Objective: To explore the value of high-resolution computed tomography (HR-CT) in pathological tissue subtypes and differentiation degree of lung adenocarcinoma (LUAD). Methods: A total of 64 patients with LUAD confirmed in the hospital were enrolled between April 2022 and April 2025, and all underwent HR-CT examination. The lesion characteristics in images were independently evaluated by two senior thoracic radiologists with double-blind method, including lesion sites, size, internal structure and relationship with adjacent structures. The clinical value of HR-CT in the diagnosis of pathological tissue subtypes and differentiation degree of LUAD was evaluated by multivariate Logistic regression analysis. Results: In terms of pathological tissue subtypes in the 64 patients by pathological examination: 32 cases with adenocarcinoma in situ (AIS), 15 cases with minimally invasive adenocarcinoma (MIA), 17 cases with invasive pulmonary adenocarcinoma (IPA). In terms of tissue differentiation degree: 12 cases with IASLC grading at grade 1, 33 cases at grade 2, 19 cases at grade 3. There were significant differences in lesion size, lobulation sign, spiculation sign, pleural indentation sign and vessel convergence sign among AIS group, MIA group and IPA group (P<0.05), There were also significant differences in the above indexes among grade 1 group, grade 2 group and grade 3 group (P<0.05). The results of multivariate Logistic regression analysis showed that lobulation sign, spiculation sign, pleural indentation sign and vessel convergence sign in HR-CT all could be applied to predict and evaluate pathological tissue subtypes and differentiation degree of LUAD (P<0.05). Conclusion: The imaging characteristics of HR-CT are significantly correlated with pathological tissue subtypes and differentiation degree of LUAD.