BACKGROUND: This study aimed to predict the malignant potential of clinical stage I non-small cell lung cancer (c-I NSCLC) by semiautomatic three-dimensional (3D) volumetric measurement of a tumor (3D-data) and the axial computed tomography (CT) data derived from a 3D volumetric dataset (2D-data). The predictive performance was evaluated in terms of overall survival (OS), disease-free survival (DFS), and pathological invasive factors (positive lymphatic invasion, blood vessel invasion, pleural invasion, or lymph node metastasis). METHODS: We identified 252 patients (122 male; mean age, 68 years; range, 23-84 years) with c-I NSCLC who underwent high resolution CT and reconstruction of 3D imaging, followed by complete resection between January 2012 and December 2015. In this study, 2D-data including whole tumor size (WTS) and solid-part size (SPS) and 3D-data including whole tumor volume (WTV) and solid-part volume (SPV) acquired by a 3D volume rendering software were analyzed. RESULTS: The area under the receiver operating characteristic (ROC) curve for WTS, SPS, WTV, SPV relevant to recurrence was 0.667, 0.727, 0.654, and 0.751 while analyses of ROC curves revealed optimal WTS, SPS, WTV, and SPV cut-off values to predict recurrence of 2.48 cm, 2.03 cm, 3,258 mm3 and 1,889 mm3, respectively. The association between SPS and SPV was the coefficient of determination (R 2) =0.59. Multivariate analysis showed that SPV >1,889 mm3 (P=0.016) and male (P=0.041) were significant predictors of OS whereas SPV >1,889 mm3 (P=0.001), male (P=0.003), and the serum carcinoembryonic antigen value (P=0.041) were significantly correlated with DFS. SPS, SPV as well as the combination of SPS and SPV were all significantly correlated with the prediction of OS and DFS, and the incidence of pathological invasive factors. CONCLUSIONS: SPV and the integrated use of SPS and SPV was highly beneficial for the prediction of postoperative prognosis in c-I NSCLC.
BACKGROUND: This study aimed to predict the malignant potential of clinical stage I non-small cell lung cancer (c-I NSCLC) by semiautomatic three-dimensional (3D) volumetric measurement of a tumor (3D-data) and the axial computed tomography (CT) data derived from a 3D volumetric dataset (2D-data). The predictive performance was evaluated in terms of overall survival (OS), disease-free survival (DFS), and pathological invasive factors (positive lymphatic invasion, blood vessel invasion, pleural invasion, or lymph node metastasis). METHODS: We identified 252 patients (122 male; mean age, 68 years; range, 23-84 years) with c-I NSCLC who underwent high resolution CT and reconstruction of 3D imaging, followed by complete resection between January 2012 and December 2015. In this study, 2D-data including whole tumor size (WTS) and solid-part size (SPS) and 3D-data including whole tumor volume (WTV) and solid-part volume (SPV) acquired by a 3D volume rendering software were analyzed. RESULTS: The area under the receiver operating characteristic (ROC) curve for WTS, SPS, WTV, SPV relevant to recurrence was 0.667, 0.727, 0.654, and 0.751 while analyses of ROC curves revealed optimal WTS, SPS, WTV, and SPV cut-off values to predict recurrence of 2.48 cm, 2.03 cm, 3,258 mm3 and 1,889 mm3, respectively. The association between SPS and SPV was the coefficient of determination (R 2) =0.59. Multivariate analysis showed that SPV >1,889 mm3 (P=0.016) and male (P=0.041) were significant predictors of OS whereas SPV >1,889 mm3 (P=0.001), male (P=0.003), and the serum carcinoembryonic antigen value (P=0.041) were significantly correlated with DFS. SPS, SPV as well as the combination of SPS and SPV were all significantly correlated with the prediction of OS and DFS, and the incidence of pathological invasive factors. CONCLUSIONS: SPV and the integrated use of SPS and SPV was highly beneficial for the prediction of postoperative prognosis in c-I NSCLC.
Authors: K Takamochi; K Nagai; J Yoshida; K Suzuki; Y Ohde; M Nishimura; K Takahashi; Y Nishiwaki Journal: J Thorac Cardiovasc Surg Date: 2000-06 Impact factor: 5.209