WHO 2010 classification of pancreatic endocrine tumors. is the new always better than the old?

Correlation between radiologic features on contrast-enhanced CT and pathological tumor grades in pancreatic neuroendocrine neoplasms

Contrast-enhanced computed tomography (CT) contributes to the increasing detection of pancreatic neuroendocrine neoplasms (PNENs). Nevertheless, its value for differentiating pathological tumor grades is not well recognized. In this report, we have conducted a retrospective study on the relationship between the 2017 World Health Organization (WHO) classification and CT imaging features in 94 patients. Most of the investigated features eventually provided statistically significant indicators for discerning PNENs G3 from PNENs G1/G2, including tumor size, shape, margin, heterogeneity, intratumoral blood vessels, vascular invasion, enhancement pattern in both contrast phases, enhancement degree in both phases, tumor-to-pancreas contrast ratio in both phases, common bile duct dilatation, lymph node metastases, and liver metastases. Ill-defined tumor margin was an independent predictor for PNENs G3 with the highest area under the curve (AUC) of 0.906 in the multivariable logistic regression and receiver operating characteristic curve analysis. The portal enhancement ratio (PER) was shown the highest AUC of 0.855 in terms of quantitative features. Our data suggest that the traditional contrast-enhanced CT still plays a vital role in differentiation of tumor grades and heterogeneity analysis prior to treatment.

Liver Tumor Burden in Pancreatic Neuroendocrine Tumors: CT Features and Texture Analysis in the Prediction of Tumor Grade and 18F-FDG Uptake

Pancreatic neuroendocrine tumors (p-NETs) are a rare group of neoplasms that often present with liver metastases. Histological characteristics, metabolic behavior, and liver tumor burden (LTB) are important prognostic factors. In this study, the usefulness of texture analysis of liver metastases in evaluating the biological aggressiveness of p-NETs was assessed. Fifty-six patients with liver metastases from p-NET were retrospectively enrolled. Qualitative and quantitative CT features of LTB were evaluated. Histogram-derived parameters of liver metastases were calculated and correlated with the tumor grade (G) and ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) standardized uptake value (SUV). Arterial relative enhancement was inversely related with G (−0.37, p = 0.006). Different metastatic spread patterns of LTB were not associated with histological grade. Arterial_entropy was significantly correlated to G (−0.368, p = 0.038) and to Ki67 percentage (−0.421, p = 0.018). The ROC curve for the Arterial_entropy reported an area under the curve (AUC) of 0.736 (95% confidence interval 0.545–0.928, p = 0.035) in the identification of G1–2 tumors. Arterial_uniformity values were correlated to G (0.346, p = 0.005) and Ki67 levels (0.383, p = 0.033). Arterial_entropy values were directly correlated with the SUV (0.449, p = 0.047) which was inversely correlated with Arterial_uniformity (−0.499, p = 0.025). Skewness and kurtosis reported no significant correlations. In conclusion, histogram-derived parameters may predict adverse histological features and metabolic behavior of p-NET liver metastases.

The molecular biology of pancreatic neuroendocrine neoplasms: Challenges and translational opportunities

Pancreatic neuroendocrine neoplasms (PanNENs) are rare, highly heterogeneous tumours. There have been significant recent advances in our knowledge of genomic events underlying their pathogenesis. However, treatment decisions remain largely based on tumour stage and grade which is inadequate, the current classification paradigm failing to capture the significant heterogeneity in tumour biology. There is a well-acknowledged unmet clinical need for novel biomarkers to enable individualised risk-adapted therapeutic strategies for PanNEN patients. Improvements in our understanding of the molecular biology of multiple solid tumours have led to the development of new biomarker assays and gene expression signatures to guide treatment decisions in other cancer types. A similar index for PanNENs, to improve patient prognostication and classification, would be highly clinically relevant and with advances in the field now seems potentially possible. This article will seek to review the molecular biology of PanNENs, the subtypes developed to date and the potential clinical opportunities these advances may afford.

Systematic review of current prognostication systems for pancreatic neuroendocrine neoplasms

BACKGROUND

Pancreatic neuroendocrine neoplasms are a heterogenous group of rare tumors whose natural history remains poorly defined. Accurate prognostication of pancreatic neuroendocrine neoplasms is essential for guiding clinical decisions. This paper aims to summarize all the commonly utilized and recently proposed prognostication systems for pancreatic neuroendocrine neoplasms published in the literature to date.

METHODS

A systematic review of Pubmed, Scopus, and Embase databases, of the period from January 1, 2000-November 29, 2016, was conducted to identify all published articles reporting on prognostication systems of pancreatic neuroendocrine neoplasms.

RESULTS

A total of 23 articles were included in our review, and a total of 25 classification systems were identified. There were 2 modifications of the World Health Organization 2004 criteria, 4 modifications of the World Health Organization 2010 criteria, 2 modifications of the American Joint Committee on Cancer 2010 staging system, 3 modifications of the European Neuroendocrine Tumor Society 2006 tumor, node, metastasis staging system, 7 novel categorial classification systems, and 2 novel proposed continuous classifications. The most commonly included variables included age, size of tumor, presence of distant and lymph node metastases, Ki-67 index, and mitotic count.

CONCLUSION

Numerous prognostication systems have been proposed for pancreatic neuroendocrine neoplasms, of which the most commonly used systems presently include the World Health Organization 2010 criteria and the two tumor, node, metastasis staging systems by the European Neuroendocrine Tumor Society and the American Joint Commission on Cancer. However, prognostication systems for pancreatic neuroendocrine neoplasms continue to evolve with time as more prognostication factors are identified. More validation and comparative studies are needed to identify the most effective prognostication system.

Grade 2 pancreatic neuroendocrine tumors: overbroad scope of Ki-67 index according to MRI features

PURPOSE

To evaluate the value of MR imaging features in stratifying Grade 2 (G2) pancreatic neuroendocrine tumors (PNETs) using the 5% cut-off value of the Ki-67 index as reference standards.

MATERIALS AND METHODS

Between January 2010 and October 2016, 41 G2 PNET patients (One patient had 3 tumors) with preoperative MR imaging were included. Tumor grading was based on the revised 2016 World Health Organization classification of PNETs. MR imaging features included size, shape, consistency, T1-w and T2-w signal intensities, enhancement pattern, apparent diffusion coefficient (ADC) ratios (tumor/normal pancreatic parenchyma).

RESULTS

16 Ki-67 index < 5% tumors (SKIT, 37.2%) and 27 Ki-67 index ≥ 5% tumors (LKIT, 62.8%) of G2 were evaluated. The LKIT showed solid consistency (85% vs. 50%, P < 0.05), incomplete envelope-like reinforcement in a delayed phase (74% vs. 62%, P < 0.05), and liver or lymph node metastases (67% vs. 31%, P < 0.05) more frequently than did SKIT. However, ADC ratios of LKIT were smaller than SKIT (0.85 ± 0.23 vs. 1.29 ± 0.39, P = 0.001). Using binary logistic regression analysis, the ADC ratio was an independent significant differentiator of SKIT from LKIT. The AUROC of ADC ratios was 0.816 ± 0.07. The optimal cut-off value for the identification of LKIT was 1.25 × 10^-3 (sensitivity 96.3%, specificity 62.5%).

CONCLUSION

MRI features may identify the overbroad scope of G2 PNETs and help predict Ki-67 values, as a surrogate for tumor aggressiveness, in G2 PNETs. An optimal cut-off value for predicting Ki-67 status (≥/< 5%) was 1.25 × 10^-3 of ADC ratio.

Recurrence of Pancreatic Neuroendocrine Tumors and Survival Predicted by Ki67

Background

Despite evidence of different malignant potentials, postoperative follow-up assessment is similar for G1 and G2 pancreatic neuroendocrine tumors (panNETs) and adjuvant treatment currently is not indicated. This study investigated the role of Ki67 with regard to recurrence and survival after curative resection of panNET.

Methods

Patients with resected non-functioning panNET diagnosed between 1992 and 2016 from three institutions were retrospectively analyzed. Patients who had G1 or G2 tumor without distant metastases or hereditary syndromes were included in the study. The patients were re-categorized into Ki67 0–5 and Ki67 6–20%. Cox regression analysis with log-rank testing for recurrence and survival was performed.

Results

The study enrolled 241 patients (86%) with Ki67 0–5% and 39 patients (14%) with Ki67 6–20%. Recurrence was seen in 34 patients (14%) with Ki67 0–5% after a median period of 34 months and in 16 patients (41%) with Ki67 6–20% after a median period of 16 months (p < 0.001). The 5-year recurrence-free and 10-year disease-specific survival periods were respectively 90 and 91% for Ki67 0–5% and respectively 55 and 26% for Ki67 6–20% (p < 0.001). The overall survival period after recurrence was 44.9 months, which was comparable between the two groups (p = 0.283). In addition to a Ki67 rate higher than 5%, tumor larger than 4 cm and lymph node metastases were independently associated with recurrence.

Conclusions

Patients at high risk for recurrence after curative resection of G1 or G2 panNET can be identified by a Ki67 rate higher than 5%. These patients should be more closely monitored postoperatively to detect recurrence early and might benefit from adjuvant treatment. A clear postoperative follow-up regimen is proposed.

Is radical surgery always curative in pancreatic neuroendocrine tumors? A cure model survival analysis

BACKGROUND

Adjuvant therapy after curative surgery for sporadic pancreatic neuroendocrine tumor (pNETs) is not currently recommended, assuming that all patients could be cured by a radical resection. The aim of our study is to establish how many and which kind of patients remained uncured after radical resection of pNET.

METHODS

Retrospective study involving 143 resected sporadic pNETs. The survival analysis was carried out using the cure model, describing the cure fraction and the excess of risk recurrence. Multivariate analyses were made in order to evaluate the non negligible effect of demographics, clinical and pathological factors on survival parameters. The results were reported as percentages, fractions, ORs and HRs with 95% confidence interval (95 CI %).

RESULTS

The cure fraction and the excess of hazard rate of the whole population were 57.1% (37.4-74.6, 95% CI) and 0.06 (0.03-0.07, 95% CI), respectively. Two independent factors were related to the cure fraction: TNM stage (OR 0.27 ± 0.17; P = 0.002) and grading (OR 0.11 ± 0.18; P = 0.004). Considering the excess of hazard rate, only two independent factors were related to an increased risk of recurrence: TNM stage (HR 3.49 ± 1.12; P = 0.004) and grading (HR 4.93 ± 1.82; P < 0.001).

CONCLUSION

The radical surgery has a high probability of cure in stages I-II or in grading 1 while, in stages III-IV or in grading 3 tumors, surgery alone failed to achieve a "cure". A multimodal treatment should be employed in order to avoid a recurrence of the disease.

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.

Pancreatic neuroendocrine tumor: Correlations between MRI features, tumor biology, and clinical outcome after surgery

PURPOSE

To assess which magnetic resonance imaging (MRI) features are associated with pNETs (pancreatic neuroendocrine tumors) grade based on the WHO classification, as well as identify MRI features related to disease progression after surgery.

MATERIALS AND METHODS

In this Institutional Review Board (IRB)-approved study, 1.5T and 3.0T MRI scans of 80 patients with surgically verified pNETs were assessed. The images were evaluated for tumor location; size; pattern; predominant signal intensity on precontrast T₁ - and T₂ -weighted images, as well as on postcontrast arterial and portal venous phase T₁ -weighted sequences; presence of pancreatic duct dilatation; pancreatic atrophy; restricted diffusion; vascular involvement by the tumor; extrapancreatic tumor spread; and synchronous liver metastases. Tumors were graded based on the WHO classification and patients were followed-up with computed tomography (CT) or MRI after surgical resection. Data were analyzed with Student's t and chi-square tests, logistic regression, and Kaplan-Meier curves.

RESULTS

The MRI features that were associated with aggressive tumors were: size >2.0 cm (odds ratio [OR] = 4.8, P = 0.002), "T₂ nonbright lesions" on T₂ -weighted images (OR = 4.6, P = 0.008), presence of pancreatic ductal dilatation (OR = 4.9, P = 0.024), and restricted diffusion within the lesion (OR = 4.9, P = 0.013). Differences in progression-free survival distribution were found for patients whose pNETs were associated with the following MRI features: size >2.0 cm (χ² (1) = 6.0, P = 0.014), "nonbright lesions" on T₂ -weighted images (χ² (1) = 6.8, P = 0.009), and presence of pancreatic duct dilatation (χ² (1) = 10.9, P = 0.001).

CONCLUSION

MRI features can be used to assess pNETs aggressiveness and identify patients at risk for early disease progression after surgical resection.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:425-432.

Vascularity and Tumor Size are Significant Predictors for Recurrence after Resection of a Pancreatic Neuroendocrine Tumor

BACKGROUND

It is difficult to identify patients at high risk of recurrence after pancreatectomy for pancreatic neuroendocrine tumor (PNET) using only the grading classification, especially the G2 category, which includes both benign and low- and high-grade malignant tumors.

METHODS

Forty-one patients with PNET who underwent pancreatectomy were enrolled in this study. We defined the computed tomography (CT) ratio as the CT value of the tumor divided by that of non-tumorous pancreatic parenchyma using the late arterial phase dynamic CT. The optimal cut-off values for CT ratio and tumor size were determined using p-values that were calculated using the log-rank test.

RESULTS

The optimal cut-off values of CT ratio and tumor size for dividing patients into groups according to the greatest difference in disease-free survival (DFS) were 0.85 (p < 0.001) and 3.0 cm (p < 0.001), respectively. In analysis using Spearman's correlation coefficient, CT ratio (p = 0.007) and tumor size (p = 0.003) were individually associated with the Ki-67 proliferative index. Cox proportional hazard analysis identified that a CT ratio <0.85 (n = 10, p = 0.006) and tumor size ≥3.0 cm (n = 13, p = 0.023) were independent prognostic factors associated with DFS. All patients in the CT ratio ≥0.85 and tumor size <3.0 cm group (n = 23, including seven patients with G2 disease) did not develop recurrence after surgery. On the other hand, 5-year DFS in the CT ratio <0.85 and tumor size ≥3.0 cm group (n = 5, including three patients with G2 disease) was zero.

CONCLUSIONS

PNETs with a CT ratio <0.85 and tumor size ≥3.0 cm should be considered as having a high risk of recurrence after pancreatectomy.

Neutrophil-lymphocyte ratio predicts survival in pancreatic neuroendocrine tumors

Although the prognostic role of neutrophil-lymphocyte ratio (NLR) has been confirmed in a variety of tumors, the prognostic role of NLR in pancreatic neuroendocrine tumors (PNETs) has not been examined. The present study was performed to assess the role of NLR as a prognostic factor in patients with PNETs. Clinical data were retrospectively retrieved from a single institution. The best cut-off value for baseline NLR levels was determined by the receiver operating characteristic (ROC) curve and area under the ROC curve. The primary event was overall survival and event times were assessed by the Kaplan-Meier method. Potential factors associated with the elevation of NLR in PNETs were examined. A total of 165 consecutive patients with pathologically confirmed PNETs were included in this study. The cutoff value of NLR was 2.4 by ROC curve (area under ROC curve, 0.70). NLR >2.4 was found to be a poor prognostic factor in the univariate and multivariate analyses. Patients with a NLR value >2.4 had a higher proportion of tumor size at >3 cm (P=0.001), TNM stage III or IV (P=0.019), and G2/G3 (P=0.003). We concluded that NLR is an independent predictor of overall survival for patients with PNETs. Aberrant elevation of NLR identifies high-risk patients with aggressive characteristics.

The ENETS/WHO grading system for neuroendocrine neoplasms of the gastroenteropancreatic system: a review of the current state, limitations and proposals for modifications

The understanding of neuroendocrine neoplasms has evolved significantly since their initial descriptions in the 1800s to early 1900s. In the gastroenteropancreatic system, this group of malignant tumors is subdivided into well and poorly differentiated neuroendocrine neoplasms based on morphologic, proliferative and biologic differences. However, it has become increasingly apparent that well-differentiated neuroendocrine tumors are not a homogeneous group. Attempting to better predict outcome of these tumors has been the motivation behind numerous proposed classification systems, the evolution of which culminated with the currently used system, the ENETS/WHO classification. Herein, we review the genesis of this classification system and some of its shortcomings. In addition, we discuss some of the most recent proposals that suggest modifications to the current system.

Validation of the 2010 WHO classification and a new prognostic proposal: A single centre retrospective study of well-differentiated pancreatic neuroendocrine tumours

BACKGOUND

In 2010, the World Health Organization (WHO) modified the classification for pancreatic neuroendocrine tumours (NETs). Recently, some modifications were proposed to improve its prognostic value. The aim of this study was to test the prognostic value of both the original and the modified 2010 WHO grading systems.

METHODS

One hundred and twenty consecutive patients surgically resected for well-differentiated NETs were evaluated in multivariate Cox regression models. Age, sex, hormonal status, size, lymph node ratio, stage, margin status and grading were evaluated in order to predict disease-free survival (DFS). Four models were evaluated: model 1: grading according to the 2010 WHO; model 2: modified grading with cut-off at 5% of the Ki-67 index; model 3: modified grading in which the G2 category was divided into two subgroups (2-5% and 5-20%) and model 4: the Ki-67 index as a continuous variable. Decision curve analysis (DCA) was carried out to evaluate the clinical utility of the various cut-offs.

RESULTS

All the grading systems remained independent factors in predicting DFS. Model 2 (c index = 0.814 and P = 0.012) and model 3 (c index = 0.865 and P = 0.015) showed higher predictive powers with respect to model 1 (c index = 0.799). Model 4 had a high predictive value (c index 0.848, P = 0.013). Decision curve analysis confirmed that biological behaviour represented the best prognostic parameter.

CONCLUSION

This study presented some limitations: single centre, retrospective design and a long period of enrolment. The result showed that, by increasing the cut-off of the G2 category to 5% or by creating two subgroups in the G2 category, it was possible to obtain a better stratification of patients.

Status quo of diagnosis and treatment of pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNETs) are clinically rare digestive system tumors, which are characterized by insidious onset, a high potential of malignant tendency and a high misdiagnosis rate. In recent years, with the gradual increase of incidence and the continuous improvement of clinical diagnosis level, the detection and diagnosis rates of PNETs have been constantly increasing. In view of their malignant potential, early diagnosis and surgical intervention are essential. Therefore, clinicians should raise their awareness of this disease so as to effectively improve the diagnosis and treatment.