ReviewLa Radiologia medica2021
Computed tomography-based radiomics approach in pancreatic tumors characterization.
Review in La Radiologia medica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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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.
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Who cites it
39 citing papers in PubMed, 59 citations in OpenAlex.
- Pancreatic Cystic Lesions: From Basic Knowledge to Recent Guidelines.Journal of clinical medicine · 2026Review
- Solid and cystic intrapancreatic accessory spleen: report of 10 cases in a single institution.Annals of medicine · 2025Article
- Radiomics analysis using machine learning to predict perineural invasion in pancreatic cancer.BMC cancer · 2025Article
- Preoperative Prediction of Perineural Invasion in Pancreatic Ductal Adenocarcinoma Using Machine Learning Radiomics Based on Contrast-Enhanced CT Imaging.Journal of imaging informatics in medicine · 2025Article
- Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single-center retrospective study in China.Journal of applied clinical medical physics · 2025Article
- A radiomics-based interpretable model to predict the pathological grade of pancreatic neuroendocrine tumors.European radiology · 2024Article
- An overview on multimodal imaging for the diagnostic workup of pleural mesothelioma.Japanese journal of radiology · 2024Review
- Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and Limits of Radiomics.Diagnostics (Basel, Switzerland) · 2023Review
- An Updated Review on Imaging and Staging of Anal Cancer-Not Just Rectal Cancer.Tomography (Ann Arbor, Mich.) · 2023Review
- Peritoneal Carcinosis: What the Radiologist Needs to Know.Diagnostics (Basel, Switzerland) · 2023Review
- Radiomics in colorectal cancer patients.World journal of gastroenterology · 2023Review
- Computed Tomography Urography: State of the Art and Beyond.Tomography (Ann Arbor, Mich.) · 2023Review
- Update on the Applications of Radiomics in Diagnosis, Staging, and Recurrence of Intrahepatic Cholangiocarcinoma.Diagnostics (Basel, Switzerland) · 2023Review
- Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics.Infectious agents and cancer · 2023Review
- Dose Reduction Strategies for Pregnant Women in Emergency Settings.Journal of clinical medicine · 2023Review
- Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications.Journal of clinical medicine · 2023Review
- Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence.Biology · 2023Review
- Diagnostic Management of Gastroenteropancreatic Neuroendocrine Neoplasms: Technique Optimization and Tips and Tricks for Radiologists.Tomography (Ann Arbor, Mich.) · 2023Review
- Radiomics in Lung Metastases: A Systematic Review.Journal of personalized medicine · 2023Review
- Immunotherapy Assessment: A New Paradigm for Radiologists.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics (or texture analysis) is a new imaging analysis technique that allows calculating the distribution of texture features of pixel and voxel values depend on the type of ROI (3D or 2D), their relationships in the image. Depending on the software, up to several thousand texture elements can be obtained. Radiomics opens up wide opportunities for differential diagnosis and prognosis of pancreatic neoplasias. The aim of this review was to highlight the main diagnostic advantages of texture analysis in different pancreatic tumors. The review describes the diagnostic performance of radiomics in different pancreatic tumor types, application methods, and problems. Texture analysis in PDAC is able to predict tumor grade and associates with lymphovascular invasion and postoperative margin status. In pancreatic neuroendocrine tumors, texture features strongly correlate with differentiation grade and allows distinguishing it from the intrapancreatic accessory spleen. In pancreatic cystic lesions, radiomics is able to accurately differentiate MCN from SCN and distinguish clinically insignificant lesions from IPMNs with advanced neoplasia. In conclusion, the use of the CT radiomics approach provides a higher diagnostic performance of CT imaging in pancreatic tumors differentiation and prognosis. Future studies should be carried out to improve accuracy and facilitate radiomics workflow in pancreatic imaging.
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Registered trials
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.