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Rationale and objectives <p>To investigate the performance of two diagnostic models based on CT-derived lung and mediastinum radiomics nomograms for identifying cardiovascular disease (CVD) in Chronic Obstructive Pulmonary Disease (COPD) patients.</p> Materials and methods <p>Hospitalized participants with COPD were retrospectively recruited between September 2015 and April 2023. Clinical data and visual coronary artery calcium score (CACS) were collected. Radiomics features of lung and mediastinum were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic model construction. We constructed 3 radiomics models, based on lung, mediastinum, and combined lung-and-mediastinum. Multivariate logistic regression model was used to establish radiomics nomograms. The performance of radiomics nomograms was evaluated by area under the ROC curve (AUC) and decision curve analysis (DCA).</p> Results <p>Of 686 COPD patients, 131 had a history of CVD. Age, neutrophilic granulocyte percentage, hematocrit and GOLD stage were independent clinical factors for CVD. 12 lung, and 6 mediastinum radiomic features were collected to construct the radiomics models. As the lung-and-mediastinum radiomics model included the same 6 features as the mediastinum model, finally 2 radiomics models were studied (lung, mediastinum). The 2 radiomics nomograms showed better discriminatory ability (AUC: 0.79, 95%CI [0.72, 0.86] for lung; 0.86, 95%CI [0.81, 0.92]) for mediastinum) than the clinical factors model (AUC: 0.71, 95%CI [0.64, 0.78]) and visual CACS (AUC: 0.65, 95%CI [0.57, 0.72]). DCA demonstrated the 2 radiomics nomograms outperformed the clinical factors and CACS across the majority of the range of reasonable threshold probabilities.</p> Conclusion <p>We developed chest CT-based nomograms to identify CVD in COPD patients, in particular based on mediastinum features, had better discriminatory power than clinical factors and visual CACS.</p> Trial registration <p>This retrospective study was approved by the institutional review boards at Second Affiliated Hospital of Naval Medical University, Tongji Hospital of Tongji University and Sir Run Run Shaw Hospital (ChiCTR2300069929 March 29, 2023). Retrospectively registered.</p>

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CT-Based radiomics nomogram of lung and mediastinal features to identify cardiovascular disease in chronic obstructive pulmonary disease: a multicenter study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月15日

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  • XiaoQing Lin,
  • TaoHu Zhou,
  • Jiong Ni,
  • XiuXiu Zhou,
  • Yu Guan,
  • Xin’ang Jiang,
  • Yi Xia,
  • FangYi Xu,
  • HongJie Hu,
  • Jie Li,
  • Jin Zhang,
  • Shiyuan Liu,
  • Rozemarijn Vliegenthart,
  • Li Fan

摘要

Rationale and objectives

To investigate the performance of two diagnostic models based on CT-derived lung and mediastinum radiomics nomograms for identifying cardiovascular disease (CVD) in Chronic Obstructive Pulmonary Disease (COPD) patients.

Materials and methods

Hospitalized participants with COPD were retrospectively recruited between September 2015 and April 2023. Clinical data and visual coronary artery calcium score (CACS) were collected. Radiomics features of lung and mediastinum were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic model construction. We constructed 3 radiomics models, based on lung, mediastinum, and combined lung-and-mediastinum. Multivariate logistic regression model was used to establish radiomics nomograms. The performance of radiomics nomograms was evaluated by area under the ROC curve (AUC) and decision curve analysis (DCA).

Results

Of 686 COPD patients, 131 had a history of CVD. Age, neutrophilic granulocyte percentage, hematocrit and GOLD stage were independent clinical factors for CVD. 12 lung, and 6 mediastinum radiomic features were collected to construct the radiomics models. As the lung-and-mediastinum radiomics model included the same 6 features as the mediastinum model, finally 2 radiomics models were studied (lung, mediastinum). The 2 radiomics nomograms showed better discriminatory ability (AUC: 0.79, 95%CI [0.72, 0.86] for lung; 0.86, 95%CI [0.81, 0.92]) for mediastinum) than the clinical factors model (AUC: 0.71, 95%CI [0.64, 0.78]) and visual CACS (AUC: 0.65, 95%CI [0.57, 0.72]). DCA demonstrated the 2 radiomics nomograms outperformed the clinical factors and CACS across the majority of the range of reasonable threshold probabilities.

Conclusion

We developed chest CT-based nomograms to identify CVD in COPD patients, in particular based on mediastinum features, had better discriminatory power than clinical factors and visual CACS.

Trial registration

This retrospective study was approved by the institutional review boards at Second Affiliated Hospital of Naval Medical University, Tongji Hospital of Tongji University and Sir Run Run Shaw Hospital (ChiCTR2300069929 March 29, 2023). Retrospectively registered.