Abstract
Background: The management of ground glass nodules (GGNs) remains a distinctive challenge. This study is aimed at comparing the predictive growth trends of radiomic features against current clinical features for the evaluation of GGNs.Methods: A total of 110 GGNs in 85 patients were included in this retrospective study, in which follow up occurred over a span ≥2 years. A total of 396 radiomic features were manually segmented by radiologists and quantitatively analyzed using an Analysis Kit software. After feature selection, three models were developed to predict the growth of GGNs. The performance of all three models was evaluated by a receiver operating characteristic (ROC) curve. The best performing model was also assessed by calibration and clinical utility.Results: After using a stepwise multivariate logistic regression analysis and dimensionality reduction, the diameter and five specific radiomic features were included in the clinical model and the radiomic model. The rad-score [odds ratio (OR) = 5.130; P < 0.01] and diameter (OR = 1.087; P < 0.05) were both considered as predictive indicators for the growth of GGNs. Meanwhile, the area under the ROC curve of the combined model reached 0.801. The high degree of fitting and favorable clinical utility was detected using the calibration curve with the Hosmer-Lemeshow test and the decision curve analysis was utilized for the nomogram.Conclusions: A combined model using the current clinical features alongside the radiomic features can serve as a powerful tool to assist clinicians in guiding the management of GGNs.
Highlights
The detection rate of pulmonary nodules has been significantly increased since the introduction of low dose computed tomography (CT) screening, especially for the ground glass nodule (GGN) [1, 2]
The purpose of the current study is to compare the performance of clinical signatures and radiomic features in predicting the growth of GGNs and to build a clinical-radiomic nomogram to accurately predict the growth of GGNs
The inclusion criteria were as follows: [1] detected pulmonary nodules showed GGNs on non-enhanced CT thin-sectioned images; [2] the GGN diameter between 5 and 30 mm in the initial CT image; [3] there were more than two follow-up, thin-section CT examinations and the follow-up interval was longer than 2 years
Summary
The detection rate of pulmonary nodules has been significantly increased since the introduction of low dose CT screening, especially for the ground glass nodule (GGN) [1, 2]. The GGN, which includes pure and part-solid GGN, is defined as a hazy region of increased opacity on lung windows without obscurity to bronchial and vascular structures [3]. Long windows of follow-up are often required. This is a source of great anxiety for patients and their families. Several studies have sought to provide a greater diagnostic indicator for the growth of GGNs through the analysis of traditional imaging features, such as diameter and CT attenuation [10,11,12,13]. Distinguishing the growing GGNs from static GGNs using traditional quantitative CT imaging remains a distinctive challenge. The management of ground glass nodules (GGNs) remains a distinctive challenge.
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