Work

From radiologic morphology to component proportion: a multicenter study on the progression and prognosis of lung adenocarcinoma with cystic airspaces

Year: 2026

Type: article

Abstract: BACKGROUND: Lung adenocarcinoma with cystic airspaces (LACA) poses clinical challenges due to its irregular morphology and uncertain biological behavior. We aimed to elucidate its progression and prognosis through radiologic morphology and component proportion. METHODS: This multicenter retrospective study included 378 patients with LACA confirmed by serial imaging and pathology. Among them, a subgroup of 86 patients with clear transformation of nodule from ground-glass opacity (GGO) to solidity was selected to identify progression phases and patterns. Clinicopathological features were compared across different progression phases and radiologic morphologies. Two imaging-based ratios -the cystic airspace-to-lesion ratio (CLR) and the solid component-to-lesion ratio (SLR)- were evaluated for their prognostic value. Kaplan-Meier curves and log-rank tests were used to analyze overall survival (OS) and recurrence-free survival (RFS). RESULTS: Four progression phases were identified, with higher progression phases correlating with advanced T/N stages, increased malignant features, and poorer prognosis. We discovered that LACA may originate from either pre-existing cystic airspaces or pure GGO, and identified eight distinct progression patterns. The walled and massed type showed similar progression and prognosis. Cox regression analyses identified high SLR, but not low CLR, as a significant independent risk factor for recurrence. SLR demonstrated a steady increase with progression, while CLR was low in both early and advanced phases. CONCLUSION: This study established a unified four-phase progression model for LACA encompassing different morphologies and delineated eight distinct progression patterns reflecting heterogeneous initiation pathways. It also highlighted SLR as a more reliable prognostic indicator than CLR. These findings provide insight into the clinical management of LACA.

Source: Cancer Imaging

DOI: 10.1186/s40644-026-01009-9