Improving the preoperative diagnosis of invasive lung adenocarcinoma by combining multiplanar volume rendering (MPVR)-based solid component measurement with pathological analysis

Abstract

Background The early diagnosis of lung adenocarcinoma (LUAD) remains challenging. Multiplanar volume rendering (MPVR) has demonstrated good diagnostic performance; however, misclassification can still occur. This study investigated the pathological basis of MPVR misclassification and developed a model to improve the preoperative diagnosis of invasive adenocarcinoma (IAC). Methods A total of 799 patients with LUAD were retrospectively included in the study. Based on computed tomography (CT) appearance (part-solid nodule vs. pure ground-glass nodule) and pathological diagnosis, the patients were classified into four groups: the false-negative group (n=96), the true-negative group (n=122), the false-positive group (n=132), and true-positive group (n=449). Clinicoradiological and pathological characteristics were compared among groups. Multivariate logistic regression was used to identify independent predictors of IAC and develop a combined prediction model, which was evaluated using receiver operating characteristic curve analysis. Results Compared with the patients in the false-positive group, those in the true-positive group were older (58.0 vs. 49.0 years, P<0.001) and had larger MPVR-measured solid component diameters (8.2 vs. 4.9 mm, P<0.001). The patients in the false-negative group were also older than those in the true-negative group (P=0.008), and both the CT- and MPVR-measured solid component diameters differed significantly between these two groups (both P<0.05). Histopathological analysis showed that false-positive findings were primarily associated with dense tumor structures and fibrous septal thickening, while false-negative findings were predominantly observed in minimally invasive adenocarcinoma (MIA) or well-differentiated IAC with invasive components <2 mm. The combined model achieved area under the curve values of 0.816 [95% confidence interval (CI): 0.781–0.851] and 0.778 (95% CI: 0.712–0.844) in the training and test sets, respectively. Conclusions MPVR-measured solid components provide valuable information for distinguishing IAC from adenocarcinoma in situ and MIA. Integrating clinical characteristics and CT imaging features further improves the preoperative diagnosis of IAC and may facilitate individualized clinical decision-making.