Objective: To explore the application of texture analysis basing on computed tomography (CT) images in predicting lymph-node metastasis in patients with clinical stage IA lung adenocarcinoma. Methods: In total, 256 patients with clinical stage IA lung adenocarcinoma who had underwentgone preoperative CT examinations were enrolled. A total of 25 texture features using MaZda (version 4.6) software and conventional radiological features were extracted from raw CT data sets. Based on surgical results, patients were stratified into lymph node metastasis-positive and -negative groups. Independent-sample t-tests and Mann-Whitney U tests were used to compare continuous variables between the groups. Continuity-correction and chi(2) tests were used for categorical variable comparison. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of lymphnode metastasis. Results: In total, 256 clinical stage IA lung adenocarcinoma cases were proved by pathology: 39 (15.23%) cases with lymph-node metastasis (14 N1a, seven N1b, six N2a1, ten N2a2, and two N2b) and 217 (84.77%) cases without lymph-node metastasis. Univariate and multivariate logistic regression analyses demonstrated that total volume (OR 3.777, p=0.015), average CT value of whole tumor (OR 16.271, p<0.001), three texture parameters (mean OR 8.473, p<0.001; skewness OR 6.393, p=0.001; and entropy OR 0.343, p=0.049) were independent factors associated with lymph-node status. As such, early-stage lung adenocarcinoma with higher total volume (>4.05 cm(3)), average CT value of whole tumor (>-70 HU), mean (>133.79), entropy (>1.98), and lower skewness (<= 0.02) pointed to positive lymph-node metastasis. Conclusion: Texture parameters were independent factors associated with lymph-node status in clinical stage IA lung adenocarcinoma.