ArticleBMC medical imaging2025
Exploration of CT-based discrimination and diagnosis of various pathological types of ground glass nodules in the lungs.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Evaluation of benign and malignant pulmonary nodules based on clinical and contrast-enhanced computed tomography data: a multicenter study.Quantitative imaging in medicine and surgery · 2026Article
- Artificial intelligence construction: a review of the bridge between CT imaging features of lung ground-glass nodules adenocarcinoma and carcinogenic driver genes.Journal of cancer research and clinical oncology · 2026Review
- WTAM-YOLO: a YOLOv11-based method for pulmonary nodule detection.Scientific reports · 2026Article
- FAD-YOLO: a lightweight feature-refined and task-aligned framework for AIS-MIA discrimination on pulmonary CT.Frontiers in medicine · 2026Article
- Integrated CT Radiomics and Circulating Tumor Cell Analysis in Predicting Lung Adenocarcinoma Invasion: A Dual-Center Study with Implications for Personalized Treatment.OncoTargets and therapy · 2026Article
- Radiomics-machine learning model for predicting invasiveness of subcentimeter subsolid lung adenocarcinoma: a validation study with external cohort and SHAP interpretability.Frontiers in oncology · 2026Article
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3 authors.
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Abstract
purposeThis study aims to examine the diagnostic usefulness of CT imaging in distinguishing between various pathological forms of lung ground-glass nodules (GGNs).
methodsWe conducted a retrospective analysis on 210 patients with lung ground-glass nodules (GGNs) who received diagnosis and treatment at our hospital between January 2021 and May 2024. Every patient had comprehensive imaging and pathology investigations. Lesion size, three-dimensional ratio, two-dimensional ratio, size of solid components, form, spiculation, lobulation, and cavitation were studied across several pathological kinds of pulmonary ground-glass nodules (GGNs).
resultsOf the 210 patients, 51 were diagnosed with benign conditions, while 159 had malignant lesions distributed across AIS, MIA, and IAC. The imaging data revealed that pulmonary ground-glass nodules (GGNs) exhibiting spiculation, lobulation, cavitation, pleural indentation, irregular shape, and fuzzy borders were considerably more prevalent in the inflammatory group, atypical adenomatous hyperplasia (AAH) group, adenocarcinoma in situ (AIS) group, minimally invasive adenocarcinoma (MIA) group, and invasive adenocarcinoma (IAC) group. These differences were statistically significant (P < 0.05). Significant variations in lesion size and size of solid components were observed among the groups, with the inflammatory group having the smallest size, followed by the AAH group, AIS group, MIA group, and finally the IAC group (P < 0.05). Nevertheless, there were no statistically significant disparities in the three-dimensional ratio and two-dimensional ratio across the five groups (P > 0.05). The calculated areas under the curve for distinguishing pre-invasive lesions from MIA and MIA from IAC, depending on the size of solid components, were 0.705 and 0.814, respectively. These values indicate a high diagnostic accuracy.
conclusionA thorough examination of the CT imaging characteristics of ground-glass nodules is crucial for accurately distinguishing between various pathological forms of pulmonary GGNs.
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