A comparison of enhancement patterns on dynamic enhanced CT and survival between patients with pancreatic neuroendocrine tumors with and without intratumoral fibrosis

Recent developments in the diagnosis of pancreatic neuroendocrine neoplasms

INTRODUCTION

Pancreatic Neuroendocrine Neoplasms (PanNENs) are characterized by a highly heterogeneous clinical and biological behavior, making their diagnosis challenging. PanNENs diagnostic work-up mainly relies on biochemical markers, pathological examination, and imaging evaluation. The latter includes radiological imaging (i.e. computed tomography [CT] and magnetic resonance imaging [MRI]), functional imaging (i.e. 68Gallium [68 Ga]Ga-DOTA-peptide PET/CT and Fluorine-18 fluorodeoxyglucose [18F]FDG PET/CT), and endoscopic ultrasound (EUS) with its associated procedures.

AREAS COVERED

This review provides a comprehensive assessment of the recent advancements in the PanNENs diagnostic field. PubMed and Embase databases were used for the research, performed from inception to October 2023.

EXPERT OPINION

A deeper understanding of PanNENs biology, recent technological improvements in imaging modalities, as well as progresses achieved in molecular and cytological assays, are fundamental players for the achievement of early diagnosis and enhanced preoperative characterization of PanNENs. A multimodal diagnostic approach is required for a thorough disease assessment.

Prognostic value of CT-based radiomics in grade 1-2 pancreatic neuroendocrine tumors

BACKGROUND

Surgically resected grade 1-2 (G1-2) pancreatic neuroendocrine tumors (PanNETs) exhibit diverse clinical outcomes, highlighting the need for reliable prognostic biomarkers. Our study aimed to develop and validate CT-based radiomics model for predicting postsurgical outcome in patients with G1-2 PanNETs, and to compare its performance with the current clinical staging system.

METHODS

This multicenter retrospective study included patients who underwent dynamic CT and subsequent curative resection for G1-2 PanNETs. A radiomics-based model (R-score) for predicting recurrence-free survival (RFS) was developed from a development set (441 patients from one institution) using least absolute shrinkage and selection operator-Cox regression analysis. A clinical model (C-model) consisting of age and tumor stage according to the 8th American Joint Committee on Cancer staging system was built, and an integrative model combining the C-model and the R-score (CR-model) was developed using multivariable Cox regression analysis. Using an external test set (159 patients from another institution), the models' performance for predicting RFS and overall survival (OS) was evaluated using Harrell's C-index. The incremental value of adding the R-score to the C-model was evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS

The median follow-up periods were 68.3 and 59.7 months in the development and test sets, respectively. In the development set, 58 patients (13.2%) experienced recurrence and 35 (7.9%) died. In the test set, tumors recurred in 14 patients (8.8%) and 12 (7.5%) died. In the test set, the R-score had a C-index of 0.716 for RFS and 0.674 for OS. Compared with the C-model, the CR-model showed higher C-index (RFS, 0.734 vs. 0.662, p = 0.012; OS, 0.781 vs. 0.675, p = 0.043). CR-model also showed improved classification (NRI, 0.330, p < 0.001) and discrimination (IDI, 0.071, p < 0.001) for prediction of 3-year RFS.

CONCLUSIONS

Our CR-model outperformed the current clinical staging system in prediction of the prognosis for G1-2 PanNETs and added incremental value for predicting postoperative recurrence. The CR-model enables precise identification of high-risk patients, guiding personalized treatment planning to improve outcomes in surgically resected grade 1-2 PanNETs.

Pancreatic neuroendocrine tumor: prediction of tumor grades by radiomics models based on ultrasound images

OBJECTIVE

We aimed to investigate whether the radiomics analysis based on B-mode ultrasound (BMUS) images could predict histopathological tumor grades in pancreatic neuroendocrine tumors (pNETs).

METHODS

A total of 64 patients with surgery and histopathologically confirmed pNETs were retrospectively included (34 male and 30 female, mean age 52.4 ± 12.2 years). Patients were divided into training cohort (n = 44) and validation cohort (n = 20). All pNETs were classified into Grade 1 (G1), Grade 2 (G2), and Grade 3 (G3) tumors based on the Ki-67 proliferation index and the mitotic activity according to WHO 2017 criteria. Maximum relevance minimum redundancy, least absolute shrinkage and selection operator were used for feature selection. Receiver operating characteristic curve analysis was used to evaluate the model performance.

RESULTS

Finally, 18 G1 pNETs, 35 G2 pNETs, and 11 G3 pNETs patients were included. The radiomic score derived from BMUS images to predict G2/G3 from G1 displayed a good performance with an area under the receiver operating characteristic curve of 0.844 in the training cohort, and 0.833 in the testing cohort. The radiomic score achieved an accuracy of 81.8% in the training cohort and 80.0% in the testing cohort, a sensitivity of 0.750 and 0.786, a specificity of 0.833 and 0.833 in the training/testing cohorts. Clinical benefit of the score also exhibited superior usefulness of the radiomic score, as shown by the decision curve analysis.

CONCLUSIONS

Radiomic data constructed from BMUS images have the potential for predicting histopathological tumor grades in patients with pNETs.

ADVANCES IN KNOWLEDGE

The radiomic model constructed from BMUS images has the potential for predicting histopathological tumor grades and Ki-67 proliferation indexes in patients with pNETs.

Qualitative imaging features of pancreatic neuroendocrine neoplasms predict histopathologic characteristics including tumor grade and patient outcome

OBJECTIVES

To identify PanNEN imaging features associated with tumor grade and aggressive histopathological features.

METHODS

Associations between histopathological and imaging features of resected PanNEN were retrospectively tested. Histopathologic features included WHO grade, lymphovascular invasion (LVI), growth pattern (infiltrative, circumscribed), and intratumoral fibrosis (mature, immature). Imaging features included size, degree/uniformity of enhancement, progressive enhancement, contour, infiltrative appearance (infiltrative_im), calcifications, cystic components, tumor thrombus, vascular occlusion (VO), duct dilatation, and atrophy. Multinomial logistic regression analyses evaluated the magnitude of associations. Association of variables with outcome was assessed using Cox-proportional hazards regression.

RESULTS

133 patients were included. 3 imaging features (infiltrative_im, ill-defined contour [contour_ill], and VO) were associated with all histopathologic parameters and poor outcome. Increase in grade increased odds of contour_ill by 15.6 times (p = 0.0001, 95% CI 3.8-64.4). PanNEN with VO were 51.1 times (p = 0.0002, 6.5-398.6) more likely to demonstrate LVI. For PanNEN with contour_ill, infiltrative growth pattern was 51.3 times (p < 0.0001, 9.1-288.4), and fibrosis was 14 times (p = 0.0065, 2.1-93.7) more likely. Contour_ill was associated with decreased recurrence-free survival (p = 0.0003, HR 18.29, 3.83-87.3) and VO (p = 0.0004, HR6.08, 2.22-16.68) with decreased overall survival.

CONCLUSIONS

Infiltrative_im, contour_ill, and VO on imaging are associated with higher grade/histopathological parameters linked to tumor aggression, and poor outcome.

Preoperative assessment of microvessel density in nonfunctioning pancreatic neuroendocrine tumors (NF-PanNETs)

BACKGROUND

Hypervascularization is a typical feature of pancreatic neuroendocrine tumors, and it frequently allows their recognition at imaging studies. However, the density of microvessels in pancreatic neuroendocrine tumors changes according to their biological behavior, and a low microvessel density is associated with higher disease aggressiveness. The primary aim was to investigate the relationship between microvessel density and aggressiveness of nonfunctioning pancreatic neuroendocrine tumors. The secondary aim was to evaluate the ability of contrast-enhanced computed tomography and contrast-enhanced endoscopic ultrasound in predicting tumor microvessel density.

METHODS

The patients who underwent surgery for nonfunctioning pancreatic neuroendocrine tumors (n = 66) with an available preoperative contrast-enhanced computed tomography (n = 39) and/or contrast-enhanced endoscopic ultrasound (n = 37) performed at San Raffaele Hospital (2016-2020) were included. The tumor vascularization was assessed by CD-34 staining, contrast-enhanced computed tomography, and contrast-enhanced endoscopic ultrasound. Median microvessel density (165 microvessels/mm2) was chosen as the cutoff to define low microvessel density and high microvessel density.

RESULTS

The patients with a low microvessel density showed a significantly higher frequency of nodal metastases (P = .026), G2-G3 tumors (P = .022), and death domain-associated protein/α-thalassemia/mental retardation syndrome X-linked loss (P = .011) compared to patients with high microvessel density. The contrast-enhanced computed tomography tumor density in the arterial phase was significantly higher in patients with high microvessel density compared to those with low microvessel density (P = .016). The patients with a low microvessel density showed a significantly higher frequency of contrast-enhanced endoscopic ultrasound arterial hypoenhancement (P = .042) and late washout (P = .034). Contrast-enhanced computed tomography arterial hypoenhancement (P = .007) and contrast-enhanced endoscopic ultrasound late washout (P = .048) independently predicted a low microvessel density in the patients who underwent contrast-enhanced computed tomography and contrast-enhanced endoscopic ultrasound, respectively.

CONCLUSION

A low microvessel density represents a marker of aggressiveness in the patients with nonfunctioning pancreatic neuroendocrine tumors. Contrast-enhanced computed tomography and contrast-enhanced endoscopic ultrasound are reliable and easily available tools for preoperative assessment of microvessel density.

CT-based radiomics for prediction of therapeutic response to Everolimus in metastatic neuroendocrine tumors

AIM

To test radiomic approach in patients with metastatic neuroendocrine tumors (NETs) treated with Everolimus, with the aim to predict progression-free survival (PFS) and death.

MATERIALS AND METHODS

Twenty-five patients with metastatic neuroendocrine tumors, 15/25 pancreatic (60%), 9/25 ileal (36%), 1/25 lung (4%), were retrospectively enrolled between August 2013 and December 2020. All patients underwent contrast-enhanced CT before starting Everolimus, histological diagnosis, tumor grading, PFS, overall survival (OS), death, and clinical data collected. Population was divided into two groups: responders (PFS ≤ 11 months) and non-responders (PFS > 11 months). 3D segmentation was performed on whole liver of naïve CT scans in arterial and venous phases, using a dedicated software (3DSlicer v4.10.2). A total of 107 radiomic features were extracted and compared between two groups (T test or Mann-Whitney), radiomics performance assessed with receiver operating characteristic curve, Kaplan-Meyer curves used for survival analysis, univariate and multivariate logistic regression performed to predict death, and interobserver variability assessed. All significant radiomic comparisons were validated by using a synthetic external cohort. P < 0.05 is considered significant.

RESULTS

15/25 patients were classified as responders (median PFS 25 months and OS 29 months) and 10/25 as non-responders (median PFS 4.5 months and OS 23 months). Among radiomic parameters, Correlation and Imc1 showed significant differences between two groups (P < 0.05) with the best performance (internal cohort AUC 0.86-0.84, P < 0.0001; external cohort AUC 0.84-0.90; P < 0.0001). Correlation < 0.21 resulted correlated with death at Kaplan-Meyer analysis (P = 0.02). Univariate analysis showed three radiomic features independently correlated with death, and in multivariate analysis radiomic model showed good performance with AUC 0.87, sensitivity 100%, and specificity 66.7%. Three features achieved 0.77 ≤ ICC < 0.83 and one ICC = 0.92.

CONCLUSIONS

In patients affected by metastatic NETs eligible for Everolimus treatment, radiomics could be used as imaging biomarker able to predict PFS and death.

Prediction of recurrence after surgery based on preoperative MRI features in patients with pancreatic neuroendocrine tumors

OBJECTIVES

To investigate useful MRI features in pancreatic neuroendocrine tumor (PNET) patients for predicting recurrence and its timing after surgery.

METHODS

A total of 99 patients with PNET who underwent MRI and surgery from 2000 to 2018 were enrolled. Two radiologists independently assessed MRI findings, including size, location, margin, T1 and T2 signal intensity, enhancement patterns, common bile duct (CBD) or main pancreatic duct (MPD) dilatation, vascular invasion, lymph node enlargement, DWI, and ADC value. Imaging findings associated with recurrence and disease-free survival (DFS) were assessed using logistic regression analysis and Cox proportional hazard regression analysis.

RESULTS

The median follow-up period was 40.4 months, and recurrence after surgery occurred in 12.1% (12/99). Among them, 6 patients experienced recurrence within 1 year, and 9 patients experienced recurrence within 2 years after surgery. In multivariate analysis, major venous invasion (OR 10.76 [1.14-101.85], p = 0.04) was associated with recurrence within 1 year, and portal phase iso- to hypoenhancement (OR 51.89 [1.73-1557.89], p = 0.02), CBD or MPD dilatation (OR 10.49 [1.35-81.64], p = 0.03) and larger size (OR 1.05 [1.00-1.10], p = 0.046) were associated with recurrence within 2 years. The mean DFS was 116.4 ± 18.5 months, and the 5-year DFS rate was 85.7%. In multivariate analysis, portal phase iso- to hypoenhancement (HR 21.36 [2.01-197.77], p = 0.01), ductal dilatation (HR 5.22 [1.46-18.68], p = 0.01), major arterial invasion (HR 42.90 [3.66-502.48], p = 0.003), and larger size (HR 1.04 [1.01-1.06], p = 0.01) showed a significant effect on poor DFS.

CONCLUSION

MRI features, including size, enhancement pattern, vascular invasion, and ductal dilatation, are useful in predicting recurrence and poor DFS after surgery in PNET. Key Points • MRI features are useful for predicting prognosis in patients with PNET after surgery. • PV or SMV invasion (OR 10.49 [1.35-81.64], p = 0.04) was significantly associated with 1-year recurrence. • Portal phase iso- to hypoenhancement (HR 21.36), CBD or MPD dilatation (HR 5.22), arterial invasion (HR 42.90), and larger size (HR 1.04) had significant effects on poor DFS (p < 0.05).

Complementary role of computed tomography texture analysis for differentiation of pancreatic ductal adenocarcinoma from pancreatic neuroendocrine tumors in the portal-venous enhancement phase

Purpose

To assess the role of CT-texture analysis (CTTA) for differentiation of pancreatic ductal adenocarcinoma (PDAC) from pancreatic neuroendocrine neoplasm (PNEN) in the portal-venous phase as compared with visual assessment and tumor-to-pancreas attenuation ratios.

Methods

53 patients (66.1 ± 8.6y) with PDAC and 42 patients (65.5 ± 12.2y) with PNEN who underwent contrast-enhanced CT for primary staging were evaluated. Volumes of interests (VOIs) were set in the tumor tissue at the portal-venous phase excluding adjacent structures. Based on pyradiomics library, 92 textural features were extracted including 1st, 2nd, and higher order features, and then compared between PNEN and PDAC. The visual assessment classified tumors into hypo-, iso-, or hyperdense to pancreas parenchyma or into homogeneous/heterogeneous. Additionally, attenuation ratios between the tumors and the non-involved pancreas were calculated.

Results

8/92 (8.6%) highly significant (p < 0.005) discriminatory textural features between PDAC and PNEN were identified including the 1st order features “median,” “total energy,” “energy,” “10th percentile,” “90th percentile,” “minimum,” “maximum,” and the 2nd order feature “Gray-Level co-occurrence Matrix (GLCM) Informational Measure of Correlation (Imc2).” In PNEN, the higher order feature “GLSZM Small Area High Gray-Level Emphasis” proved significantly higher in G1 compared to G2/3 tumors (p < 0.05). The tumor/parenchyma ratios as well as the visual assessment into hypo-/iso-/hyperdense or homogeneous/heterogeneous did not significantly differ between PDAC and PNEN.

Conclusions

Our data indicate that CTTA is a feasible tool for differentiation of PNEN from PDAC and also of G1 from G2/3 PNEN in the portal-venous phase. Visual assessment and tumor-to-parenchyma ratios were not useful for discrimination.

Electronic supplementary material

The online version of this article (10.1007/s00261-020-02406-9) contains supplementary material, which is available to authorized users.

The prognostic value of multidetector CT features in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors

PURPOSE

To assess the prognostic value of multidetector CT in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors (PNETs).

METHOD

Seventy-one patients pathologically diagnosed with PNETs were retrospectively included. The clinical and imaging information was evaluated by two radiologists. The difference between well-differentiated and poorly differentiated PNETs was analyzed. Cox proportional hazards models were created to determine the risk factors for overall survival. Kaplan-Meier survival analyses with log-rank tests were used among different subgroups of patients with PNETs.

RESULTS

In the whole cohort, the median survival was 36 months, and the 5-year survival rate was 84.8 %. Patients with poorly differentiated PNETs were more likely to present with symptoms, abnormal tumor markers, larger diameters, irregular shapes, ill-defined margins, invasion into nearby tissues, liver and lymph node metastases, and lower enhancement ratio than those with well-differentiated PNETs (P < 0.05). In the multivariate analysis, lymph node metastases (hazard ratio: 21.52, P = 0.009) and a portal enhancement ratio less than 1.02 (hazard ratio: 30.89, P = 0.024) were significant factors for overall survival. Overall survival decreased with an ill-defined margin, irregular shape, poor differentiation, grade 3 disease, nonfunctional status, abnormal tumor marker levels, invasion into nearby tissues, lymph node and liver metastases, and lower enhancement ratio (log-rank P < 0.05).

CONCLUSIONS

Poorly differentiated PNETs were more aggressiveness than well-differentiated PNETs. Lymph node metastases and a portal enhancement ratio < 1.02 were independent prognostic factors for worse overall survival outcomes in patients with PNETs.

Differentiation of duodenal gastrointestinal stromal tumors from hypervascular pancreatic neuroendocrine tumors in the pancreatic head using contrast-enhanced computed tomography

PURPOSE

To determine useful contrast-enhanced computed tomography (CE-CT) features in differentiating duodenal gastrointestinal stromal tumors (duodenal GISTs) from hypervascular pancreatic neuroendocrine tumors in the pancreatic head (pancreatic head NETs).

METHODS

Seventeen patients with pathologically confirmed duodenal GISTs and 25 with pancreatic NETs underwent preoperative CE-CT. CT image analysis included tumor size, morphology, and contrast enhancement. Receiver operating characteristic curves were performed, and cutoff values were calculated to determine CT findings with high sensitivity and specificity.

RESULTS

CT imaging showed duodenal GISTs with higher frequencies of tumor central location close to the duodenum and a predominantly solid tumor type when compared with pancreatic head NETs (p < 0.05 for both). Duodenal GISTs were larger than pancreatic head NETs (3.3 ± 0.9 cm vs. 2.5 ± 1.1 cm, p = 0.03). Duodenal GISTs had significantly lower CT attenuation values (112.9 ± 17.9HU vs. 137.4 ± 32.1HU, p < 0.01) at the arterial phase and higher CT attenuation values at the delayed phase (94.3 ± 7.9HU vs. 84.9 ± 10.4HU, p < 0.01) when compared with pancreatic head NETs. A CT attenuation value of ≤ 135 HU at the arterial phase (30 s) was 76% sensitive, 94.1% specific, and 83.3% accurate for the diagnosis of duodenal GISTs, while a CT attenuation value of ≥ 89.5 HU at the delayed phase (120 s) was 93.3% sensitive, 81.8% specific, and 76.2% accurate for the diagnosis of duodenal GISTs.

CONCLUSION

Tumor central location, size, texture, and contrast enhancement are valuable characteristics for the differentiation between duodenal GISTs and hypervascular pancreatic head NETs during preoperative examination.

What Is New in the 2017 World Health Organization Classification and 8th American Joint Committee on Cancer Staging System for Pancreatic Neuroendocrine Neoplasms?

The diagnosis and management of pancreatic neuroendocrine neoplasms (NENs) have evolved significantly in recent years. There are several diagnostic and therapeutic challenges and controversies regarding the management of these lesions. In this review, we focus on the recent significant changes and controversial issues regarding the diagnosis and management of NENs and discuss the role of imaging in the multidisciplinary team approach.

Long-Term Follow-Up of Desmoid Fibromatosis Treated with PF-03084014, an Oral Gamma Secretase Inhibitor

BACKGROUND

Desmoid fibromatosis is a fibroblastic neoplasm driven by aberrations within the WNT pathway, exhibiting mutations in β-catenin or APC. We review the long-term follow-up of patients in a phase I study treated with an oral gamma secretase inhibitor, PF-03084014.

METHODS

PF-03084014 was administered orally at doses ranging from 20 to 330 mg twice daily. Tumor assessments were performed using computed tomography/magnetic resonance imaging (CT/MRI) within 4 weeks of study entry, and every other cycle through cycle 9. After cycle 9, patients were evaluated as clinically indicated.

RESULTS

Seven patients with desmoid fibromatosis were treated between December 2009 and December 2016 at the University of Colorado. Five patients (71.4%, 95% confidence interval [CI] 29.0-96.3%) achieved a partial response (PR), with a mean time to achieving response of 11.9 months (95% CI 2.5-21.4 months). All patients who achieved a PR continue to maintain responses between 47.9 and 73+ months. Four patients stopped treatment yet remain free of progression between 11 and 53+ months. One patient had PFS of 42+ months, with a 17% decrease in the target lesion. A biopsy performed at the end of the study showed decreased tumoral cellularity compared with previous biopsies. Effective treatment doses ranged from 80 to 330 mg administered orally twice daily.

CONCLUSIONS

PF-03084014 was effective in treating desmoid tumors, with an objective response rate of 71.4% (95% CI 29.0-96.3%) in this small cohort of patients. PF-03084014 exhibits promising activity, even at relatively low doses (80 mg twice daily), with high tolerability leading to prolonged disease control even after therapy discontinuation.