Enhancing identification of early-stage lung adenocarcinomas through solid component analysis of three-dimensional computed tomography images.

Abstract

As the role of segmentectomy expands in managing early-stage lung adenocarcinoma, precise preoperative assessments of tumor invasiveness via computed tomography become crucial. This study aimed to evaluate the effectiveness of solid component analysis of three-dimensional (3D) computed tomography images and establish segmentectomy criteria for early-stage lung adenocarcinomas. This retrospective study included 101 cases with adenocarcinoma diagnoses, with patients undergoing segmentectomy for clinical stage 0 or IA between 2012 and 2017. The solid component volume (3D-volume) and solid component ratio (3D-ratio) of tumors were calculated using 3D computed tomography. Additionally, based on two-dimensional (2D) computed tomography, the solid component diameter (2D-diameter) and solid component ratio (2D-ratio) were calculated. The area under the receiver-operating characteristic curve (AUC) was calculated for each method, facilitating predictions of mortality and recurrence within 5years. The AUC of each measurement was compared with those of invasive component diameter (path-diameter) and invasive component ratio (path-ratio) obtained through pathology analysis. The predictive performance of 3D-volume did not differ significantly from that of path-diameter, whereas 2D-diameter exhibited less predictive accuracy (AUC: 3D-volume, 2D-diameter, and path-diameter: 0.772, 0.624, and 0.747, respectively; 3D-volume vs. path-diameter: p = 0.697; 2D-diameter vs. path-diameter: p = 0.048). Results were similar for the solid component ratio (AUC: 3D-ratio, 2D-ratio, path-ratio: 0.707, 0.534, and 0.698, respectively; 3D-ratio vs. path-ratio: p = 0.882; 2D-ratio vs. path-ratio: p = 0.038). Solid component analysis using 3D computed tomography offers advantages in prognostic prediction for early-stage lung adenocarcinomas.