Prognostic value of tumor-to-parenchymal contrast enhancement ratio on portal venous-phase CT in pancreatic neuroendocrine neoplasms

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.

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.

Radiologic tumor border can further stratify prognosis in patients with pancreatic neuroendocrine tumor

BACKGROUND AND OBJECTIVES

Pancreatic neuroendocrine tumor (PanNET), although rare in incidence, is increasing in recent years. Several clinicopathologic and molecular factors have been suggested for patient stratification due to the extensive heterogeneity of PanNETs. We aimed to discover the prognostic role of assessing the tumor border of PanNETs with pre-operative computed tomography (CT) images and correlate them with other clinicopathologic factors.

METHODS

The radiologic, macroscopic, and microscopic tumor border of 183 surgically resected PanNET cases was evaluated using preoperative CT images (well defined vs. poorly defined), gross images (expansile vs. infiltrative), and hematoxylin and eosin-stained slides (pushing vs. infiltrative). The clinicopathologic and prognostic significance of the tumor border status was compared with other clinicopathologic factors.

RESULTS

A poorly defined radiologic tumor border was observed in 65 PanNET cases (35.5 %), and were more frequent in male patients (P = 0.031), and tumor with larger size, infiltrative macroscopic growth pattern, infiltrative microscopic tumor border, higher tumor grade, higher pT category, lymph node metastasis, lymphovascular and perineural invasions (all, P < 0.001). Patients with PanNET with a poorly defined radiologic tumor border had significantly worse overall survival (OS) and recurrence-free survival (RFS; both, P < 0.001). Multivariable analysis revealed that PanNET with a poorly defined radiologic border is an independent poor prognostic factor for both OS (P = 0.049) and RFS (P = 0.027).

CONCLUSION

Pre-operative CT-based tumor border evaluation can provide additional information regarding survival and recurrence in patients with PanNET.

Accuracy and Prognostic Impact of Nodal Status on Preoperative Imaging for Management of Pancreatic Neuroendocrine Tumors: A Multi-Institutional Study

BACKGROUND

We sought to define the accuracy of preoperative imaging to detect lymph node metastasis (LNM) among patients with pancreatic neuroendocrine tumors (pNETs), as well as characterize the impact of preoperative imaging nodal status on survival.

METHODS

Patients who underwent curative-intent resection for pNETs between 2000 and 2020 were identified from eight centers. Sensitivity and specificity of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)-CT, and OctreoScan for LNM were evaluated. The impact of preoperative lymph node status on lymphadenectomy (LND), as well as overall and recurrence-free survival was defined.

RESULTS

Among 852 patients, 235 (27.6%) individuals had LNM on final histologic examination (hN1). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 12.4%, 98.1%, 71.8%, and 74.4% for CT, 6.3%, 100%, 100%, and 80.1% for MRI, 9.5%, 100%, 100%, and 58.7% for PET, 11.3%, 97.5%, 66.7%, and 70.8% for OctreoScan, respectively. Among patients with any combination of these imaging modalities, overall sensitivity, specificity, PPV, and NPV was 14.9%, 97.9%, 72.9%, and 75.1%, respectively. Preoperative N1 on imaging (iN1) was associated with a higher number of LND (iN1 13 vs. iN0 9, p = 0.003) and a higher frequency of final hN1 versus preoperative iN0 (iN1 72.9% vs. iN0 24.9%, p < 0.001). Preoperative iN1 was associated with a higher risk of recurrence versus preoperative iN0 (median recurrence-free survival, iN1→hN1 47.5 vs. iN0→hN1 92.7 months, p = 0.05).

CONCLUSIONS

Only 4% of patients with LNM on final pathologic examine had preoperative imaging that was suspicious for LNM. Traditional imaging modalities had low sensitivity to determine nodal status among patients with pNETs.

A nomogram to preoperatively predict the aggressiveness of non-functional pancreatic neuroendocrine tumors based on CT features

OBJECTIVES

To develop a nomogram to predict the aggressiveness of non-functional pancreatic neuroendocrine tumors (NF-pNETs) based on preoperative computed tomography (CT) features.

METHODS

This study included 176 patients undergoing radical resection for NF-pNETs. These patients were randomly divided into the training (n = 123) and validation sets (n = 53). A nomogram was developed based on preoperative predictors of aggressiveness of the NF-pNETs which were identified by univariable and multivariable logistic regression analysis. The aggressiveness of NF-pNETs was defined as a composite measure including G3 grading, N+, distant metastases, and/ or disease recurrence.

RESULTS

Altogether, the number of patients with highly aggressive NF-pNETs was 37 (30.08 %) and 15 (28.30 %) in the training and validation sets, respectively. Multivariable logistic regression analysis identified that tumor size, biliopancreatic duct dilatation, lymphadenopathy, and enhancement pattern were preoperative predictors of aggressiveness. Those variables were used to develop a nomogram with good concordance statistics of 0.89 and 0.86 for predicting aggressiveness in the training and validation sets, respectively. With a nomogram score of 59, patients with NF-pNETs were divided into low-aggressive and high-aggressive groups. The high-aggressive group had decreased overall survival (OS) and disease-free survival (DFS). Moreover, the nomogram showed good performance in predicting OS and DFS at 3, 5, and 10 years.

CONCLUSION

The nomogram integrating CT features helped preoperatively predict the aggressiveness of NF-pNETs and could potentially facilitate clinical decision-making.