Trial reportRadiology. Imaging cancer2021
Radiomic Features at CT Can Distinguish Pancreatic Cancer from Noncancerous Pancreas.
Erratum issuedOpen access · diamondAbstract readRandomized Controlled Trial
In one paragraph
Trial report in Radiology. Imaging cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 papers, 3 of them syntheses that pooled it.
0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
3.5field-weighted citation impact, top 5% of its field
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 66 citations in OpenAlex.
- Diagnostic Performance of Artificial Intelligence in Detecting and Distinguishing Pancreatic Ductal Adenocarcinoma via Computed Tomography: A Systematic Review and Meta-Analysis.Journal of imaging informatics in medicine · 2026Pooled it
- Deep learning models for pancreatic cancer detection on CT: a meta-analysis.Frontiers in medicine · 2026Pooled it
- Accuracy of machine learning models for pre-diagnosis and diagnosis of pancreatic ductal adenocarcinoma in contrast-CT images: a systematic review and meta-analysis.Abdominal radiology (New York) · 2025Pooled it
- Pancreatic Cancer Early Detection Biomarkers for High-Risk Individuals: Insights From the PRECEDE Consortium.International journal of cancer · 2026Review
- A bibliometric analysis of the 100 most cited radiology papers on pancreatic diseases (1990-Present).Abdominal radiology (New York) · 2026Review
- Factors Associated with Stage at Diagnosis in Pancreatic Cancer: Implications for Precision Screening and Early Detection.Biomedicines · 2026Review
- Catching pancreatic cancer early: Are we there yet?Journal of the National Cancer Center · 2026Review
- Radiomics-Driven Machine Learning Models for Diagnosis of Pancreatic Adenocarcinoma.Iranian journal of medical sciences · 2026Article
- Pancreatic cancer diagnosis on unenhanced CT with deep learning for opportunistic diagnosis.Radiology advances · 2026Article
- Clinical Applications of Quantitative Imaging and Artificial Intelligence for Pancreatic Cance.Seminars in radiation oncology · 2025Review
- Early detection of pancreatic cancer on computed tomography: advancements with deep learning.Radiology advances · 2025Review
- Advancements in Radiomics-Based AI for Pancreatic Ductal Adenocarcinoma.Bioengineering (Basel, Switzerland) · 2025Review
- Review
- AI-Driven insights in pancreatic cancer imaging: from pre-diagnostic detection to prognostication.Abdominal radiology (New York) · 2025Review
- Radiomics in differential diagnosis of pancreatic tumors.European journal of radiology open · 2025Article
- Pancreas segmentation using AI developed on the largest CT dataset with multi-institutional validation and implications for early cancer detection.Scientific reports · 2025Article
- Article
- Review
- Radiomics in sporadic microsatellite instable, mismatch repair deficient and Lynch syndrome-associated pancreatic ductal adenocarcinoma: a pilot study.Frontiers in oncology · 2025Article
- Machine Learning-Based Radiomics for Differentiating Pancreatic Lesions: A Potential Tool to Enhance Clinical Decision-Making and Nursing Management.Journal of nursing management · 2025Article
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
9 authors at 2 institutions in 2 countries.
Po-Ting ChenFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).ORCID 0000-0002-8675-5863
Dawei ChangFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).
Huihsuan YenFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).ORCID 0000-0002-8687-5128
Kao-Lang LiuFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).
Su-Yun HuangFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).
Holger RothFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).
Ming-Shiang WuFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).
Wei-Chih LiaoFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).ORCID 0000-0001-5362-6953
Weichung WangFrom the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).
National Taiwan University · TWNvidia (United Kingdom) · GB
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose To identify distinguishing CT radiomic features of pancreatic ductal adenocarcinoma (PDAC) and to investigate whether radiomic analysis with machine learning can distinguish between patients who have PDAC and those who do not. Materials and Methods This retrospective study included contrast material-enhanced CT images in 436 patients with PDAC and 479 healthy controls from 2012 to 2018 from Taiwan that were randomly divided for training and testing. Another 100 patients with PDAC (enriched for small PDACs) and 100 controls from Taiwan were identified for testing (from 2004 to 2011). An additional 182 patients with PDAC and 82 healthy controls from the United States were randomly divided for training and testing. Images were processed into patches. An XGBoost (
Indexed as
Carcinoma, Pancreatic DuctalPancreatic NeoplasmsAgedHumansMalePancreasRetrospective StudiesTomography, X-Ray ComputedComputer Aided Diagnosis (CAD)Computer Applications-Detection/DiagnosisCTPancreas
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.