ArticleMilitary Medical Research2024
CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD.
Article in Military Medical Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Chest CT in the evaluation of chronic obstructive pulmonary disease: recommendations of Asian Society of Thoracic Radiology.The British journal of radiology · 2026Guideline
- Diagnostic performance and generalizability of a clinical-ultrasound radiomics model for predicting extrathyroidal extension in thyroid carcinoma: a retrospective study.Annals of medicine · 2026Article
- AI-assisted Radiomic Model for Cervical Cancer Recurrence Prediction: A Multicenter Retrospective Study with Experimental Validation.Radiology. Imaging cancer · 2026Article
- Predicting the progression risk of chronic obstructive pulmonary disease in high-risk individuals based on whole-lung radiomics and deep learning: a multicenter study.Journal of thoracic disease · 2026Article
- Lobar-level radiomic clustering reveals background lung changes associated with lung cancer risk: a new perspective for early screening.Insights into imaging · 2026Article
- Unfolding Immune Dysregulation in COPD: Identification of a Three-Gene Signature and Functional Validation ofInternational journal of molecular sciences · 2026Article
- Automated identification of chronic obstructive pulmonary disease and asthma using impulse oscillometry combined with quantitative computed tomography parameters and radiomics features.Journal of thoracic disease · 2026Article
- Radiomics differences between GOLD I-II and GOLD III-IV in patients with chronic obstructive pulmonary disease.Journal of thoracic disease · 2026Article
- Interpretable chronic obstructive pulmonary disease identification using chest X-ray radiomics: a multicenter study.Insights into imaging · 2026Article
- Nomogram based on quantitative lung CT features to identify cardiovascular disease in chronic obstructive pulmonary disease and predict prognosis.BMC medical imaging · 2026Article
- CT image-based machine learning models for predicting blood eosinophil levels in acute exacerbation of chronic obstructive pulmonary disease.BMC pulmonary medicine · 2026Article
- An interpretable machine learning model integrating clinical and CT radiomic features for the detection of interstitial lung disease in idiopathic inflammatory myopathies.Arthritis research & therapy · 2026Article
- Quantitative MRI Values for Atrial and Ventricular Parameters in Altitude-Dwelling Youth.Journal of magnetic resonance imaging : JMRI · 2026Article
- A clinical-radiomics nomogram based on multisequence MRI for predicting intraoperative vertebral artery injury in patients with primary cervical spine tumor: a diagnostic study.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- An Integrated QSM-Radiomics Nomogram With Clinical and Imaging Markers for Stratifying Cognitive Impairment in Hypertension.CNS neuroscience & therapeutics · 2026Article
- An applied study on the assessment of concomitant pulmonary hypertension in patients with chronic obstructive pulmonary disease based on whole-lung CT imaging histologic features.Journal of thoracic disease · 2026Article
- Development and validation of a nomogram for predicting postoperative bone nonunion in spinal tuberculosis patients.Frontiers in surgery · 2026Article
- Development and validation of a clinical-radiomics nomogram for differentiatingFrontiers in pediatrics · 2026Article
- Deep Learning Image Reconstruction Algorithm for Quantitative Assessment of Low-Dose Biphasic Chest CT in Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2026Article
- CT Radiomics-based machine learning approach for the invasiveness of pulmonary ground-glass nodules prediction.European journal of radiology open · 2025Article
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19 authors.
Funding
Abstract
backgroundComputed tomography (CT) plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease (COPD). This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients.
methodsThis retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group. The radiomic features of the whole lung volume were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic signature construction. A radiomic nomogram was established by combining the radiomic score and clinical factors. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive performance of the radiomic nomogram in the training, internal validation, and independent external validation cohorts.
resultsEighteen radiomic features were collected from the whole lung volume to construct a radiomic model. The area under the curve (AUC) of the radiomic model in the training, internal, and independent external validation cohorts were 0.888 [95% confidence interval (CI) 0.869-0.906], 0.874 (95%CI 0.844-0.904) and 0.846 (95%CI 0.822-0.870), respectively. All were higher than the clinical model (AUC were 0.732, 0.714, and 0.777, respectively, P < 0.001). DCA demonstrated that the nomogram constructed by combining radiomic score, age, sex, height, and smoking status was superior to the clinical factor model.
conclusionsThe intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.
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