ArticleFrontiers in oncology2021
Radiomics-Based Texture Analysis of
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
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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
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 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
- Texture analysis of [European journal of nuclear medicine and molecular imaging · 2026Observational
- Texture Analysis of 68Ga-DOTATOC PET/CT Images for the Prediction of Outcome in Patients with Neuroendocrine Tumors.Biomedicines · 2025Article
- Role ofFrontiers in medicine · 2025Article
- Inter- and intra-tumoral heterogeneity on [EJNMMI reports · 2024Article
- Advancing Precision Medicine: Algebraic Topology and Differential Geometry in Radiology and Computational Pathology.Laboratory investigation; a journal of technical methods and pathology · 2024Review
- Review
- Article
- Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens.Diagnostics (Basel, Switzerland) · 2024Review
- Preoperative prediction of pituitary neuroendocrine tumor invasion using multiparametric MRI radiomics.Frontiers in oncology · 2024Article
- Prediction ofCancers · 2023Article
- Methodological evaluation of original articles on radiomics and machine learning for outcome prediction based on positron emission tomography (PET).Nuklearmedizin. Nuclear medicine · 2023Review
- Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis.Scientific reports · 2023Article
- Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs).Life (Basel, Switzerland) · 2023Review
- Spatial and temporal heterogeneity of digestive neuroendocrine neoplasms.Therapeutic advances in medical oncology · 2023Review
- CT-based radiomics for prediction of therapeutic response to Everolimus in metastatic neuroendocrine tumors.La Radiologia medica · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers.Diagnostics (Basel, Switzerland) · 2022Review
- Radiolabeled Somatostatin Analogues for Diagnosis and Treatment of Neuroendocrine Tumors.Cancers · 2022Review
- Improved risk stratification by PET-based intratumor heterogeneity in children with high-risk neuroblastoma.Frontiers in oncology · 2022Article
- Exploring CT Texture Parameters as Predictive and Response Imaging Biomarkers of Survival in Patients With Metastatic Melanoma Treated With PD-1 Inhibitor Nivolumab: A Pilot Study Using a Delta-Radiomics Approach.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeNeuroendocrine tumors (NET) are rare cancers with variable behavior. A better understanding of prognosis would aid individualized management. The aim of this hypothesis-generating pilot study was to investigate the prognostic potential of tumor heterogeneity and tracer avidity in NET using texture analysis (TA) of
methodsThe pretherapy
resultsMeasures of heterogeneity (higher kurtosis, higher entropy, and lower skewness) on coarse-texture scale CT and unfiltered PET images predicted shorter PFS (CT coarse kurtosis: p=0.05, PET entropy: p=0.01, PET skewness: p=0.03) and shorter OS (CT coarse kurtosis: p=0.05, PET entropy: p=0.01, PET skewness p=0.02). Conventional PET parameters such as SUV
conclusionThese preliminary data generate a hypothesis that radiomic analysis of neuroendocrine cancer on
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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.