Current update on imaging for pancreatic neuroendocrine neoplasms

Segaran, Nicole; Devine, Catherine; Wang, Mindy; Ganeshan, Dhakshinamoorthy

doi:10.5306/wjco.v12.i10.897

Cited by 10 publications

(4 citation statements)

References 74 publications

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“…In most cases, MRI displayed iso‐low intensity on T1WI and iso‐high intensity on T2WI, and contrast‐enhanced CT exhibited iso‐low contrast in the arterial phase and iso‐high contrast in the portal phase in all cases 2 . Conversely, NET typically demonstrates hyperenhancement in the arterial phase and remains mildly hyperattenuating in the portal phase on contrast‐enhanced CT 52 . In our patient, we suspected NET as the lesion was relatively hypervascular on contrast‐enhanced CT.…”

Section: Discussionmentioning

confidence: 98%

Pancreatic hamartoma: Possibility of a preoperative diagnosis via endoscopic ultrasound–guided fine‐needle aspiration biopsy

Shintaku

Gokita

Oshima

et al. 2023

Diagnostic Cytopathology

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Endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNAB) is useful for preoperatively diagnosing various pancreatic tumors. Although there is a risk of complications, such as pancreatitis, this procedure achieves the crucial need of reducing unnecessary invasive surgery for benign lesions. Herein, we reported a surgically resected case of pancreatic hamartoma in the pancreatic head whose retrospective analysis revealed that the specimens obtained via EUS-FNAB contained hamartoma fragments. Pancreatic hamartoma is an extremely rare benign disease that is exceptionally difficult to diagnose before surgical resection owing to its rarity and lack of established imaging findings. To the best of our knowledge, the preoperative diagnosis of pancreatic hamartoma via EUS-FNAB specimens has not been reported to date. Herein, postoperative EUS-FNAB evaluation revealed a collection of pancreatic hamartoma lesions, although the initial diagnosis was pancreatic tissue with focal atrophy and fibrosis. Diagnosis using EUS-FNAB can be challenging owing to the very small sample size. If mature acini and ducts with fibrous stroma without islets are observed in the EUS-FNAB specimen, pancreatic hamartoma should be considered as a differential diagnosis. Thus, careful follow-up or reexamination of EUS-FNAB should be considered instead of surgery if a benign lesion is suspected preoperatively.

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Section: Discussionmentioning

confidence: 98%

Pancreatic hamartoma: Possibility of a preoperative diagnosis via endoscopic ultrasound–guided fine‐needle aspiration biopsy

Shintaku

Gokita

Oshima

et al. 2023

Diagnostic Cytopathology

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“…Vessels and bile ducts were excluded from the ROI as much as possible. For multiple tumors, the tumor with the largest diameter was selected as the representative [ 23 ].…”

Section: Methodsmentioning

confidence: 99%

A radiomics-based interpretable model to predict the pathological grade of pancreatic neuroendocrine tumors

Ye,

Fang,

Peng

et al. 2023

Eur Radiol

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Objectives To develop a computed tomography (CT) radiomics-based interpretable machine learning (ML) model to predict the pathological grade of pancreatic neuroendocrine tumors (pNETs) in a non-invasive manner. Methods Patients with pNETs who underwent contrast-enhanced abdominal CT between 2010 and 2022 were included in this retrospective study. Radiomics features were extracted, and five radiomics-based ML models, namely logistic regression (LR), random forest (RF), support vector machine (SVM), XGBoost, and GaussianNB, were developed. The performance of these models was evaluated using a time-independent testing set, and metrics such as sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC) were calculated. The accuracy of the radiomics model was compared to that of needle biopsy. The Shapley Additive Explanation (SHAP) tool and the correlation between radiomics and biological features were employed to explore the interpretability of the model. Results A total of 122 patients (mean age: 50 ± 14 years; 53 male) were included in the training set, whereas 100 patients (mean age: 48 ± 13 years; 50 male) were included in the testing set. The AUCs for LR, SVM, RF, XGBoost, and GaussianNB were 0.758, 0.742, 0.779, 0.744, and 0.745, respectively, with corresponding accuracies of 73.0%, 70.0%, 77.0%, 71.9%, and 72.9%. The SHAP tool identified two features of the venous phase as the most significant, which showed significant differences among the Ki-67 index or mitotic count subgroups (p < 0.001). Conclusions An interpretable radiomics-based RF model can effectively differentiate between G1 and G2/3 of pNETs, demonstrating favorable interpretability. Clinical relevance statement The radiomics-based interpretable model developed in this study has significant clinical relevance as it offers a non-invasive method for assessing the pathological grade of pancreatic neuroendocrine tumors and holds promise as an important complementary tool to traditional tissue biopsy. Key Points • A radiomics-based interpretable model was developed to predict the pathological grade of pNETs and compared with preoperative needle biopsy in terms of accuracy. • The model, based on CT radiomics, demonstrated favorable interpretability. • The radiomics model holds potential as a valuable complementary technique to preoperative needle biopsy; however, it should not be considered a replacement for biopsy.

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“…Endoscopic ultrasonography-guided fine-needle aspiration (EUS-FNA) is a more accurate method for obtaining PNET pathological grading prior to surgery, but it is a invasive examination and greatly affected by the location and depth of tumors [12,13]. Imaging examination plays a crucial role in diagnosing, localizing, staging, and evaluating the effectiveness of PNETs, and it aids in qualitatively and differentially diagnosing tumors [14]. Traditional imaging examinations, such as CT and MRI, can be utilized for the diagnosis of PNETs, but they offer limited information in reflecting the heterogeneity and predicting the pathological grading of tumors [15].…”

Section: Introductionmentioning

confidence: 99%

Preoperative prediction of pancreatic neuroendocrine tumor grade based on 68Ga-DOTATATE PET/CT

Ma,

Wang,

Tang

et al. 2023

Endocrine

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Objective To establish a prediction model for preoperatively predicting grade 1 and grade 2/3 tumors in patients with pancreatic neuroendocrine tumors (PNETs) based on 68Ga-DOTATATE PET/CT. Methods Clinical data of 41 patients with PNETs were included in this study. According to the pathological results, they were divided into grade 1 and grade 2/3. 68Ga-DOTATATE PET/CT images were collected within one month before surgery. The clinical risk factors and significant radiological features were filtered, and a clinical predictive model based on these clinical and radiological features was established. 3D slicer was used to extracted 107 radiomic features from the region of interest (ROI) of 68Ga-dotata PET/CT images. The Pearson correlation coefficient (PCC), recursive feature elimination (REF) based five-fold cross validation were adopted for the radiomic feature selection, and a radiomic score was computed subsequently. The comprehensive model combining the clinical risk factors and the rad-score was established as well as the nomogram. The performance of above clinical model and comprehensive model were evaluated and compared. Results Adjacent organ invasion, N staging, and M staging were the risk factors for PNET grading (p < 0.05). 12 optimal radiomic features (3 PET radiomic features, 9 CT radiomic features) were screen out. The clinical predictive model achieved an area under the curve (AUC) of 0.785. The comprehensive model has better predictive performance (AUC = 0.953). Conclusion We proposed a comprehensive nomogram model based on 68Ga-DOTATATE PET/CT to predict grade 1 and grade 2/3 of PNETs and assist personalized clinical diagnosis and treatment plans for patients with PNETs.

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Current update on imaging for pancreatic neuroendocrine neoplasms

Cited by 10 publications

References 74 publications

Pancreatic hamartoma: Possibility of a preoperative diagnosis via endoscopic ultrasound–guided fine‐needle aspiration biopsy

Pancreatic hamartoma: Possibility of a preoperative diagnosis via endoscopic ultrasound–guided fine‐needle aspiration biopsy

A radiomics-based interpretable model to predict the pathological grade of pancreatic neuroendocrine tumors

Preoperative prediction of pancreatic neuroendocrine tumor grade based on 68Ga-DOTATATE PET/CT

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