1. CT-based whole lung radiomics nomogram for identification of PRISm from non-COPD subjects
- Author
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TaoHu Zhou, Yu Guan, XiaoQing Lin, XiuXiu Zhou, Liang Mao, YanQing Ma, Bing Fan, Jie Li, ShiYuan Liu, and Li Fan
- Subjects
PRISm ,Radiomics ,Computed tomography ,Nomogram ,Diseases of the respiratory system ,RC705-779 - Abstract
Abstract Background Preserved Ratio Impaired Spirometry (PRISm) is considered to be a precursor of chronic obstructive pulmonary disease. Radiomics nomogram can effectively identify the PRISm subjects from non-COPD subjects, especially when during large-scale CT lung cancer screening. Methods Totally 1481 participants (864, 370 and 247 in training, internal validation, and external validation cohorts, respectively) were included. Whole lung on thin-section computed tomography (CT) was segmented with a fully automated segmentation algorithm. PyRadiomics was adopted for extracting radiomics features. Clinical features were also obtained. Moreover, Spearman correlation analysis, minimum redundancy maximum relevance (mRMR) feature ranking and least absolute shrinkage and selection operator (LASSO) classifier were adopted to analyze whether radiomics features could be used to build radiomics signatures. A nomogram that incorporated clinical features and radiomics signature was constructed through multivariable logistic regression. Last, calibration, discrimination and clinical usefulness were analyzed using validation cohorts. Results The radiomics signature, which included 14 stable features, was related to PRISm of training and validation cohorts (p
- Published
- 2024
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