ArticleOncoTargets and therapy2017
Pancreatic neuroendocrine neoplasms at magnetic resonance imaging: comparison between grade 3 and grade 1/2 tumors.
Article in OncoTargets and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 33 citations in OpenAlex.
- Preoperative prediction of pancreatic neuroendocrine tumors grade based on computed tomography, magnetic resonance imaging and endoscopic ultrasonography.Abdominal radiology (New York) · 2025Article
- Values of apparent diffusion coefficient in pancreatic cancer patients receiving neoadjuvant therapy.BMC cancer · 2024Article
- A Machine Learning Approach Using [Molecular imaging and biology · 2023Article
- The association between pain and WHO grade of pancreatic neuroendocrine neoplasms: A multicenter study.Cancer biomarkers : section A of Disease markers · 2023Article
- New frontiers in imaging including radiomics updates for pancreatic neuroendocrine neoplasms.Abdominal radiology (New York) · 2022Review
- Prediction of recurrence after surgery based on preoperative MRI features in patients with pancreatic neuroendocrine tumors.European radiology · 2022Article
- Nomogram for preoperative estimation of histologic grade in gastrointestinal neuroendocrine tumors.Frontiers in endocrinology · 2022Article
- Serotonin immunoreactive pancreatic neuroendocrine neoplasm associated with main pancreatic duct dilation: a recognizable entity with excellent long-term outcome.European radiology · 2021Article
- Review
- Prediction of Pancreatic Neuroendocrine Tumor Grading Risk Based on Quantitative Radiomic Analysis of MR.Frontiers in oncology · 2021Article
- Pancreatic neuroendocrine tumours: spectrum of imaging findings.Gland surgery · 2020Review
- Correlation Between Apparent Diffusion Coefficient Value on MRI and Histopathologic WHO Grades of Neuroendocrine Tumors.Journal of the Belgian Society of Radiology · 2020Article
- Application of Radiomics Analysis Based on CT Combined With Machine Learning in Diagnostic of Pancreatic Neuroendocrine Tumors Patient's Pathological Grades.Frontiers in oncology · 2020Article
- CD56 Expression Is Associated with Biological Behavior of Pancreatic Neuroendocrine Neoplasms.Cancer management and research · 2020Article
- CT radiomics may predict the grade of pancreatic neuroendocrine tumors: a multicenter study.European radiology · 2019Article
- Imaging of pancreatic neuroendocrine tumors: recent advances, current status, and controversies.Expert review of anticancer therapy · 2018Review
- Can histogram analysis of MR images predict aggressiveness in pancreatic neuroendocrine tumors?European radiology · 2018Article
- Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCOncotarget · 2017Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe grading of pancreatic neuroendocrine neoplasms (PanNENs) is associated with the choice of treatment strategy. The aim of this study is to identify the magnetic resonance imaging (MRI) features in differentiating pancreatic neuroendocrine tumors (PanNETs) grade 1/2 (G1/G2) and pancreatic neuroendocrine carcinoma grade 3 (PanNEC G3). PATIENTS AND
methodsA total of 59 patients with histologically proven PanNENs and who underwent pretreatment MRI were retrospectively analyzed. Tumor location, size, boundary, cystic or solid appearance, enhancement degree, pancreatic duct dilatation, metastases and MRI signal were evaluated. Apparent diffusion coefficients (ADCs) were measured on ADC maps. Receiver operating characteristic curve was used to determine the cut off values and the sensitivity and specificity of prediction. Spearman correlation and logistic regression analysis were adopted to identify the association between MRI features and pathological parameters.
resultsA total of 47 lesions were PanNETs G1/G2 and 12 lesions were PanNEC G3. G1/G2 tumors were more common with well-circumscribed border compared with PanNEC G3. Ill- defined boundary, big size, necrosis, low-moderate enhancement, pancreatic duct dilatation, metastases and high diffusion-weighted imaging (DWI) intensity were more common in PanNEC G3 than in PanNETs G1/G2. The ADC values of PanNEC G3 were also significantly lower compared with the PanNETs G1/G2 and normal pancreatic parenchyma. The cut off value of ADC was 0.95×10
conclusionMetastases and ADC value may have potential for differentiating PanNEC G3 from PanNETs G1/G2.
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