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Quantitative research of lung adenocarcinoma with pure ground-glass opacity on CT / 中华放射学杂志
Chinese Journal of Radiology ; (12): 836-841, 2018.
Article in Zh | WPRIM | ID: wpr-707995
Responsible library: WPRO
ABSTRACT
Objective To find the invasion-associated clinical and CT risk factors of lung adenocarcinoma presenting as pure ground glass opacity nodule (pGGN) and to calculate odds ratio valve of each independent risk factor, the total risk value(TRV) of each lesion and an alert value for the management of pGGN. Methods From January 2014 to December 2016, 265 patients with 274 lesions pathologically confirmed lung adenocarcinoma with pGGN on CT who had undergone curative resection were included. Patient′s clinical data and CT features of pGGN were collected. CT features included the location, size, density and edge of pGGN, bubble-like sign, intrinsic abnormal air-bronchogram and vascular changes, tumor-lung interface. All lesions were divided into preinvasive groups (74 lesions) and invasive groups (200 lesions) according to the histopathology. Quantitative data were compared between preinvasive and invasive groups using t test or variance analysis (ANOVA) or nonparametric test. Qualitative data were compared between two groups using chi-square test. Logistic regression analysis was performed to evaluate the clinical and imaging independent risk factors of invasiveness. Receiver operating characteristics curve analysis was used to get the optimal cutoff value (alert value) for lesion invasiveness. Results There were statistically significant differences in patient age, lesion size, bubble-like sign, abnormal air-bronchogram, intrinsic vascular changes and tumor-lung interface between preinvasive and invasive groups (P<0.05). Logistic regression analysis showed that bubble-like sign, abnormal air-bronchogram, tumor-lung interface and lesion size were independent risk factors of invasiveness of pGGN, the OR value and 95%CI were 2.145(1.157—3.977), 3.167(1.211—8.281), 3.253(1.444—7.324), 1.175(1.061—1.303), respectively. The ROC curve demonstrated the optimal cutoff of TRV for predicting invasiveness was 3.5 with the sensitivity of 85.5%and specificity of 69.0%. Conclusions TRV can predict the invasiveness of pGGN. Surgical treatment is recommended if TRV is≥3.5.
Key words
Full text: 1 Database: WPRIM Type of study: Prognostic_studies / Qualitative_research / Risk_factors_studies Language: Zh Journal: Chinese Journal of Radiology Year: 2018 Document type: Article
Full text: 1 Database: WPRIM Type of study: Prognostic_studies / Qualitative_research / Risk_factors_studies Language: Zh Journal: Chinese Journal of Radiology Year: 2018 Document type: Article