Contrast-Enhanced Ultrasonography Findings Correlate with Pathologic Grades of Pancreatic Neuroendocrine Tumors

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.

Prediction of Pathological Grades of Pancreatic Neuroendocrine Tumors Based on Dynamic Contrast-Enhanced Ultrasound Quantitative Analysis

Objective: To investigate whether the dynamic contrast-enhanced ultrasound (DCE-US) analysis and quantitative parameters could be helpful for predicting histopathologic grades of pancreatic neuroendocrine tumors (pNETs). Methods: This retrospective study conducted a comprehensive review of the CEUS database between March 2017 and November 2021 in Zhongshan Hospital, Fudan University. Ultrasound examinations were performed by an ACUSON Sequioa unit equipped with a 3.5 MHz 6C−1 convex array transducer, and an ACUSON OXANA2 unit equipped with a 3.5 MHz 5C−1 convex array transducer. SonoVue® (Bracco Inc., Milan, Italy) was used for all CEUS examinations. Time intensity curves (TICs) and quantitative parameters of DCE-US were created by Vuebox® software (Bracco, Italy). Inclusion criteria were: patients with histopathologically proved pNETs, patients who underwent pancreatic B-mode ultrasounds (BMUS) and CEUS scans one week before surgery or biopsy and had DCE-US imaging documented for more than 2 min, patients with solid or predominantly solid lesions and patients with definite diagnosis of histopathological grades of pNETs. Based on their prognosis, patients were categorized into two groups: pNETs G1/G2 group and pNETs G3/pNECs group. Results: A total of 42 patients who underwent surgery (n = 38) or biopsy (n = 4) and had histopathologically confirmed pNETs were included. According to the WHO 2019 criteria, all pNETs were classified into grade 1 (G1, n = 10), grade 2 (G2, n = 21), or grade 3 (G3)/pancreatic neuroendocrine carcinomas (pNECs) (n = 11), based on the Ki−67 proliferation index and the mitotic activity. The majority of the TICs (27/31) of pNETs G1/G2 were above or equal to those of pancreatic parenchyma in the arterial phase, but most (7/11) pNETs G3/pNECs had TICs below those of pancreatic parenchyma from arterial phase to late phase (p < 0.05). Among all the CEUS quantitative parameters of DCE-US, values of relative rise time (rPE), relative mean transit time (rmTT) and relative area under the curve (rAUC) were significantly higher in pNETs G1/G2 group than those in pNETs G3/pNECs group (p < 0.05). Taking an rPE below 1.09 as the optimal cut-off value, the sensitivity, specificity and accuracy for prediction of pNETs G3/pNECs from G1/G2 were 90.91% [58.70% to 99.80%], 67.64% [48.61% to 83.32%] and 85.78% [74.14% to 97.42%], respectively. Taking rAUC below 0.855 as the optimal cut-off value, the sensitivity, specificity and accuracy for prediction of pNETs G3/pNECs from G1/G2 were 90.91% [66.26% to 99.53%], 83.87% [67.37% to 92.91%] and 94.72% [88.30% to 100.00%], respectively. Conclusions: Dynamic contrast-enhanced ultrasound analysis might be helpful for predicting the pathological grades of pNETs. Among all quantitative parameters, rPE, rmTT and rAUC are potentially useful parameters for predicting G3/pNECs with aggressive behavior.

Differential diagnosis between pancreatic solid pseudopapillary tumors and pancreatic neuroendocrine tumors based on contrast enhanced ultrasound imaging features

PURPOSES

To evaluate the application of contrast enhanced ultrasound (CEUS) in preoperatively differential diagnosis between pancreatic solid pseudopapillary tumors (SPTs) and pancreatic neuroendocrine tumors (pNETs).

PATIENTS AND METHODS

This retrospective study was approved by Institutional Review Board. Patients with surgical resection and histopathological diagnosis as SPTs and pNETs were included. All patients underwent B mode ultrasound (BMUS) and CEUS examinations within one week before surgical operation. On BMUS, the size, location, echogenicity, calcification, and margin of lesions were observed and recorded. On CEUS imaging, enhancement patterns, and enhancement degrees were recorded and analyzed. An independent t-test or Mann-Whitney U test was used for comparison between continuous variables. Chi-square test was used to compare the CEUS patterns.

RESULTS

From February 2017 to Dec 2022, patients diagnosed as SPTs (n = 39) and pNETs (n = 48) were retrospectively included. On BMUS, anechoic cystic changes (19/39, 48.72%) and hyperechoic calcification (14/39, 35.90%) are more commonly detected in SPTs (P = 0.000). On CEUS imaging, the majority of SPTs (27/39, 69.23%) showed hypo-enhancement in the arterial phase, while most of the pNETs (36/48, 75.00%) showed hyper- or iso-enhancement in the arterial phase (P = 0.000). In the venous phase, most of the SPTs (32/39, 82.05%) showed hypo-enhancement, while over half of pNETs (29/48, 60.42%) showed hyper- or iso-enhancement compared to pancreatic parenchyma (P = 0.001).

CONCLUSIONS

CEUS is a valuable and non-invasive imaging method to make preoperatively differential diagnoses between SPTs and pNETs.

Contrast-Enhanced Harmonic Endoscopic Ultrasound for Diagnosis of the Aggressiveness of Pancreatic Neuroendocrine Neoplasm

The purpose of this study is to clarify the associations between the enhancement patterns on contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) and the aggressiveness and prognosis of pancreatic neuroendocrine neoplasms (PanNENs). Patients who underwent CH-EUS and were pathologically diagnosed with PanNEN were included in this study. Patients were divided into three groups according to contrast-enhancement patterns on early-phase and late-phase imaging: “Group A”, vascular rich in both phases; “Group B”, vascular rich and vascular poor in early and late phases, respectively; “Group C”, vascular poor in both phases. Of 39 patients, 25 were assigned to Group A, 7 to Group B, and 7 to Group C. The median overall survival was not reached in Groups A and B and was 335 days in Group C (p < 0.001). The 1-year survival rates were 100% in Group A, 60% in Group B, and 43% in Group C. Patients in Group C showed the shortest overall survival among the three groups. The vascular-poor pattern on late-phase CH-EUS had the highest sensitivity, specificity, and accuracy for aggressive PanNENs among the patterns analyzed on CH-EUS and CECT (84.6%, 91.7%, and 89.2%, respectively). CH-EUS is useful for the diagnosis of and predicting the prognosis of PanNENs.