ArticleFrontiers in oncology2022
Radiomic Signatures for Predicting
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 5 of them syntheses 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
11 citing papers in PubMed, 5 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- Pooled it
- A Bayesian meta-analysis on MRI-based radiomics for predicting EGFR mutation in brain metastasis of lung cancer.BMC medical imaging · 2025Pooled it
- The potential of MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations: a systematic review and meta-analysis.Biomedical engineering online · 2025Pooled it
- A systematic review of brain metastases from lung cancer using magnetic resonance neuroimaging: Clinical and technical aspects.Journal of medical radiation sciences · 2024Pooled it
- Diagnostic accuracy of MRI-based radiomic features for EGFR mutation status in non-small cell lung cancer patients with brain metastases: a meta-analysis.Frontiers in oncology · 2024Pooled it
- MET alterations are enriched in lung adenocarcinoma brain metastases, defining a distinct biologic subtype.The Journal of clinical investigation · 2026Article
- Molecular testing and targeting for solid tumors with CNS metastases.Journal of neuro-oncology · 2025Review
- Predicting the T790M mutation in non-small cell lung cancer (NSCLC) using brain metastasis MR radiomics: a study with an imbalanced dataset.Discover oncology · 2024Article
- Multisequence MRI-based radiomics signature as potential biomarkers for differentiating KRAS mutations in non-small cell lung cancer with brain metastases.European journal of radiology open · 2024Article
- Radiomics for the non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to non-small cell lung cancer.Journal of neuro-oncology · 2023Article
- Current status and prospect of PET-related imaging radiomics in lung cancer.Frontiers in oncology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung cancer is the most common primary tumor metastasizing to the brain. A significant proportion of lung cancer patients show epidermal growth factor receptor ( Methods: Data from 162 patients with resected brain metastases originating from lung cancer (70 with mutant Results: The best-performing model was a combination of 10 features selected from multiple sequences (two from T1CE, five from T2WI, and three from T2 FLAIR) in both the training and test sets, resulting in classification area under the curve, accuracy, sensitivity, and specificity values of 0.85 and 0.81, 77.8% and 75.9%, 83.7% and 73.1%, and 73.8% and 78.6%, respectively. Conclusions: Radiomic signatures integrating multi-sequence MR images have the potential to noninvasively predict the
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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.