L Han1, P Zhang1, Y Wang1, Z Gao1, H Wang1, X Li2, Z Ye3. 1. Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin, 300060, China. 2. Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin, 300060, China. Electronic address: lixb@bjmu.edu.cn. 3. Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin, 300060, China. Electronic address: yezhaoxiang@163.com.
Abstract
AIM: To investigate the value of computed tomography (CT) quantitative parameters in predicting the invasiveness of lung pure ground-glass nodules (pGGNs). MATERIALS AND METHODS: Chest CT images and pathological findings of 163 pGGNs in 154 consecutive patients were reviewed. According to the clinical management strategies, cases were divided into pre-invasive and MIA groups (atypical adenomatous hyperplasia [AAH], adenocarcinoma in situ [AIS], and minimally invasive adenocarcinoma [MIA]) and invasive group (invasive adenocarcinoma [IAC]). CT quantitative parameters including maximum diameter, largest diameter perpendicular to the maximum diameter, maximum cross-sectional area, volume, mass, and mean attenuation value were measured and compared between two groups. Their diagnostic performances were evaluated using receiver operating characteristic (ROC) and logistic regression analysis. RESULTS: Significant differences existed for all the CT quantitative parameters in both groups (p<0.01). The values of area under the curve (AUC) were 0.783 of maximum diameter (95% CI: 0.711-0.843), 0.779 of longest diameter perpendicular to maximum diameter (95% CI: 0.707-0.840), 0.796 of largest cross-sectional area (95% CI: 0.726-0.855), 0.781 of volume (95% CI: 0.710-0.842), 0.794 of mass (95% CI: 0.722-0.865) and 0.625 of mean attenuation value (95% CI: 0.546-0.700), respectively. A pairwise-manner comparison showed the AUC of mean attenuation value was the smallest (p<0.01). Logistic regression analysis showed the largest cross-sectional area (OR=2.307, 95% CI: 1.689-3.150) was the independent predictor for IAC with a cut-off value of 2.22 cm2. CONCLUSIONS: CT quantitative parameters could predict the invasiveness of lung pGGNs. The largest cross-sectional area is the most valuable independent predictor and the mean attenuation value is less valuable.
AIM: To investigate the value of computed tomography (CT) quantitative parameters in predicting the invasiveness of lung pure ground-glass nodules (pGGNs). MATERIALS AND METHODS: Chest CT images and pathological findings of 163 pGGNs in 154 consecutive patients were reviewed. According to the clinical management strategies, cases were divided into pre-invasive and MIA groups (atypical adenomatous hyperplasia [AAH], adenocarcinoma in situ [AIS], and minimally invasive adenocarcinoma [MIA]) and invasive group (invasive adenocarcinoma [IAC]). CT quantitative parameters including maximum diameter, largest diameter perpendicular to the maximum diameter, maximum cross-sectional area, volume, mass, and mean attenuation value were measured and compared between two groups. Their diagnostic performances were evaluated using receiver operating characteristic (ROC) and logistic regression analysis. RESULTS: Significant differences existed for all the CT quantitative parameters in both groups (p<0.01). The values of area under the curve (AUC) were 0.783 of maximum diameter (95% CI: 0.711-0.843), 0.779 of longest diameter perpendicular to maximum diameter (95% CI: 0.707-0.840), 0.796 of largest cross-sectional area (95% CI: 0.726-0.855), 0.781 of volume (95% CI: 0.710-0.842), 0.794 of mass (95% CI: 0.722-0.865) and 0.625 of mean attenuation value (95% CI: 0.546-0.700), respectively. A pairwise-manner comparison showed the AUC of mean attenuation value was the smallest (p<0.01). Logistic regression analysis showed the largest cross-sectional area (OR=2.307, 95% CI: 1.689-3.150) was the independent predictor for IAC with a cut-off value of 2.22 cm2. CONCLUSIONS: CT quantitative parameters could predict the invasiveness of lung pGGNs. The largest cross-sectional area is the most valuable independent predictor and the mean attenuation value is less valuable.