ArticleEuropean radiology2020
Development and validation of an
Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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.
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.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis.BMC medical informatics and decision making · 2024Pooled it
- Development of a radiomic-clinical nomogram for prediction of survival in patients with diffuse large B-cell lymphoma treated with chimeric antigen receptor T cells.Journal of cancer research and clinical oncology · 2023Trial
- Radiomic analysis for predicting prognosis of colorectal cancer from preoperativeJournal of translational medicine · 2022Trial
- Can the BMI-based dose regimen be used to reduce injection activity and to obtain a constant image quality in oncological patients byEuropean journal of nuclear medicine and molecular imaging · 2021Trial
- Development and validation of a radiomics nomogram for predicting outcomes following combined radiotherapy and modern chemotherapy in early-stage extranodal nasal-type NK/T-cell lymphoma: a multicenter study.Annals of hematology · 2026Article
- Robust and interpretable deep learning system for prognostic stratification of extranodal natural killer/T-cell lymphoma.European journal of nuclear medicine and molecular imaging · 2025Article
- Metabolic parameter of baseline 18 F-FDG PET/CT with PINK models improve the prediction of treatment outcome in extranodal NK/T-cell lymphoma treated with P-GEMOX chemotherapy.Annals of hematology · 2025Article
- Development of a Radiomic-clinical Nomogram for Prediction of Survival in Patients with Nasal Extranodal Natural Killer/T-cell LymphomaCurrent medical imaging · 2025Article
- Development and validation of prognostic models based onAnnals of hematology · 2024Article
- Review
- Prognostic Value ofKorean journal of radiology · 2024Article
- Semiquantitative 2-[Frontiers in medicine · 2024Review
- PET-based radiomic feature based on the cross-combination method for predicting the mid-term efficacy and prognosis in high-risk diffuse large B-cell lymphoma patients.Frontiers in oncology · 2024Article
- Different hydration protocols for the quantification of healthy tissue uptake of half-doseQuantitative imaging in medicine and surgery · 2023Article
- Value of pre-treatmentEuropean journal of radiology open · 2023Article
- Multimodality imaging evaluation of primary testicular extranodal natural killer/T-cell lymphoma: two case reports.Frontiers in medicine · 2023Article
- Review
- Role of Radiomics-Based Baseline PET/CT Imaging in Lymphoma: Diagnosis, Prognosis, and Response Assessment.Molecular imaging and biology · 2022Review
- Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma.European journal of nuclear medicine and molecular imaging · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
objectivesTo identify an
methodsIn this retrospective study, a total of 110 ENKTL patients were divided into a training cohort (n = 82) and a validation cohort (n = 28). Forty-one features were extracted from pretreatment PET images of the patients. Least absolute shrinkage and selection operator (LASSO) regression was used to develop the radiomic signatures (R-signatures). A radiomics-based model was built and validated in the two cohorts and compared with a metabolism-based model.
resultsThe R-signatures were constructed with moderate predictive ability in the training and validation cohorts (R-signature
conclusionsRadiomic features derived from PET images can predict the outcomes of patients with ENKTL, but the performance of the radiomics-based model was inferior to that of the metabolism-based model. KEY POINTS: • The R-signatures calculated by using
Indexed as
Identifiers
What OpenQuestion holds
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.