Construction and validation of a risk stratification model based on Lung-RADS® v2022 and CT features for predicting the invasive pure ground-glass pulmonary nodules in China

Construction and validation of a risk stratification model based on Lung-RADS® v2022 and CT features for predicting the invasive pure ground-glass pulmonary nodules in China

Abstract Objectives A novel risk stratification model based on Lung-RADS® v2022 and CT features was constructed and validated for predicting invasive pure ground-glass nodules (pGGNs) in China. Methods Five hundred and twenty-six patients with 572 pulmonary GGNs were prospectively enrolled and divid...

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Bibliographic Details
Main Authors: Qingcheng Meng, Tong Liu, Hui Peng, Pengrui Gao, Wenda Chen, Mengjia Fang, Wentao Liu, Hong Ge, Renzhi Zhang, Xuejun Chen
Format: Article
Language:English
Published: SpringerOpen 2025-03-01
Series:Insights into Imaging
Subjects:
Lung (ground glass nodule)
Tomography (X-Ray computed)
Lung reporting and data system
CT features
Online Access:https://doi.org/10.1186/s13244-025-01937-3
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https://doi.org/10.1186/s13244-025-01937-3

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