Differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma using magnetic resonance imaging: The value of contrast-enhanced and diffusion weighted imaging

A CT-based diagnostic nomogram and survival analysis for differentiating grade 3 pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas

Objective

To construct a CT-based diagnostic nomogram for distinguishing grade 3 pancreatic neuroendocrine tumors (G3 PNETs) from pancreatic ductal adenocarcinomas (PDACs) and assess their respective survival outcomes.

Methods

Patients diagnosed with G3 PNETs (n = 30) and PDACs (n = 78) through surgery or biopsy from two medical centers were retrospectively identified. Demographic and radiological information, including age, gender, tumor diameter, shape, margin, dilatation of pancreatic duct, and invasive behavior, were carefully collected. A nomogram was established after univariate and multivariate logistic regression analyses. The Kaplan-Meier survival was performed to analyze their survival outcomes.

Results

Factors with a p-value <0.05, including age, CA 19-9, pancreatic duct dilatation, irregular shape, ill-defined margin, pancreatic atrophy, combined pancreatitis, arterial/portal enhancement ratio, were included in the multivariate logistic analysis. The independent predictive factors, including age (OR, 0.91; 95% CI, 0.85-0.98), pancreatic duct dilatation (OR, 0.064; 95% CI, 0.01-0.32), and portal enhancement ratio (OR, 1,178.08; 95% CI, 5.96-232,681.2) were determined to develop a nomogram. The internal calibration curve and decision curve analysis demonstrate that the nomogram exhibits good consistency and discriminative capacity in distinguishing G3 PNETs from PDACs. Patients diagnosed with G3 PNETs exhibited considerably better overall survival outcomes compared to those diagnosed with PDACs (median survival months, 42 vs. 9 months, p < 0.001).

Conclusions

The nomogram model based on age, pancreatic duct dilatation, and portal enhancement ratio demonstrates good accuracy and discriminative ability effectively predicting the probability of G3 PNETs from PDACs. Furthermore, patients with G3 PNETs exhibit better prognosis than PDACs.

Apparent Diffusion Coefficient Values for Neuroendocrine Liver Metastases

RATIONALE AND OBJECTIVES

We aimed to investigate whether there are any differences in apparent diffusion coefficient (ADC) values obtained from liver metastases due to gastroenteropancreatic neuroendocrine tumors (GEP-NET) and adenocarcinomas.

MATERIALS AND METHODS

We included 54 patients with 167 liver metastases due to gastroenteropancreatic tumors. We divided the patients into two groups as liver metastases due to GEP-NETs (seven patients with 51 lesions, mean age: 48) and adenocarcinomas (47 patients with 116 lesions, mean age: 61.2). We used the independent samples t-test to compare the ADC and ADC_mean values of the two groups and performed a receiver-operating characteristic analysis.

RESULTS

ADC and ADC_mean values were significantly lower in the GEP-NET group compared with the adenocarcinoma group. Receiver-operating characteristic curve analysis showed a significant difference for ADC and ADC_mean values, and area under the curve values were 0.733 and 0.790, respectively. The cut-off values were 933x10^-6 mm²/s for ADC and 801x10^-6 mm²/s for ADC_mean. Diagnostic accuracies of ADC (Sensitivity = 80.2, Specificity = 64.7, PPV = 83.8, NPV = 58.9) and ADC_mean (Sensitivity = 63.8, Specificity = 82.4, PPV = 89.2, NPV = 50) were calculated in differentiating adenocarcinoma metastases from GEP-NET metastases.

CONCLUSION

The lower ADC and ADC_mean values of liver metastases suggest GEP-NET rather than adenocarcinomas. ADC and ADC_mean values obtained from liver metastases may be used to differentiate NETs from adenocarcinomas.

Current update on imaging for pancreatic neuroendocrine neoplasms

Pancreatic neuroendocrine neoplasms (panNEN) are a heterogeneous group of tumors with differing pathological, genetic, and clinical features. Based on clinical findings, they may be categorized into functioning and nonfunctioning tumors. Adoption of the 2017 World Health Organization classification system, particularly its differentiation between grade 3, well-differentiated pancreatic neuroendocrine tumors (panNET) and grade 3, poorly-differentiated pancreatic neuroendocrine carcinomas (panNEC) has emphasized the role imaging plays in characterizing these lesions. Endoscopic ultrasound can help obtain biopsy specimen and assess tumor margins and local spread. Enhancement patterns on computed tomography (CT) and magnetic resonance imaging (MRI) may be used to classify panNEN. Contrast enhanced MRI and diffusion-weighted imaging have been reported to be useful for characterization of panNEN and quantifying metastatic burden. Current and emerging radiotracers have broadened the utility of functional imaging in evaluating panNEN. Fluorine-18 fluorodeoxyglucose positron emission tomography (PET)/CT and somatostatin receptor imaging such as Gallium-68 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid–octreotate PET/CT may be useful for improved identification of panNEN in comparison to anatomic modalities. These new techniques can also play a direct role in optimizing the selection of treatment for individuals and predicting tumor response based on somatostatin receptor expression. In addition, emerging methods of radiomics such as texture analysis may be a potential tool for staging and outcome prediction in panNEN, however further investigation is required before clinical implementation.

Accuracy of quantitative diffusion-weighted imaging for differentiating benign and malignant pancreatic lesions: a systematic review and meta-analysis

BACKGROUND

A variety of imaging techniques can be used to evaluate diffusion characteristics to differentiate malignant and benign pancreatic lesions. The diagnostic performance of diffusion parameters has not been systematic assessed.

PURPOSE

We aimed to investigate the diagnostic efficacy of quantitative diffusion-weighted imaging (DWI) for pancreatic lesions.

METHODS

A literature search was conducted using the PubMed, Embase, and Cochrane Library databases for studies from inception to March 30, 2020, which involves the quantitative diagnostic performance of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in the pancreas. Studies were reviewed according to inclusion and exclusion criteria. The quality of articles was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUATAS-2). A bivariate random-effects model was used to evaluate pooled sensitivities and specificities. Univariable meta-regression analysis was used to test the effects of factors that contributed to the heterogeneity.

RESULTS

A total of 31 studies involving 1558 patients were ultimately eligible for data extraction. The lowest heterogeneity was found in specificity of perfusion fraction (f) with the I² value was 17.97% and Cochran p value was 0.28. However, high heterogeneities were found for the other parameters (all I² > 50%). There was no publication bias found in funnel plot (p = 0.30) for the apparent diffusion coefficient (ADC) parameter. The pooled sensitivities for ADC, f, pure diffusion coefficient (D), and pseudo diffusivity coefficient (D*) were 83%, 81%, 76%, and 84%, respectively. The pooled specificities for ADC, f, D, and D* were 87%, 83%, 69%, and 81% respectively. The areas under the curves for ADC, f, D, and D* were 0.92, 0.87, 0.79, and 0.87 respectively.

CONCLUSION

Quantitative DWI and IVIM have a good diagnostic performance for differentiating malignant and benign pancreatic lesions.

KEY POINTS

• IVIM has high sensitivity and specificity (84% and 83%, respectively) for differential diagnosis of pancreatic lesions, which is comparable to that of the ADC (83% and 87%, respectively). • The ADC has an excellent diagnostic performance for differentiating malignant from benign IPMNs (sensitivity, 0.83; specificity, 0.92); the f has the best diagnostic performance for differentiating pancreatic carcinoma from PNET (sensitivity, 0.85; specificity, 0.85). • For the ADC, using a maximal b value < 800 s/mm² has a higher diagnostic accuracy than ≥ 800 s/mm²; performing in a high field strength (3.0 T) system has a higher diagnostic accuracy than a low field strength (1.5 T) for pancreatic lesions.

Diagnostic performance of diffusion MRI for pancreatic ductal adenocarcinoma characterisation: A meta-analysis

PURPOSE

To assess the diagnostic performance of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) for characterising pancreatic ductal adenocarcinoma (PDAC).

METHOD

A literature search was performed through PubMed, Web of Science, the Cochrane Library, and Embase databases. The search date was updated to extend until 28 October 2020, with no starting time limitation. The pooled sensitivity and specificity were calculated using a bivariate random effects model. Summary receiver operating characteristic curves were constructed, and area under the curve (AUC) of each diffusion parameter was calculated. Subgroup and meta-regression analyses were performed to assess for heterogeneity. Study quality was assessed.

RESULTS

Twenty-nine studies involving 1579 participants were included, of which 26 evaluated the apparent diffusion coefficient (ADC) and eight evaluated IVIM, with five evaluating both ADC and IVIM. Pooled sensitivity and specificity of ADC were 83 % (95 % CI, 76 %-88 %, I² = 86 %) and 85 % (95 % CI, 79 %-90 %, I² = 77 %), respectively, and AUC was 0.91 (95 % CI, 0.88-0.93). The perfusion fraction had the highest diagnostic accuracy in the IVIM model; the pooled sensitivity, specificity, and AUC were 87 % (95 % CI, 81 %-92 %, I² = 45 %), 88 % (95 % CI, 77 %-94 %, I² = 57 %), and 0.93 (95 % CI, 0.91-0.95), respectively. The pooled sensitivity, specificity and AUC for the tissue diffusion coefficient were 74 % (95 % CI, 55 %-87 %, I² = 87 %), 69 % (95 % CI, 52 %-82 %, I² = 73 %), and 0.77 (95 % CI, 0.73-0.81), respectively. And the pooled sensitivity, specificity, and AUC for the pseudodiffusion coefficient were 89 % (95 % CI, 77 %-96 %, I² = 79 %), 74 % (95 % CI, 60 %-84 %, I² = 78 %), and 0.88(95 %CI,0.85-0.91), respectively. Meta-regression analyses revealed that study design (specificity, P＜0.01), region-of-interest delineation (sensitivity, P = 0.02;specificity, P = 0.03), field strength (sensitivity, P＜0.01), and thickness (sensitivity, P＜0.01; specificity, P = 0.01) were sources of ADC heterogeneity.

CONCLUSIONS

DWI and IVIM have comparable diagnostic power and good diagnostic performance for characterising PDAC.

Diffusion-weighted MRI versus FDG-PET/CT for diagnosing pancreatic cancer: an indirect comparison meta-analysis

BACKGROUND

Fluorodeoxyglucose positron emission tomography (FDG-PET)/computed tomography (CT) and diffusion-weighted magnetic resonance imaging (DWI or DW-MRI) are tools for the diagnosis of pancreatic cancer. However, comparison of their diagnostic performance remains unknown.

PURPOSE

To indirectly compare the diagnostic value of DWI and FDG-PET/CT in the detection of pancreatic cancer.

MATERIAL AND METHODS

A literature search of PubMed, Embase, and Cochrane Library electronic databases for articles published through May 2018 yielded 875 articles. For the meta-analysis, we included 26 studies evaluating the efficacy of DWI and FDG-PET/CT for determining pancreatic cancer with a total of 1377 patients. QUADAS (Quality Assessment of Diagnostic Accuracy Studies) was used to assess the study quality. Sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curves (AUC) with their 95% confidence intervals were calculated for each individual study.

RESULTS

There were no significant differences between DWI and FDG-PET/CT for sensitivity, specificity, PLR, NLR, or DOR, while DWI AUC was higher than that of FDG-PET/CT for the detection of pancreatic cancer.

CONCLUSION

The diagnostic value of both DWI and FDG-PET/CT were comparable and, hence, both techniques seem to be equally useful tools for the diagnosis of pancreatic cancer.

Pancreatic Neuroendocrine Neoplasm Invading the Entire Main Pancreatic Duct Diagnosed by a Preoperative Endoscopic Biopsy

A 78-year-old man was referred to our hospital for a detailed examination of a pancreatic tumor that filled the main pancreatic duct (MPD). The histological diagnosis of the endoscopic biopsy specimen was neuroendocrine tumor (NET) G3. The patient subsequently underwent total pancreatectomy. The histological diagnosis of the surgical specimen was also NET G3. This is the first report of a NET that occupied the MPD and was diagnosed by a preoperative endoscopic biopsy through the papilla of Vater. This case is a good example of a histopathological diagnostic method for pancreatic tumors invading the entire MPD.

Anatomic and Functional Imaging of Neuroendocrine Tumors

OPINION STATEMENT

Neuroendocrine tumors (NETs) can occur in a wide variety of organs and display a spectrum of pathologic behavior. Accurate and effective imaging is paramount to the diagnosis, staging, therapy, and surveillance of patients with NET. There have been continuous advancements in the imaging of NET which includes anatomic and functional techniques.

Grade 3 Pancreatic Neuroendocrine Tumors on MDCT: Establishing a Diagnostic Model and Comparing Survival Against Pancreatic Ductal Adenocarcinoma

OBJECTIVE. The purpose of this study is to establish a diagnostic model for differentiating grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs) and to analyze survival outcomes. MATERIALS AND METHODS. Twenty patients with G3 PNETs and 58 patients with PDACs confirmed by surgery or biopsy were retrospectively included. Demographic and radiologic information was collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model. An ROC curve was created to determine diagnostic ability. Kaplan-Meier survival analysis was performed. RESULTS. Patients with G3 PNETs were more likely to present with normal carbohydrate antigen (CA) 19-9 levels, normal pancreatic ducts, and round tumors with well-defined margins and higher portal enhancement ratios than were patients with PDAC (p < 0.05). After multivariate analysis, a normal CA 19-9 level (odds ratio, 0.0125; 95% CI, 0.0008-0.2036), round tumor shape (odds ratio, 0.0143; 95% CI, 0.0004-0.5461), and pancreatic duct dilation of 4 mm or less (odds ratio, 17.9804; 95% CI, 1.0098-320.1711) were independent predictors of G3 PNETs. The AUC of the ROC curve was 0.916, and sensitivity and specificity were 90.0% and 81.0%, respectively. Furthermore, patients with G3 PNETs had better overall survival than patients with PDACs. Among patients in the G3 PNET subgroup, patients with liver or lymph node metastases had worse overall survival than patients without metastases. CONCLUSION. A diagnostic model was established to differentiate G3 PNETs from PDACs. A normal CA 19-9 level, round tumor shape, and pancreatic duct dilation of 4 mm or less were factors that were strongly predictive of G3 PNET.

Differential and prognostic MRI features of gallbladder neuroendocrine tumors and adenocarcinomas

OBJECTIVES

To identify MRI features that are helpful for the differentiation of gallbladder neuroendocrine tumors (GB-NETs) from gallbladder adenocarcinomas (GB-ADCs) and to evaluate their prognostic values.

METHODS

Between January 2008 and December 2018, we retrospectively enrolled patients who underwent MRI for GB malignancy. Two radiologists independently assessed the MRI findings and reached a consensus. Significant MRI features, which distinguish GB-NETs from GB-ADCs, were identified. Cox regression analyses were performed to find MRI features that were prognostic for overall survival.

RESULTS

There were 63 patients with GB-NETs (n = 21) and GB-ADCs (n = 42). Compared with GB-ADCs, GB-NETs more frequently demonstrated the following MRI features: well-defined margins, intact overlying mucosa, and thick rim contrast enhancement and/or diffusion restriction (ps < 0.001). Liver metastases were more common and demonstrated thick rim contrast enhancement and diffusion restriction in GB-NETs (ps < 0.001). Lymph node (LN) metastasis showed thick rim diffusion restriction more often in GB-NETs than in GB-ADCs (p = 0.009). On quantitative analysis, the sizes of the GB mass and metastatic LNs in GB-NETs were larger than those in GB-ADCs (p = 0.002 and p = 0.010, respectively). The ratio of apparent diffusion coefficient values between the lesion and the spleen was lower in the GB mass, liver metastases, and LN metastases of GB-NETs than those of GB-ADCs (p < 0.001, p = 0.017, and p < 0.001, respectively). Survival analysis revealed that a large metastatic LN (hazard ratio 1.737; 95% confidence interval, 1.112-2.712) was the only poor prognostic factor (p = 0.015).

CONCLUSION

Several MRI features aided in differentiating between GB-NETs and GB-ADCs. A large metastatic LN was associated with poor survival.

KEY POINTS

• Compared with gallbladder adenocarcinomas (GB-ADCs), neuroendocrine tumors (GB-NETs) and their metastases to the liver and lymph nodes more frequently demonstrated a thick rim appearance on contrast-enhanced MRI and diffusion-weighted images. • The ratio of apparent diffusion coefficient values between the lesion and the spleen was significantly lower for the primary mass, liver metastases, and lymph node metastases of GB-NETs than for those of GB-ADCs. • A large metastatic lymph node was the only poor prognostic factor for overall survival in patients with GB-NETs and GB-ADCs.

Exploratory Study of Apparent Diffusion Coefficient Histogram Metrics in Assessing Pancreatic Malignancy

PURPOSE

To evaluate whole-lesion 3D-histogram apparent diffusion coefficient (ADC) metrics for assessment of pancreatic malignancy.

METHODS

Forty-two pancreatic malignancies (36 pancreatic adenocarcinoma [PDAC], 6 pancreatic neuroendocrine [PanNET]) underwent abdominal magnetic resonance imaging (MRI) with diffusion-weighted imaging before endoscopic ultrasound biopsy or surgical resection. Two radiologists independently placed 3D volumes of interest to derive whole-lesion histogram ADC metrics. Mann-Whitney tests and receiver operating characteristic analyses were used to assess metrics' diagnostic performance for lesion histology, T-stage, N-stage, and grade.

RESULTS

Whole-lesion ADC histogram metrics lower in PDACs than PanNETs for both readers (P ≤ .026) were mean ADC (area under the curve [AUC] = 0.787-0.792), mean of the bottom 10th percentile (mean_0-10) (AUC = 0.787-0.880), mean of the 10th-25th percentile (mean_10-25) (AUC = 0.884-0.917) and mean of the 25th-50th percentile (mean_25-50) (AUC = 0.829-0.829). For mean_10-25 (metric with highest AUC for identifying PDAC), for reader 1 a threshold > 0.94 × 10^-3 mm²/s achieved sensitivity 94% and specificity 83%, and for reader 2 a threshold > 0.82 achieved sensitivity 97% and specificity 67%. Metrics lower in nodal status ≥ N₁ than N₀ for both readers (P ≤ .043) were mean_0-10 (AUC = 0.789-0.822) and mean_10-25 (AUC = 0.800-0.822). For mean_10-25 (metric with highest AUC for identifying N₀), for reader 1 a threshold <1.17 achieved sensitivity 87% and specificity 67%, and for reader 2 a threshold <1.04 achieved sensitivity 87% and specificity 83%. No metric was associated with T-stage (P > .195) or grade (P > .215).

CONCLUSION

Volumetric ADC histogram metrics may serve as non-invasive biomarkers of pancreatic malignancy. Mean_10-25 outperformed standard mean for lesion histology and nodal status, supporting the role of histogram analysis.

Differentiation of hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinoma using contrast-enhanced computed tomography

Hypovascular pancreatic neuroendocrine tumors (hypo-PNETs) are often misdiagnosed as pancreatic ductal adenocarcinoma (PDAC). However, the treatment options and prognosis of PNETs and PDAC are substantially different. This retrospective study differentiated hypo-PNETs from PDAC using contrast-enhanced CT (CE-CT). Clinical data and CE-CT findings, including tumor location, size, boundary, pancreatic duct dilatation, local invasion or metastases, tumor contrast enhancement, and tumor-to-pancreas enhancement ratio, were compared between 39 PDACs and 18 hypo-PNETs. At CT imaging, hypo-PNETs showed a higher frequency of a well-defined margin and lower frequencies of pancreatic duct dilatation and local invasion or metastasis when compared with PDAC (p < 0.05 for all). The mean attenuation of hypo-PNETs at the arterial and portal venous phase was significantly higher than that of PDAC (p < 0.001, p = 0.003, respectively). Similar results were observed in tumor-to-pancreas enhancement ratio. Tumor attenuation and tumor-to-pancreas enhancement ratio at the arterial phase showed the largest area under the curve (AUC) of 0.888 and 0.812 with 83.3–88.9% of sensitivity and 61.6–77.0% of specificity. Pancreatic duct dilatation, local invasion or metastasis, and tumor attenuation at the portal venous phase also showed acceptable AUC (0.703–0.748). Thus CE-CT features, especially the enhancement degree at the arterial phases, may be useful for differentiating hypo-PNETs from PDAC using CE-CT.

The Levels of Tumor Markers in Pancreatic Neuroendocrine Carcinoma and Their Values in Differentiation Between Pancreatic Neuroendocrine Carcinoma and Pancreatic Ductal Adenocarcinoma

OBJECTIVES

The levels of tumor markers in pancreatic neuroendocrine carcinoma (PNEC) are unknown, and imaging findings of PNEC and pancreatic ductal adenocarcinoma (PDAC) have overlaps. In this study, we show the tumor markers in PNEC and evaluate their values for distinguishing PNEC from PDAC.

METHODS

Thirty-three cases of PDAC and 21 cases of PNEC were retrospectively evaluated. The demographic information and clinical data were reviewed.

RESULTS

Pancreatic neuroendocrine carcinoma was usually misdiagnosed (57.1%) as PDAC based on imaging findings. Abnormal carbohydrate antigen (CA) 19-9, carcinoembryonic antigen (CEA), and α-fetoprotein (AFP) were observed in 19.0% to 28.6% of PNECs. Abnormal CA 19-9 and CA 125 levels were more common in PDAC than in PNEC (P < 0.05). Higher level of AFP was more common in PNEC than in PDAC (33.3% vs 3.0%, P < 0.05). The cutoff value of CA 19-9 for detecting PNEC was calculated as 38.5 U/mL or less with 0.788 sensitivity and 0.800 specificity. Carbohydrate antigen 19-9 (odds ratio [OR], 22.9; 95% confidence interval [CI], 2.94-179.3), AFP (OR, 0.08; 95% CI, 0.012-0.564), and CA 125 (OR, 17.4; 95% CI, 1.13-267.3) were predictors in differentiating PDAC from PNEC.

CONCLUSIONS

Carbohydrate antigen 19-9, AFP, and CA 125 have potential for distinguishing hypovascularized PNEC from PDAC.

The differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma: the values of CT imaging features and texture analysis

BACKGROUND

Imaging findings for pancreatic neuroendocrine carcinoma (PNEC) and pancreatic ductal adenocarcinoma (PDAC) often overlap. The aim of this study was to demonstrate the value of computed tomography (CT) imaging features and texture analysis to differentiate PNEC from PDAC.

METHODS

Twenty-eight patients with pathologically-proved PDAC and 14 patients with PNEC were included in this study. CT imaging findings, including tumor boundary, size, enhancement degree, duct dilatation and parenchymal atrophy were used to compare PDAC and PNEC. CT texture features were extracted from CT images at the arterial and portal phases.

RESULTS

More PNEC than PDAC had well-defined margins (57.1% vs 25.0%, p = 0.04). Parenchymal atrophy was more common in PDAC than in PNEC (67.9% vs 28.1%, p = 0.02). CT attenuation values (HU) and contrast ratios of PNEC inthe arterial and portal phases were higher than those of PDAC (p < 0.05 or 0.01). Entropy was lower and uniformity was higher in PNEC compare to PDAC at the arterial phase (p < 0.05). Contrast ratio showed the highest area under curve (AUC) for differentiating PNEC from PDAC (AUC = 0.98-0.99). Entropy and uniformity also showed an acceptable AUC (0.71-0.72).

CONCLUSIONS

Our data indicate that CT imaging features, including tumor margin, enhanced degree and parenchymal atrophy, as well as texture parameters can aid in the differentiation of PNEC from PDAC.

Imaging of pancreatic neuroendocrine tumors: recent advances, current status, and controversies

INTRODUCTION

Recently, there have been a number of advances in imaging pancreatic neuroendocrine tumors (panNETs), as well as other neuroendocrine tumors (NETs), which have had a profound effect on the management and treatment of these patients, but in some cases are also associated with controversies. Areas covered: These advances are the result of numerous studies attempting to better define the roles of both cross-sectional imaging, endoscopic ultrasound, with or without fine-needle aspiration, and molecular imaging in both sporadic and inherited panNET syndromes; the increased attempt to develop imaging parameters that correlate with tumor classification or have prognostic value; the rapidly increasing use of molecular imaging in these tumors and the attempt to develop imaging parameters that correlate with treatment/outcome results. Each of these areas and the associated controversies are reviewed. Expert commentary: There have been numerous advances in all aspects of the imaging of panNETs, as well as other NETs, in the last few years. The advances are leading to expanded roles of imaging in the management of these patients and the results being seen in panNETs/GI-NETs with these newer techniques are already being used in more common tumors.