Preoperative Prognosis Prediction for Pathological Stage IA Lung Adenocarcinoma: 3D-Based Consolidation Tumor Ratio is Superior to 2D-Based Consolidation Tumor Ratio.
Authors
Affiliations (3)
Affiliations (3)
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, PR China (L.Z., H.D., Y.C., F.W., C.H., P.K., X.G., X.X.); Department of Radiology, Traditional Chinese Medical Hospital of Zhuji, Shaoxing, Zhejiang 311800, PR China (L.Z.).
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, PR China (L.Z., H.D., Y.C., F.W., C.H., P.K., X.G., X.X.).
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, PR China (L.Z., H.D., Y.C., F.W., C.H., P.K., X.G., X.X.). Electronic address: [email protected].
Abstract
The two-dimensional computed tomography measurement of the consolidation tumor ratio (2D-CTR) has limitations in the prognostic evaluation of early-stage lung adenocarcinoma: the measurement is subject to inter-observer variability and lacks spatial information, which undermines its reliability as a prognostic tool. This study aims to investigate the value of the three-dimensional volume-based CTR (3D-CTR) in preoperative prognosis prediction for pathological Stage IA lung adenocarcinoma, and compare its predictive performance with that of 2D-CTR. A retrospective cohort of 980 patients with pathological Stage IA lung adenocarcinoma who underwent surgery was included. Preoperative thin-section CT images were processed using artificial intelligence (AI) software for 3D segmentation. Tumor solid component volume was quantified using different density thresholds (-300 to -150 HU, in 50 HU intervals), and 3D-CTR was calculated. The optimal threshold associated with prognosis was selected using multivariate Cox regression. The predictive performance of 3D-CTR and 2D-CTR for recurrence-free survival (RFS) post-surgery was compared using receiver operating characteristic (ROC) curves, and the best cutoff value was determined. The integrated discrimination improvement (IDI) was utilized to assess the enhancement in predictive efficacy of 3D-CTR relative to 2D-CTR. Among traditional preoperative factors, 2D-CTR (cutoff value 0.54, HR=1.044, P=0.001) and carcinoembryonic antigen (CEA) were identified as independent prognostic factors for RFS. In 3D analysis, -150 HU was determined as the optimal threshold for distinguishing solid components from ground-glass opacity (GGO) components. The corresponding 3D-CTR (cutoff value 0.41, HR=1.033, P<0.001) was an independent risk factor for RFS. The predictive performance of 3D-CTR was significantly superior to that of 2D-CTR (AUC: 0.867 vs. 0.840, P=0.006), with a substantial enhancement in predictive capacity, as evidenced by an IDI of 0.038 (95% CI: 0.021-0.055, P<0.001). Kaplan-Meier analysis revealed that the 5-year RFS rate for the 3D-CTR >0.41 group was significantly lower than that of the ≤0.41 group (68.5% vs. 96.7%, P<0.001). The 3D-CTR based on a -150 HU density threshold provides a more accurate prediction of postoperative recurrence risk in pathological Stage IA lung adenocarcinoma, demonstrating superior performance compared to traditional 2D-CTR.