Comparison of Two-dimensional and Three-dimensional Features of Chest CT
in the Diagnosis of Invasion of Pulmonary Ground Glass Nodules.
10.3779/j.issn.1009-3419.2022.102.39
- Author:
Hongya WANG
1
;
He YANG
1
;
Zicheng LIU
1
;
Liang CHEN
1
;
Xinfeng XU
1
;
Quan ZHU
1
Author Information
1. Department of Thoracic Surgery, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University,
Nanjing 210029, China.
- Publication Type:Journal Article
- Keywords:
Computed tomography;
Computer-generated 3D imaging;
Lung neoplasms;
Radiology;
Volume
- MeSH:
Humans;
Lung Neoplasms/pathology*;
Retrospective Studies;
Neoplasm Invasiveness;
Multiple Pulmonary Nodules/diagnostic imaging*;
Adenocarcinoma/pathology*
- From:
Chinese Journal of Lung Cancer
2022;25(10):723-729
- CountryChina
- Language:Chinese
-
Abstract:
BACKGROUND:At 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).
METHODS:The 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.
RESULTS:The 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).
CONCLUSIONS:The 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.
