Bibliographic Details
| Title: |
The value of CT shape quantification in predicting pathological classification of lung adenocarcinoma |
| Authors: |
Mingjie guo, Zhan Cao, Zhichao Huang, Shaowen Hu, Yafei Xiao, Qianzhou Ding, Yalong Liu, Xiaokang An, Xianjie Zheng, Shuanglin Zhang, Guoyu Zhang |
| Source: |
BMC Cancer, Vol 24, Iss 1, Pp 1-7 (2024) |
| Publisher Information: |
BMC, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| Subject Terms: |
Lung adenocarcinoma, CT shape quantification, Pulmonary ground glass nodules, Prediction, Cut-off value, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| More Details: |
Abstract Objective To evaluate whether quantification of lung GGN shape is useful in predicting pathological categorization of lung adenocarcinoma and guiding the clinic. Methods 98 patients with primary lung adenocarcinoma were pathologically confirmed and CT was performed preoperatively, and all lesions were pathologically ≤ 30 mm in size. On CT images, we measured the maximum area of the lesion’s cross-section (MA). The longest diameter of the tumor (LD) was marked with points A and B, and the perpendicular diameter (PD) was marked with points C and D, which was the longest diameter perpendicular to AB. and D, which was the longest diameter perpendicular to AB. We took angles A and B as big angle A (BiA) and small angle A (SmA). We measured the MA, LD, and PD, and for analysis we derived the LD/PD ratio and the BiA/SmA ratio. The data were analysed using the chi-square test, t-test, ROC analysis, and binary logistic regression analysis. Results Precursor glandular lesions (PGL) and microinvasive adenocarcinoma (MIA) were distinguished from invasive adenocarcinoma (IAC) by the BiA/SmA ratio and LD, two independent factors (p = 0.007, p = 0.018). Lung adenocarcinoma pathological categorization was indicated by the BiA/SmA ratio of 1.35 and the LD of 11.56 mm with sensitivity of 81.36% and 71.79%, respectively; specificity of 71.79% and 74.36%, respectively; and AUC of 0.8357 (95% CI: 0.7558–0.9157, p |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1471-2407 |
| Relation: |
https://doaj.org/toc/1471-2407 |
| DOI: |
10.1186/s12885-023-11802-5 |
| Access URL: |
https://doaj.org/article/2d9c7bf4ad6a4362ba780d26981f0d50 |
| Accession Number: |
edsdoj.2d9c7bf4ad6a4362ba780d26981f0d50 |
| Database: |
Directory of Open Access Journals |
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