Use of CT radiomics to differentiate minimally invasive adenocarcinomas and invasive adenocarcinomas presenting as pure ground-glass nodules larger than 10 mm. Issue 141 (August 2021)

• Record Type: Journal Article
• Authors: Xiong, Ziqi; Jiang, Yining; Che, Siyu; Zhao, Wenjing; Guo, Yan; Li, Guosheng; Liu, Ailian; Li, Zhiyong
• Is Part Of: European journal of radiology. Issue 141(2021)
• Publication Date: 2021-08
• Subjects: GGN ground-glass nodule -- pGGN pure ground-glass nodule -- IASLC International Association for the Study of Lung Cancer -- ATS American Thoracic Society -- ERS European Respiratory Society -- AIS adenocarcinomas in situ -- MIA minimally invasive adenocarcinoma -- IA invasive adenocarcinoma -- DFS disease-free survival -- CT computed tomography -- ROI region of interest -- mCTv mean CT value after volumetric segmentation -- mCTv-Lcs mean CT value of the largest cross-section -- ICC inter- and intra- class correlation coefficient -- LASSO least absolute shrinkage and selection operator -- LR Logistic Regression -- SVM Support Vector Machine -- NBC Naive Bayesian Classifier -- KNN K-Nearest Neighbor -- DT Decision Tree -- RF Random Forest -- ROC receiver operator characteristic -- AUC area under the receiver operator characteristic curve -- CI confidence interval -- SEN sensitivity -- SPE specificity -- BA balanced accuracy -- GLCM gray level co-occurrence matrix -- NGTDM neighbouring gray tone difference matrix; Lung adenocarcinoma -- Pulmonary ground-glass nodules -- Machine learning -- Multidetector computed tomography; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2021.109772
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: Primary focus on pure ground-glass nodules larger than 10 mm. Application of CT radiomics to preliminarily determine the invasiveness of nodules. Comparison of the radiomics model with a standard CT model and a combined radiomics-standard CT model. Abstract: Purpose: This study aimed to develop a model based on radiomics features extracted from computed tomography (CT) images to effectively differentiate between minimally invasive adenocarcinomas (MIAs) and invasive adenocarcinomas (IAs) manifesting as pure ground-glass nodules (pGGNs) larger than 10 mm. Method: This retrospective study included patients who underwent surgical resection for persistent pGGN between November 2012 and June 2018 and diagnosed with MIAs or IAs. The patients were randomly assigned to the training and test cohorts. The correlation coefficient method and the least absolute shrinkage and selection operator (LASSO) method were applied to select radiomics features useful for constructing a model whose performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC). The radiomics model was compared to a standard CT model (shape, volume and mean CT value of the largest cross-section) and the combined radiomics-standard CT model using univariate and multivariate logistic regression analysis. Results: The radiomics model showed better discriminative ability (training AUC, 0.879; test AUC, 0.877) than the standard CT model (training AUC, 0.820; test AUC, 0.828). The combined model (training AUC, 0.879; test AUC, 0.870) did not demonstrate improved performance compared with the radiomics model. Radiomics_score was an independent predictor of invasiveness following multivariate logistic analysis. Conclusions: For pGGNs larger than 10 mm, the radiomics model demonstrated superior diagnostic performance in differentiating between IAs and MIAs, which may be useful to clinicians for diagnosis and treatment selection.