ArticleJapanese journal of radiology2017
Is the combination of MR and CT findings useful in determining the tumor grade of pancreatic neuroendocrine tumors?
Article in Japanese journal of radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 32 citations in OpenAlex.
- Role of extracellular volume fraction determined by dual-layer spectral detector CT in predicting the tumor grade of pancreatic neuroendocrine neoplasms.Japanese journal of radiology · 2026Article
- Clinicopathological and molecular determinants of pancreatic neuroendocrine tumors: toward precision risk stratification.Journal of translational medicine · 2026Review
- Preoperative prediction of pancreatic neuroendocrine tumors grade based on computed tomography, magnetic resonance imaging and endoscopic ultrasonography.Abdominal radiology (New York) · 2025Article
- Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.BMC medical imaging · 2025Article
- Hypovascular insulinoma with reduced microvessel density on histopathology: a case report.Diabetology international · 2024Article
- Article
- Can solid pseudopapillary neoplasm of the pancreas without degeneration be diagnosed with imaging? a comparison study of the solid component of solid pseudopapillary neoplasm, neuroendocrine neoplasm, and ductal adenocarcinoma.Abdominal radiology (New York) · 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
- Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade.JCO clinical cancer informatics · 2021Article
- Magnetic resonance imaging radiomic analysis can preoperatively predict G1 and G2/3 grades in patients with NF-pNETs.Abdominal radiology (New York) · 2021Article
- Usefulness of texture analysis for grading pancreatic neuroendocrine tumors on contrast-enhanced computed tomography and apparent diffusion coefficient maps.Japanese journal of radiology · 2021Article
- Noncontrast Radiomics Approach for Predicting Grades of Nonfunctional Pancreatic Neuroendocrine Tumors.Journal of magnetic resonance imaging : JMRI · 2020Article
- Correlation between radiologic features on contrast-enhanced CT and pathological tumor grades in pancreatic neuroendocrine neoplasms.Journal of biomedical research · 2020Article
- Pancreatic Neuroendocrine Neoplasm Invading the Entire Main Pancreatic Duct Diagnosed by a Preoperative Endoscopic Biopsy.Internal medicine (Tokyo, Japan) · 2020Article
- Homogenously isoattenuating insulinoma on biphasic contrast-enhanced computed tomography: Little benefits of diffusion-weighted imaging for lesion detection.Oncology letters · 2018Article
- 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
- A Novel Observational Strategy for Nonfunctional Pancreatic Neuroendocrine Neoplasms With Texture Analysis: A Multicenter Retrospective Study.Cancer diagnosis & prognosisArticle
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo retrospectively elucidate the findings useful in determining the tumor grade of pancreatic neuroendocrine tumors (PNETs) by combined assessment of magnetic resonance (MR) and dynamic computed tomography (CT) images. MATERIALS AND
methodsEighty-nine patients with PNETs (96 lesions) were included, and classified as G1, 59; G2, 29; and G3, 8 lesions. Image analysis included lesion diameter, shape, enhancement pattern on arterial phase (AP) and delayed phase CT images, calcification, cystic portion, main pancreatic duct dilatation, signal-intensity on T1-, T2-weighted MR images, and appearance of apparent diffusion coefficient (ADC).
resultsSignificant differences among G1, G2, and G3 groups were noted in tumor maximal diameter (p < 0.0001), shape (p < 0.0001), enhancement pattern on AP image (p < 0.0001), cystic portion (p = 0.012), and ADC finding. In multivariate analysis, ADC finding was the independent factor (p = 0.002). The combination findings of low ADC ratio (ADC value of the lesion/ADC value of the parenchyma <0.94), not homogeneous hyper-attenuation, lobulated shape, and hyper-intensity on T2-weighted image were suggestive of G2 or G3 with a probability of 100%. Conversely, all lesions with high ADC ratio and small size (≤25 mm) belonged to the G1 group.
conclusionCombined assessment of MR and CT findings could improve the prediction of tumor grading in PNETs.
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