ArticleJCO clinical cancer informatics2021
Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade.
Article in JCO clinical cancer informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.
- Predicting histologic grades for pancreatic neuroendocrine tumors by radiologic image-based artificial intelligence: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- GEP-NET radiomics: a systematic review and radiomics quality score assessment.European radiology · 2022Pooled it
- Automated Radiomics Model for Preoperative Pancreatic Neuroendocrine Tumor Grade Prediction.Annals of surgical oncology · 2026Article
- Multi-omic profiles of neuroendocrine neoplasms of the pancreas: an integrated landscape.Molecular cancer · 2026Review
- Development and validation of a CT-based nomogram to preoperative prediction of pancreatic neuroendocrine tumors (pNETs) grade.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
- Multi-channel multiphase CT-based deep learning and radiomics fusion model for noninvasive pathological grading of clear cell renal cell carcinoma.Frontiers in oncology · 2025Article
- Radiomics in sporadic microsatellite instable, mismatch repair deficient and Lynch syndrome-associated pancreatic ductal adenocarcinoma: a pilot study.Frontiers in oncology · 2025Article
- Radiomics and outcome prediction to antiangiogenic treatment in advanced gastroenteropancreatic neuroendocrine tumours: findings from the phase II TALENT trial.BJC reports · 2023Article
- A novel tool to predict nodal metastasis in small pancreatic neuroendocrine tumors: A multicenter study.Surgery · 2022Article
Corrections and comments
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Authors and funding
15 authors at 3 institutions in 2 countries.
Funding
Abstract
purposeThe therapeutic management of pancreatic neuroendocrine tumors (PanNETs) is based on pathological tumor grade assessment. A noninvasive imaging method to grade tumors would facilitate treatment selection. This study evaluated the ability of quantitative image analysis derived from computed tomography (CT) images to predict PanNET grade.
methodsInstitutional database was queried for resected PanNET (2000-2017) with a preoperative arterial phase CT scan. Radiomic features were extracted from the primary tumor on the CT scan using quantitative image analysis, and qualitative radiographic descriptors were assessed by two radiologists. Significant features were identified by univariable analysis and used to build multivariable models to predict PanNET grade.
resultsOverall, 150 patients were included. The performance of models based on qualitative radiographic descriptors varied between the two radiologists (reader 1: sensitivity, 33%; specificity, 66%; negative predictive value [NPV], 63%; and positive predictive value [PPV], 37%; reader 2: sensitivity, 45%; specificity, 70%; NPV, 72%; and PPV, 47%). The model based on radiomics had a better performance predicting the tumor grade with a sensitivity of 54%, a specificity of 80%, an NPV of 81%, and a PPV of 54%. The inclusion of radiomics in the radiographic descriptor models improved both the radiologists' performance.
conclusionCT quantitative image analysis of PanNETs helps predict tumor grade from routinely acquired scans and should be investigated in future prospective studies.
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