Background: Many delayed diagnoses of lung adenocarcinoma (LADC) are identified due to poor understanding of protean imaging findings. Moreover, clarifying the relationship between computed tomography (CT) morphological classification and epidermal growth factor receptor (EGFR) mutations of LADC might inform therapeutic decision-making while obtaining pathological specimens is difficult. Here, we retrospectively analyzed CT manifestations of LADC and investigated the morphological classification of tumors in relation to EGFR mutation status.
Methods: We included 1075 LADC patients undergoing chest CT and EGFR genotype examinations from January 2013 to January 2019. CT morphological characteristics of tumors were carefully evaluated and their correlation with EGFR mutation status was analyzed using the chi-squared test.
Results: Tumors were divided into eight types: I (peripheral solid nodule/mass; 526/1075, 48.93%), II (central solid nodule/mass; 220/1075, 20.47%), III (subsolid nodule/mass; 92/1075, 8.56%), IV (focal consolidation; 32/1075, 2.98%), V (cystic airspace; 14/1075, 1.30%), VI (multiple lesions with similar appearances to I–V; 85/1075, 7.91%), VII (diffuse consolidation; 53/1075, 4.93%), VIII (occult lesion usually obscured by nonobstructive atelectasis; 53/1075, 4.93%). Type III and IV tumors were more frequent in patients with EGFR mutation, whereas type II and VII tumors were more common in patients without EGFR mutation (all P < 0.05). However, we did not identify any significant associations between other tumor types and EGFR mutation status (all P > 0.05). Among patients with type VI tumors, EGFR mutation status was closely related to tumor density (all P < 0.05). Furthermore, type VII tumors were associated with 19 deletion mutation positive and non-L858R mutation positive (all P < 0.05).
Conclusion: LADC can be categorized into eight types based on CT imaging. Improving our understanding of the morphological classification and correlation with EGFR mutation status may contribute to the accurate diagnosis of LADC, while suggesting the presence of underlying EGFR genetic mutations.
Keywords: lung adenocarcinoma, morphology, computed tomography, epidermal growth factor receptor, mutation