation between tumor size and aggressiveness is clearly established in sporadic nonfunctional pancreatic neuroendocrine tumors, the management of tumors ≤2 cm remains debated. In recent guidelines, the cut-off size to operate ranged from 1 to 2 cm. The aim of this retrospective study was to report the rate of lymph nodes metastases in resected sporadic nonfunctional pancreatic neuroendocrine tumors, according to tumor size and, second, to identify risk factors of lymph node metastases and disease-free survival.

METHODS

Resected sporadic nonfunctional pancreatic neuroendocrine tumors from 9 international expert centers were included (1999-2017). Functional pancreatic neuroendocrine tumors, genetic syndromes, and R2 resection were excluded. Aggressiveness was defined as microvascular invasion, perineural invasion, lymph node metastases, G3 grading, distant metastases, and/or recurrence.

RESULTS

Overall, 495 resected sporadic nonfunctional pancreatic neuroendocrine tumors were included. For tumors up to 5 cm, the risk of lymph node metastases was increased by 1.73 for every 1 cm increase in size (odds ratio = 1.73; 95% confidence interval = 1.46-2.03). Tumor size >2 cm (P < .001), perineural invasion (P = .002), microvascular invasion (P < .001), and distant metastases (P = .008) were independently associated with lymph node metastases. Tumor size >2 cm (P = .003), R1 status (P = .004), lymph node metastases (P < .001), and World Health Organization grade 3 (P = .002) were independently associated with disease-free survival. Aggressiveness rate was 13.1% in tumors ≤1 cm and 29% in tumors between 1.1 and 2 cm.

CONCLUSION

In resected sporadic nonfunctional pancreatic neuroendocrine tumors, the risk of lymph node metastases is correlated to tumor size. Considering that sporadic nonfunctional pancreatic neuroendocrine tumors between 1.1 and 2 cm had a higher risk of lymph node metastases and recurrence compared to tumors ≤1 cm, the decision to perform surgery in this subgroup of patients should be individualized in surgically fit patients.

Clinicopathological Characteristics of Nonfunctional Pancreatic Neuroendocrine Neoplasms and the Effect of Surgical Treatment on the Prognosis of Patients with Liver Metastases: A Study Based on the SEER Database

Background

The incidence of nonfunctional pancreatic neuroendocrine neoplasms (NF-pNENs) has been increasing annually. This study is aimed at investigating the clinicopathological characteristics and high-risk factors of NF-pNENs and the influence of surgical treatment on the prognosis of NF-pNEN patients with liver metastases.

Methods

pNEN patients in this study were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. This study analyzed patients diagnosed with NF-pNENs from 2000 to 2017 who met the inclusion criteria. A retrospective analysis of the clinicopathological characteristics of NF-pNEN patients was conducted. Kaplan-Meier method was used to calculate the survival time. A multivariate Cox regression model was used to analyze the survival outcomes and risk factors.

Results

From 2000 to 2017, the SEER database registered 10576 patients with pNENs and 1774 patients with liver metastases. Cox analysis revealed that age, sex, primary site, grade, tumor stage, surgery, tumor size, and liver metastasis were risk factors of prognosis, with grade being the most influential index. Patients with NF-pNENs with liver metastasis and no metastasis had different primary site, grade, and tumor size. In general, a higher grade was associated with a larger tumor and a greater risk of liver metastasis. Meanwhile, patients with liver metastasis showed that those with tumors originated from the tail of the pancreas had better prognoses than those with tumors originated from other parts. Surgical treatment can improve the prognosis of patients with liver metastases, despite the tumor grade.

Conclusions

The incidence of pNENs has been increasing annually, and the liver has been the most common site of metastasis. Liver metastasis in patients with NF-pNENs, related to tumor size and grade, affected their long-term survival. Surgery significantly improved the prognosis of patients with liver metastases secondary to NF-pNENs with different grades.

Preoperative Prediction of G1 and G2/3 Grades in Patients With Nonfunctional Pancreatic Neuroendocrine Tumors Using Multimodality Imaging

OBJECTIVES

We aimed to develop and validate a multimodality radiomics model for the preoperative prediction of nonfunctional pancreatic neuroendocrine tumor (NF-pNET) grade (G).

METHODS

This retrospective study assessed 123 patients with surgically resected, pathologically confirmed NF-pNETs who underwent multidetector computed tomography and MRI scans between December 2012 and May 2020. Radiomic features were extracted from multidetector computed tomography and MRI. Wilcoxon rank-sum test and Max-Relevance and Min-Redundancy tests were used to select the features. The linear discriminative analysis (LDA) was used to construct the four models including a clinical model, MRI radiomics model, computed tomography radiomics model, and mixed radiomics model. The performance of the models was assessed using a training cohort (82 patients) and a validation cohort (41 patients), and decision curve analysis was applied for clinical use.

RESULTS

We successfully constructed 4 models to predict the tumor grade of NF- pNETs. Model 4 combined 6 features of T2-weighted imaging radiomics features and 1 arterial-phase computed tomography radiomics feature, and showed better discrimination in the training cohort (AUC = 0.92) and validation cohort (AUC = 0.85) relative to the other models. In the decision curves, if the threshold probability was 0.07-0.87, the use of the radiomics score to distinguish NF-pNET G1 and G2/3 offered more benefit than did the use of a "treat all patients" or a "treat none" scheme in the training cohort of the MRI radiomics model.

CONCLUSION

The LDA classifier combining multimodality images may be a valuable noninvasive tool for distinguishing NF-pNET grades and avoid unnecessary surgery.

Insights of Outcome after Resection of Small Nonfunctioning Neuroendocrine Pancreatic Tumors

Background

The incidence of small nonfunctioning neuroendocrine pancreatic tumors (NF-PNETs) has been increasing systematically in the last few decades. Surgical resection was once considered the treatment of choice but has been questioned in the direction of a more conservative approach for selected patients. Our aim was to analyze the outcome of surgical resection of small (≤3cm) NF-PNETs.

Methods

We retrospectively evaluated 14 patients with sporadic NF-PNETs who underwent pancreatic resection. Data were collected from patients' medical records.

Results

Of the 14 patients included, 35.71% were men, and the average age was 52.36 ± 20.36 years. Comorbidities were present in 92.86% of the cases. The incidence of postoperative complications was 42.86%, the 30-day mortality was zero, and the length of follow-up was 3.31 ± 3.0 years. The results of pathological evaluations revealed WHO grade I in 42.86% of cases, II in 21.43%, and neuroendocrine carcinoma in 35.71%. The median tumor size was 1.85cm (range, 0.5–3cm), and 2 cases had synchronous metastasis. The median TNM stage was IIa (range, I–IV). The disease-free and patient survival rates were 87.5% and 100% at 3 years and 43.75% and 75% at 10 years, respectively. The tumor pathological grade was significantly higher in head tumors than body-tail tumors, but there were no differences with respect to tumor size and TNM staging.

Conclusion

A surgical approach to treat small sporadic NF-PNETs is safe with low mortality and high patient survival. Based on these data, small pancreatic head tumors can be more aggressive, suggesting that surgical resection is still the best option to treat small nonfunctioning PNETS. Thus, conservative treatment should be indicated very cautiously for only cases with absolute contraindications for surgery.

CT-derived radiomic features to discriminate histologic characteristics of pancreatic neuroendocrine tumors

PURPOSE

To assess the ability of radiomic features (RF) extracted from contrast-enhanced CT images (ceCT) and non-contrast-enhanced (non-ceCT) in discriminating histopathologic characteristics of pancreatic neuroendocrine tumors (panNET).

METHODS

panNET contours were delineated on pre-surgical ceCT and non-ceCT. First- second- and higher-order RF (adjusted to eliminate redundancy) were extracted and correlated with histological panNET grade (G1 vs G2/G3), metastasis, lymph node invasion, microscopic vascular infiltration. Mann-Whitney with Bonferroni corrected p values assessed differences. Discriminative power of significant RF was calculated for each of the end-points. The performance of conventional-imaged-based-parameters was also compared to RF.

RESULTS

Thirty-nine patients were included (mean age 55-years-old; 24 male). Mean diameters of the lesions were 24 × 27 mm. Sixty-nine RF were considered. Sphericity could discriminate high grade tumors (AUC = 0.79, p = 0.002). Tumor volume (AUC = 0.79, p = 0.003) and several non-ceCT and ceCT RF were able to identify microscopic vascular infiltration: voxel-alignment, neighborhood intensity-difference and intensity-size-zone families (AUC ≥ 0.75, p < 0.001); voxel-alignment, intensity-size-zone and co-occurrence families (AUC ≥ 0.78, p ≤ 0.002), respectively). Non-ceCT neighborhood-intensity-difference (AUC = 0.75, p = 0.009) and ceCT intensity-size-zone (AUC = 0.73, p = 0.014) identified lymph nodal invasion; several non-ceCT and ceCT voxel-alignment family features were discriminative for metastasis (p < 0.01, AUC = 0.80-0.85). Conventional CT 'necrosis' could discriminate for microscopic vascular invasion (AUC = 0.76, p = 0.004) and 'arterial vascular invasion' for microscopic metastasis (AUC = 0.86, p = 0.001). No conventional-imaged-based-parameter was significantly associated with grade and lymph node invasion.

CONCLUSIONS

Radiomic features can discriminate histopathology of panNET, suggesting a role of radiomics as a non-invasive tool for tumor characterization.

TRIAL REGISTRATION NUMBER

NCT03967951, 30/05/2019.

Magnetic resonance imaging radiomic analysis can preoperatively predict G1 and G2/3 grades in patients with NF-pNETs

PURPOSE

We aimed to explore the relationship between the magnetic resonance imaging (MRI) radiomic score (rad-score) and the grades of non-functioning pancreatic neuroendocrine tumors (NF-pNETs) and evaluate the potential of the calculated MRI rad-score to differentiate grade 1 from grade 2/3 NF-pNETs.

METHODS

This retrospective study assessed 157 patients with surgically resected, pathologically confirmed NF-pNETs who underwent magnetic resonance scans from November 2012 to December 2019. Radiomic features were extracted from arterial and portal venous MRI. The least absolute shrinkage and selection operator method were used to select the features. Multivariate logistic regression models were used to analyze the association between the MRI rad-score and NF-pNET grades. The MRI rad-score performance was assessed based on its discriminative ability and clinical usefulness.

RESULTS

The MRI rad-score, which consisted of seven selected features, was significantly associated with the NF-pNET grades. Every 1-point increase in the rad-score was associated with a 35% increased risk of grade 2/3 disease. The score also showed high accuracy (area under the curve = 0.775). The best cut-off point for maximal sensitivity and specificity was at 0.41. In the decision curves, when the threshold probability was higher than 0.3, the rad-score used in this study to distinguish grades 1 and 2/3 NF-pNETs offered more benefits than the use of a treat-all-patients or a treat-none scheme.

CONCLUSIONS

The MRI rad-score showed a significant association with the grades of NF-pNETs. Thus, it may be used as a valuable non-invasive tool for differential NF-pNET grading.

Upregulation of Peroxiredoxin-2 in Well-Differentiated Pancreatic Neuroendocrine Tumors and Its Utility as a Biomarker for Predicting the Response to Everolimus

Pancreatic neuroendocrine neoplasms (pNENs) account for 2–3% of pancreatic malignancies. Peroxiredoxins (Prdxs), which are major cellular antioxidants, are involved in multiple oncogenic signaling pathways. We investigated the role of peroxiredoxin-2 in QGP-1 human pNEN cell line and patient-derived pNEN tissue. To validate the cancer stem cell-like cell characteristics of QGP-1 cells in spheroid culture, in vitro analyses and xenografting were performed. Furthermore, immunohistochemical staining was conducted to verify the overexpression of Prdx2 in pNEN tissue. Prdx2 expression was high at the mRNA and protein levels in QGP-1 cells. Prdx2 was also overexpressed in patient-derived pNEN tissue. Silencing of Prdx2 using siRNA induced overexpression and phosphorylation of ERK and AKT in QGP-1. Cell proliferation was increased by treating QGP-1 cells with siPrdx2, and the IC50 of everolimus increased suggesting resistance to everolimus. Interestingly, QGP-1 spheroid cells, which exhibited cancer stem cell-like features, exhibited lower expression of Prdx2 and mTOR. The results suggest that Prdx2 expression level and its activity may be a potential predictive biomarker for therapeutic response or resistance to everolimus in pNEN.

Predictive significance of tumor budding in postoperative liver metastasis of pancreatic neuroendocrine tumors

BACKGROUND

Although pancreatic neuroendocrine tumors (PNETs) are considered indolent tumors, nearly half of cases metastasize to the liver, which can be lethal. However, effective indicators to predict aggressive behavior have not been well-established.

METHODS

In the current study, we explored the prognostic significance of tumor budding in Grade 1-2 PNETs. Hematoxylin-eosin and immunohistochemically stained slides of surgically removed Grade 1-2 PNETs were evaluated.

RESULTS

Tumor budding, a histomorphological parameter that corresponds to single cells or small cell clusters (<5 cells), was classified as low (0-10 buds) and high (>10 buds) grade. We observed that tumor budding was correlated with aggressive histopathological parameters, such as T stage, lymph node status, metastasis, and vascular invasion (p < .05). Univariate and multivariate analyses showed that high-grade budding was an independent predictive factor for postoperative liver metastasis (p = .012). Moreover, Grade 1-2 PNETs with high-grade budding was associated with worse overall survival and disease-free survival (p = .0015 and p = .0041, respectively).

CONCLUSIONS

We conclude that tumor budding may serve as a valuable parameter in the risk stratification of postoperative liver metastasis and that incorporating tumor budding into histopathological reports may aid in appropriate clinical management.

The Landmark Series: Pancreatic Neuroendocrine Tumors

Pancreatic neuroendocrine tumors (PNETs) comprise a heterogeneous group of neoplasms arising from pancreatic islet cells that remain relatively rare but are increasing in incidence worldwide. While significant advances have been made in recent years with regard to systemic therapies for patients with advanced disease, surgical resection remains the standard of care for most patients with localized tumors. Although formal pancreatectomy with regional lymphadenectomy is the standard approach for most PNETs, pancreas-preserving approaches without formal lymphadenectomy are acceptable for smaller tumors at low risk for lymph node metastases. Furthermore, observation of small, asymptomatic, low-grade PNETs is a safe, initial strategy and is generally recommended for tumors < 1 cm in size. In this Landmark Series review, we highlight the critical studies that have defined the surgical management of PNETs.

Usefulness of texture analysis for grading pancreatic neuroendocrine tumors on contrast-enhanced computed tomography and apparent diffusion coefficient maps

PURPOSE

To determine whether texture analysis of contrast-enhanced computed tomography (CECT) and apparent diffusion coefficient (ADC) maps could predict tumor grade (G1 vs G2-3) in patients with pancreatic neuroendocrine tumor (PNET).

MATERIALS AND METHODS

Thirty-three PNETs (22 G1 and 11 G2-3) were retrospectively reviewed. Fifty features were individually extracted from the arterial and portal venous phases of CECT and ADC maps by two radiologists. Diagnostic performance was assessed by receiver operating characteristic curves while inter-observer agreement was determined by calculating intraclass correlation coefficients (ICCs).

RESULTS

G2-G3 tumors were significantly larger than G1. Seventeen features significantly differed among the two readers on univariate analysis, with ICCs > 0.6; the largest area under the curve (AUC) for features of each CECT phase and ADC map was log-sigma 1.0 joint-energy = 0.855 for the arterial phase, log-sigma 1.5 kurtosis = 0.860 for the portal venous phase, and log-sigma 1.0 correlation = 0.847 for the ADC map. The log-sigma 1.5 kurtosis of the portal venous phase showed the largest AUC in the CECT and ADC map, and its sensitivity, specificity, and accuracy were 95.5%, 72.7%, and 87.9%, respectively.

CONCLUSION

Texture analysis may aid in differentiating between G1 and G2-3 PNET.

CT-Based Radiomics Score for Distinguishing Between Grade 1 and Grade 2 Nonfunctioning Pancreatic Neuroendocrine Tumors

OBJECTIVE. The objective of our study was to explore the relationship between a CT-based radiomics score and grade of nonfunctioning pancreatic neuroendocrine tumors (PNETs) and to evaluate the ability of a calculated CT radiomics score to distinguish between grade 1 and grade 2 nonfunctioning PNETs. MATERIALS AND METHODS. This retrospective study assessed 102 patients with surgically resected, pathologically confirmed nonfunctioning PNETs who underwent MDCT from January 2014 to December 2017. Radiomic methods were used to extract features from portal venous phase CT scans, and the least absolute shrinkage and selection operator (LASSO) method was used to select the features. Multivariate logistic regression models were used to analyze the association between the CT radiomics score and nonfunctioning PNET grades. The performance of the CT radiomics score was assessed on the basis of its discriminative ability and clinical usefulness. RESULTS. The CT radiomics score, which consisted of four selected features, was significantly associated with nonfunctioning PNET grades. Every 1-point increase in radiomics score was associated with a 57% increased risk of grade 2 disease. The score also showed high accuracy (AUC = 0.86 for all PNETs; AUC = 0.81 for PNETs ≤ 2 cm). The best cutoff point for maximal sensitivity and specificity was a CT radiomics score of -0.134. Decision curve analysis showed that the CT radiomics score is clinically useful. CONCLUSION. The CT radiomics score shows a significant association with the grade of nonfunctioning PNETs and provides a potentially valuable noninvasive tool for distinguishing between different grades of nonfunctioning PNET, especially among patients with tumors 2 cm or smaller.

Propensity score-matched analysis of clinical outcome after enucleation versus regular pancreatectomy in patients with small non-functional pancreatic neuroendocrine tumors

OBJECTIVES

The effectiveness of enucleation in treatment for low-grade (G1, G2) small (≤2 cm) non-functional pancreatic neuroendocrine tumors (sNF-pNETs) remains controversial. This study investigated short- and long-term outcome of enucleation comparing with regular pancreatectomy in patients with sNF-pNETs.

METHODS

The clinical data of patients with sNF-pNETs who underwent surgery in our hospital from January 2000 to December 2017 were retrospectively collected. Short- and long-term outcomes of two operations were analyzed. The propensity score matching (PSM) was performed to reduce potential selection bias.

RESULTS

A total of 123 patients with sNF-pNETs were enrolled with 62 males, 69 G1, and median age was 56.91 ± 10.04 years old. During the follow-up period (mean 87 ± 58.1 months), 9(7.32%) disease progressed (recurrence or metastasis) and 2 died (1.62%), 5-years OS was 100%, 5-years DFS was 91.4%. Both lymph node metastasis (p = 0.117) and pathological grade (p = 0.050) were not prognostic factors for sNF-pNETs. The propensity score-matched cohort comprised 27 patients with enucleation and 44 patients with regular pancreatectomy. Enucleation was noninferior to regular pancreatectomy in terms of DFS, before or after PSM. The surgical duration (P < 0.01) and blood loss (P < 0.01) significantly decreased in enucleation compared with regular pancreatectomy. The other postoperative complications tended to occur in regular pancreatectomy than in enucleation, but no statistically significant difference (all p > 0.05).

CONCLUSION

Enucleation seems to be an effective option for the treatment of sNF-pNETs with a lower total rate of postoperative complications and similar long-term prognosis, compared with regular pancreatectomy.

Impact of tumor size and nodal status on recurrence of nonfunctional pancreatic neuroendocrine tumors ≤2 cm after curative resection: A multi‐institutional study of 392 cases

BACKGROUND

The current study sought to define the impact of lymph node metastasis (LNM) relative to tumor size on tumor recurrence after curative resection for nonfunctional pancreatic neuroendocrine tumors (NF-pNETs) ≤2 cm.

METHODS

Patients who underwent curative resection for ≤2-cm NF-pNETs were identified from a multi-institutional database. Risk factors associated with tumor recurrence as well as LNM were identified. Recurrence-free survival (RFS) was compared among patients with or without LNM.

RESULTS

A total of 392 ≤2-cm NF-pNETs patients were identified. Among the 328 patients who had lymph node dissection and evaluation, 42 (12.8%) patients had LNM. LNM was associated with tumor recurrence (hazard ratio, 3.06; P = .026) after surgery. RFS was worse among LNM vs no LNM patients (5-year RFS, 81.7% vs 94.1%; P = .019). Patients with tumors measuring 1.5-2 cm had a two-fold increase in the incidence of LNM vs patients with tumors <1.5 cm (17.9% vs 8.7%, odds ratio, 2.59; P = .022), as well as a higher risk of advanced tumor grade and higher Ki-67 levels (both P < .01). After curative resection, a total of 14 (8.0%) patients with a tumor of 1.5-2 cm and 10 (4.5%) patients with tumor <1.5 cm developed tumor recurrence.

CONCLUSION

Surgical resection with lymphadenectomy should be considered for patients with NF-pNETs ≥1.5-2.0 cm.

Clinicopathological characteristics and risk factors for recurrence of well-differentiated pancreatic neuroendocrine tumors after radical surgery: a case-control study

Background

Well-differentiated pancreatic neuroendocrine tumors (PanNETs) usually have a good prognosis; however, there are patients that experience recurrence after curative resection.

Aim

To explore recurrence-related risk factors by analyzing clinicopathological data of PanNETs after radical surgery.

Methods

Clinical and pathological data from 47 patients with well-differentiated PanNETs at China-Japan Friendship Hospital from January 2012 to March 2016 were analyzed retrospectively. Univariate and multivariate analyses of the risk factors of PanNETs for postoperative recurrence were conducted.

Results

Among the 47 patients with well-differentiated PanNETs, there were 38 cases with non-functioning tumors, 9 cases with functional tumors (6 insulinomas, 1 gastrinoma, 1 glucagonoma, and 1 VIPomas). There are 17 cases (36.2%) in the pancreatic head, 17 (36.2%) in the body and tail, 9 (19.1%) in the tail, and 4 (8.5%) in the body. The median tumor size was 3.65 (IQR 2–5.5) cm. Fourteen cases (29.8%) were NET G1, and 33 cases (70.2%) were NET G2. In regard to the clinical stage, 9 (19.1%) cases were IA, 14 (29.8%) cases were IB, 7 (14.9%) cases were IIA, 14 (29.8%) cases were IIB, and 3 cases unknown. There were 17 patients who presented with postoperative recurrence. Univariate analysis showed that AJCC TNM staging, Ki67 index, vascular invasion, margin status, and the regional stage of the tumors are related to the recurrence of patients with PanNETs (p < 0.05). The results of multivariate analysis showed that Ki67 index ≥ 10% is an independent risk factor for the postoperative recurrence of PanNETs (p < 0.05).

Conclusion

The Ki67 index ≥ 10% is an independent risk factor for recurrence in well-differentiated PanNETs after radical surgery, and close surveillance for these patients may be needed.

Combination of laparoscopy and endoscopy as an option for treatment patients with gastric neuroendocrine tumors

Background

Neuroendocrine tumors (NETs) are relatively rare neoplasms with the increasing survival due to the development of early diagnostics. There is no universal position in treatment and follow up of small (~20 mm) gastric NETs.

Clinical cases

Two female patients 51 and 66 y.o. with multiple gastric NETs <2 cm were observed in our department. In both cases treatment was performed by combination of two minimally invasive technologies: laparoscopy and gastroscopy. According to the localization of tumors in one case intraluminal gastric resection controlled by laparoscopy was performed. In the second case laparoscopic gastric resection with gastroscopy assistance was done.

Discussion

There are two positions for surgical treatment of small NETs: to operate as the typical premalignant neoplasm or to make submucosa resections. We demonstrated combination of laparoscopy and gastroscopy as feasible approach with minimal risk of complications.

Ct radiomic features of pancreatic neuroendocrine neoplasms (panNEN) are robust against delineation uncertainty

PURPOSE

The aim of this study was to quantify the impact of CT delineation uncertainty of pancreatic neuroendocrine neoplasms (panNEN) on Radiomic features (RF).

METHODS

Thirty-one previously operated patients were considered. Three expert radiologists contoured panNEN lesions on pre-surgical high-resolution contrast-enhanced CT images and contours were transferred onto pre-contrast CT. Volume agreement was quantified by the DICE index. After images resampling and re-binning, 69 RF were extracted and the impact of inter-observer variability was assessed by Intra-Class Correlation (ICC): ICC > 0.80 was considered as a threshold for "very high" inter-observer agreement.

RESULTS

The median volume was 1.3 cc (range: 0.2-110 cc); a satisfactory inter-observer volume agreement was found (mean DICE = 0.78). Only 4 RF showed ICC < 0.80 (0.48-0.73), including asphericity and three RFs (of five) of the neighborhood intensity difference matrix (NID).

CONCLUSIONS

The impact of inter-observer variability in delineating panNEN on RF was minimum, with the exception of the NID family and asphericity, showing a moderate agreement. These results support the feasibility of studies aiming to assess CT radiomic biomarkers for panNEN.

Parenchyma-sparing, local pancreatic head resection for premalignant and low-malignant neoplasms - A systematic review and meta-analysis

BACKGROUND

Parenchyma-sparing, local pancreatic head resection, but not pancreaticoduodenectomy (PD) preserves tissue and maintains the pancreatic metabolic functions.

METHODS

PubMed/Medline, Embase, and Cochrane library collections were systematically searched. Twenty-six cohort studies with 523 cumulative patients, who underwent duodenum-sparing pancreatic head resection (DPPHR), were retrieved. The meta-analysis was based on 14 controlled studies.

RESULTS

In total, 338 patients suffered cystic neoplasms and 59 PNETs, IPMN-174, MCN-43 and SPN-23 patients. Eighty-one patients (15.5%) histo-pathologically displayed a low-malignant tumor, of which 27 were carcinoma in-situ. Tumor recurrence was observed after a mean follow-up of 47.1 months in 11 patients. In-hospital and late mortality after DPPHR was 0.6% and 1.7%, respectively. The meta-analysis was based on 318 DPPHR compared to 404 PD patients. DPPHR was performed for premalignant neoplasm and PNET in 164 and 46 patients, and PD in 181 and 46 patients, respectively. Events of recurrence displayed no statistically significant difference between the DPPHR and PD groups.

CONCLUSION

DPPHR is associated with oncologically complete tumor resection for patients suffering premalignant IPMN, MCN, or SPN and for low-risk cancer.

Exploring the surgical landscape of pancreatic neuroendocrine neoplasia in Austria: Results from the ASSO pNEN study group

INTRODUCTION

Pancreatic neuroendocrine neoplasia (pNEN) show increasing incidence and management is complex due to biological heterogeneity. Most publications report isolated high-volume single-centre data. This Austrian multi-centre study on surgical management of pNENs provides a comprehensive real-life picture of quality indicators, recurrence-patterns, survival factors and systemic treatments.

METHODS

Retrospective, national cohort-study from 7 medium-/high-volume centres in Austria, coordinated under the auspices of the Austrian Society of Surgical Oncology (ASSO).

RESULTS

Two-hundred patients underwent resection for pNEN, 177 had non-functioning tumours and 31 showed stage 4 disease. Participating centres were responsible for 2/3 of pNEN resections in Austria within the last years. The mean rate of completeness of variables was 98.6%. Ninety-days mortality was 3.5%, overall rate of complications was 42.5%. Morbidity did not influence long-term survival. The 5-year overall-survival (OS) was 81.3%, 10-year-OS 52.5% and 5-year recurrence-free-survival (RFS) 69.8%. Recurrence was most common in the liver (68.1%). Four out of five patients with recurrence underwent further treatment, most commonly with medical therapy or chemotherapy. Multivariable analysis revealed grading (HR:2.7) and metastasis (HR:2.5) as significant factors for relapse. Tumours-size ≥2 cm (HR:5.9), age ≥60 years (HR:3.1), metastasis (HR:2.3) and grading (HR:2.0) were associated with OS. Tumours <2 cm showed 93.9% 10-year-OS, but 33% had G2/G3 grading, 12.5% positive lymph-nodes and 4.7% metastasis at diagnosis, each associated with significant worse survival.

CONCLUSION

Resection of pNENs in Austria is performed with internationally comparable safety. Analysed factors allow for risk-stratification in clinical treatment and future prospective trials. A watch-and-wait strategy purely based on tumour-size cannot be recommended.

Prediction of Pancreatic Neuroendocrine Tumor Grade Based on CT Features and Texture Analysis

OBJECTIVE

The purposes of this study were to assess whether CT texture analysis and CT features are predictive of pancreatic neuroendocrine tumor (PNET) grade based on the World Health Organization (WHO) classification and to identify features related to disease progression after surgery.

MATERIALS AND METHODS

Preoperative contrast-enhanced CT images of 101 patients with PNETs were assessed. The images were evaluated for tumor location, tumor size, tumor pattern, predominantly solid or cystic composition, presence of calcification, presence of heterogeneous enhancement on contrast-enhanced images, presence of pancreatic duct dilatation, presence of pancreatic atrophy, presence of vascular involvement by the tumor, and presence of lymphadenopathy. Texture features were also extracted from CT images. Surgically verified tumors were graded according to the WHO classification, and patients underwent CT or MRI follow-up after surgical resection. Data were analyzed with chi-square tests, kappa statistics, logistic regression analysis, and Kaplan-Meier curves.

RESULTS

The CT features predictive of a more aggressive tumor (grades 2 and 3) were size larger than 2.0 cm (odds ratio [OR], 3.3; p = 0.014), presence of vascular involvement (OR, 25.2; p = 0.003), presence of pancreatic ductal dilatation (OR, 6.0; p = 0.002), and presence of lymphadenopathy (OR, 6.8; p = 0.002). The texture parameter entropy (OR, 3.7; p = 0.008) was also predictive of more aggressive tumors. Differences in progression-free survival distribution were found for grade 1 versus grades 2 and 3 tumors (χ² [df, 1] = 21.6; p < 0.001); for PNETs with vascular involvement (χ² [df, 1] = 20.8; p < 0.001); and for tumors with entropy (spatial scale filter 2) values greater than 4.65 (χ² (df, 1) = 4.4; p = 0.037).

CONCLUSION

CT texture analysis and CT features are predictive of PNET aggressiveness and can be used to identify patients at risk of early disease progression after surgical resection.

Decreased UCHL1 expression as a cytologic biomarker for aggressive behavior in pancreatic neuroendocrine tumors

BACKGROUND

There are currently no reliable markers associated with aggressive behavior in well-differentiated and moderately differentiated pancreatic neuroendocrine tumors. We aimed to determine whether expression of ubiquitin carboxyl-terminal hydrolase L1 in conjunction with Ki67 can identify metastatic potential of well-differentiated and moderately differentiated pancreatic neuroendocrine tumors from fine-needle aspiration samples obtained by endoscopic ultrasound.

METHODS

Retrospective review of 48 patients with well-differentiated and moderately differentiated pancreatic neuroendocrine tumors diagnosed by endoscopic ultrasound fine-needle aspiration at a single center identified 35 biopsy samples with adequate material for analysis. Ubiquitin carboxyl-terminal esterase L1 immunocytochemistry of primary pancreatic neuroendocrine tumors was performed along with Ki67 staining and scored semiquantitatively. The combination of ubiquitin carboxyl-terminal esterase L1 score ≤4 (weak) and Ki67 ≥3% (high) was considered a positive test for predicting tumors associated with metastases.

RESULTS

Weak ubiquitin carboxyl-terminal hydrolase L1 staining had 80% sensitivity, 65% specificity, 63% positive predictive value, and 81% negative predictive value to identify primary tumors associated with metastatic disease. The combination of weak ubiquitin carboxyl-terminal hydrolase L1 staining and high Ki67 staining increased the test specificity to 95%. On multivariable analysis, combined positive test of weak ubiquitin carboxyl-terminal esterase L1 staining and high Ki67 staining was an independent predictor of metastatic disease (P = .047).

CONCLUSION

Ubiquitin carboxyl-terminal hydrolase L1 is a novel biomarker for identifying malignant potential of primary well-differentiated and moderately differentiated pancreatic neuroendocrine tumors and in combination with Ki67 is an independent predictor of development of metastatic disease.

Management Options for Advanced Low or Intermediate Grade Gastroenteropancreatic Neuroendocrine Tumors: Review of Recent Literature

Our understanding of the biology, genetics, and natural history of neuroendocrine tumors (NETs) of the gastrointestinal tract and pancreas has improved considerably in the last several decades and the spectrum of available therapeutic options is rapidly expanding. The management of patients with metastatic low or intermediate grade NETs has been revolutionized by the development of new treatment strategies such as molecular targeting therapies with everolimus and sunitinib, somatostatin analogs, tryptophan hydroxylase inhibitors, and peptide receptor radionuclide therapy that can be used alone or as a multimodal approach with or without surgery. To further define and clarify the utility, appropriateness, and the sequence of the growing list of available therapies for this patient population will require more high level evidence; however, data from well-designed randomized phase III clinical trials is rapidly accumulating that will further stimulate development of new management strategies. It is therefore important to thoroughly review emerging evidence and report major findings in frequent updates, which will expand our knowledge and contribute to a better understanding, characterization, and management of advanced NETs.

Pancreatic neuroendocrine tumors

Pancreatic neuroendocrine neoplasms (pNENs) are a heterogeneous group of tumors including well differentiated pancreatic neuroendocrine tumors (pNETs) and neuroendocrine carcinomas (pNECs). The incidence of pNENs has increased over the past few decades. Although, the understanding and interest for this tumor have also increased significantly, the debate about classification and diagnosis continues. Although the primary treatment for pNENs is surgical resection, there is still a lack of effective therapeutic options for patients with advanced unresectable pNENs. Although many therapeutic methods have proven effective, the choice of treatment and specific programs are still unclear. Our article presents an overview of pNENs, with a focus on their diagnostic work-up, clinical presentation and treatment options.