ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2022
[Comparison of Two-dimensional and Three-dimensional Features of Chest CT in the Diagnosis of Invasion of Pulmonary Ground Glass Nodules].
Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 1 citations in OpenAlex.
- Differentiating pulmonary sarcoidosis from mediastinal lymph node metastasis via conventional computed tomography features and quantitative imaging parameters: a retrospective study.Quantitative imaging in medicine and surgery · 2026Article
- Artificial intelligence-measured nodule mass for determining the invasiveness of neoplastic ground glass nodules.Quantitative imaging in medicine and surgery · 2024Article
- [Prediction of Lymph Node Metastasis of Mixed Ground-glass Nodules Based on Clinical Imaging Information].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023Article
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6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundAt present, more and more studies predict invasive adenocarcinoma (IAC) through three-dimensional features of pulmonary nodules, but few studies have confirmed that three-dimensional features have more advantages in diagnosing IAC than traditional two-dimensional features of pulmonary nodules. This study analyzed the differences of chest computed tomography (CT) features between IAC and minimally invasive adenocarcinoma (MIA) from three-dimensional and two-dimensional levels, and compared the ability of diagnosing IAC. The non-invasive adenocarcinoma group includes precursor glandular lesions (PGL) and minimally invasive adenocarcinoma (MIA).
methodsThe clinical data of 1,045 patients with ground glass opacity (GGO) from January to December 2019 were collected. Then the correlation between preoperative CT image characteristics and pathological results were analyzed retrospectively. The independent influencing factors for the identification of IAC were screened out according to two-dimensional and three-dimensional classification by multivariate Logistic regression and the cut-off point for the identification of IAC was found out through the receiver operating characteristic (ROC) curve. At last, the ability of diagnosing IAC was evaluated by Yoden index.
resultsThe diameter of nodule, the diameter of solid component, the diameter of mediastinal window nodule in two-dimensional factors, and the volume of nodule, the volume of solid part and the average CT value in three-dimensional factors were independent risk factors for the diagnosis of IAC. These factors were arranged by Yoden index: solid partial volume (0.601)>nodule volume (0.536)>solid component diameter (0.525)>nodule diameter (0.518)>mediastinal window nodule diameter (0.488)>proportion of solid component volume (0.471)>1-tumor disappearance ratio (TDR) (0.468)>consolidation tumor ratio (CTR) (0.394)>average CT value (0.380).
conclusionsThe CT features of three-dimensional are better than two-dimensional in the diagnosis of IAC, and the size of solid components is better than the overall size of nodules.
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