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High-resolution computed tomography findings independently predict epidermal growth factor receptor mutation status in ground-glass nodular lung adenocarcinoma
- Source :
- World Journal of Clinical Cases
- Publication Year :
- 2021
-
Abstract
- BACKGROUND For lung adenocarcinoma with epidermal growth factor receptor (EGFR) gene mutation, small molecule tyrosine kinase inhibitors are more effective. Some patients could not obtain enough histological specimens for EGFR gene mutation detection. Specific imaging features can predict EGFR mutation status to a certain extent. AIM To assess the associations of EGFR mutations with high-resolution computerized tomography (HRCT) features in ground-glass nodular lung adenocarcinoma. METHODS This study retrospectively assessed patients with ground-glass nodular lung adenocarcinoma diagnosed between January 2011 and March 2017. EGFR gene mutations in exons 18-21 were detected. The patients were classified into mutant EGFR and wild-type groups, and general data and HRCT image characteristics were assessed. RESULTS Among 98 patients, 31 (31.6%) and 67 (68.4%) had mutated and wild-type EGFR in exons 18-21, respectively. Gender, age, smoking history, location of lesions, morphology, edges, borders, pleural indentations, and associations of nodules with bronchus and blood vessels were comparable in both groups (all P > 0.05). Patients with mutant EGFR had larger nodules than those with the wild-type (17.19 ± 6.79 and 14.37 ± 6.30 mm, respectively; P = 0.047). Meanwhile, the vacuole/honeycomb sign was more frequent in the mutant EGFR group (P = 0.011). The logistic regression prediction model included the combination of nodule size and vacuole/honeycomb sign (OR = 1.120, 95%CI: 1.023-1.227, P = 0.014) revealed a sensitivity of 83.9%, a specificity of 52.2% and an AUC of 0.698 (95%CI: 0.589-0.806; P = 0.002). CONCLUSION Nodule size and vacuole/honeycomb features could independently predict EGFR mutation status in ground-glass nodular lung adenocarcinoma.
- Subjects :
- Lung adenocarcinoma
Pathology
medicine.medical_specialty
High-resolution computed tomography
Lung
integumentary system
medicine.diagnostic_test
biology
business.industry
Epidermal growth factor receptor
Logistic model
Computed tomography
General Medicine
medicine.disease
medicine.anatomical_structure
Retrospective Study
Receiver operating characteristic analysis
Mutation (genetic algorithm)
medicine
biology.protein
Adenocarcinoma
business
Tomography
Subjects
Details
- ISSN :
- 23078960
- Volume :
- 9
- Issue :
- 32
- Database :
- OpenAIRE
- Journal :
- World journal of clinical cases
- Accession number :
- edsair.doi.dedup.....bafa505cf1850a16aa9d5e286a737fc6