ArticleThe European respiratory journal2021
Validation of the BRODERS classifier (Benign
Article in The European respiratory journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Deep learning in pulmonary nodule detection and segmentation: a systematic review.European radiology · 2025Pooled it
- Development and internal validation of a clinical nomogram incorporating quantitative CT features for predicting malignancy in pulmonary nodules ≤ 3 cm.BMC medical imaging · 2026Article
- Theoretical Clinical Utility of Advanced Practice Provider Use of an Artificial Intelligence Radiomics-based Tool for Pulmonary Nodule Evaluation and Management.CHEST pulmonary · 2026Article
- Radiomics to understand pre-treatment tumor biology for resectable non-small cell lung cancer.Frontiers in oncology · 2026Review
- Long-Term Prognosis of Resected Stage 1 Lung Adenocarcinoma With Radiomics, Regionality, and Histopathologic Correlation.CHEST pulmonary · 2025Article
- A predictive clinical-radiomics nomogram for early diagnosis of mesenteric arterial embolism based on non-contrast CT and biomarkers.Abdominal radiology (New York) · 2025Article
- From images to clinical insights: an educational review on radiomics in lung diseases.Breathe (Sheffield, England) · 2025Review
- Radiomics and artificial intelligence for risk stratification of pulmonary nodules: Ready for primetime?Cancer biomarkers : section A of Disease markers · 2025Review
- Development and validation of an integrated system for lung cancer screening and post-screening pulmonary nodules management: a proof-of-concept study (ASCEND-LUNG).EClinicalMedicine · 2024Article
- Assessment of interobserver concordance in radiomic tools for lung nodule classification, with a focus on BRODERS and SILA.Scientific reports · 2023Article
- Review
- Improving Lung Cancer Diagnosis with CT Radiomics and Serum Histoplasmosis Testing.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- The Intervention Probability Curve: Modeling the Practical Application of Threshold-Guided Decision-Making, Evaluated in Lung, Prostate, and Ovarian Cancers.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022Article
- Artificial Intelligence-based Radiomics in the Era of Immuno-oncology.The oncologist · 2022Review
- The impact of the lung EDRN-CVC on Phase 1, 2, & 3 biomarker validation studies.Cancer biomarkers : section A of Disease markers · 2022Article
- A model based on the quantification of complement C4c, CYFRA 21-1 and CRP exhibits high specificity for the early diagnosis of lung cancer.Translational research : the journal of laboratory and clinical medicine · 2021Article
- Radiomics in Lung Diseases Imaging: State-of-the-Art for Clinicians.Journal of personalized medicine · 2021Review
- Volumetric histograms-based analysis of apparent diffusion coefficients and standard uptake values for the assessment of pediatric sarcoma at staging: preliminary results of a PET/MRI study.La Radiologia medica · 2021Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
Abstract
introductionImplementation of low-dose chest computed tomography (CT) lung cancer screening and the ever-increasing use of cross-sectional imaging are resulting in the identification of many screen- and incidentally detected indeterminate pulmonary nodules. While the management of nodules with low or high pre-test probability of malignancy is relatively straightforward, those with intermediate pre-test probability commonly require advanced imaging or biopsy. Noninvasive risk stratification tools are highly desirable.
methodsWe previously developed the BRODERS classifier (Benign
resultsFor the entire Vanderbilt validation set (n=170, 54% malignant), the AUC was 0.87 (95% CI 0.81-0.92) for the Brock model and 0.90 (95% CI 0.85-0.94) for the BRODERS model. Using the optimal cut-off determined by Youden's index, the sensitivity was 92.3%, the specificity was 62.0%, the positive (PPV) and negative predictive values (NPV) were 73.7% and 87.5%, respectively. For nodules with intermediate pre-test probability of malignancy, Brock score of 5-65% (n=97), the sensitivity and specificity were 94% and 46%, respectively, the PPV was 78.4% and the NPV was 79.2%.
conclusionsThe BRODERS radiomic predictive model performs well on an independent dataset and may facilitate the management of indeterminate pulmonary nodules.
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Registered trials
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