Wenjia Yang1, Yifeng Sun2, Wentao Fang2, Fangfei Qian1, Jianding Ye3, Qunhui Chen3, Yifeng Jiang3, Keke Yu4, Baohui Han5. 1. Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China. 2. Department of Thoracic Surgery Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China. 3. Department of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China. 4. Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China. 5. Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China. Electronic address: xkyyhan@gmail.com.
Abstract
INTRODUCTION: We retrospectively investigated the high-resolution computed tomography features that distinguish benign lesions (BLs) from malignant lesions (MLs) appearing as persistent solitary subsolid nodules (SSNs). MATERIALS AND METHODS: In 2015, the data from patients treated in our department with persistent solitary SSNs 5 to 30 mm in size were analyzed retrospectively. The demographic data and HRCT findings were analyzed and compared between those with BLs and MLs. RESULTS: Of the 1934 SSNs, 94 were BLs and 1840 were MLs. One half of the MLs (920 SSNs) were randomly selected and analyzed. The BLs were classified into 2 subgroups: 28 pure ground-glass nodules (pGGNs) and 66 part-solid nodules (PSNs). After matching in each group, 56 pGGNs and 132 PSNs in the ML group were selected. In the pGGN subgroup, multivariate analysis found that a well-defined border (odds ratio [OR], 4.320; 95% confidence interval [CI], 1.534-12.168; P = .006; area under the curve, 0.705; 95% CI, 0.583-0.828; P = .002) and a higher average CT value (OR, 1.007; 95% CI, 1.001-1.013; P = .026; area under the curve, 0.715; 95% CI, 0.599-0.831; P = .001) favored the diagnosis of malignancy. In the PSN subgroup, multivariate analysis revealed that a larger size (OR, 1.084; 95% CI, 1.015-1.158; P = .016), a well-defined border (OR, 3.447; 95% CI, 1.675-7.094; P = .001), and a spiculated margin (OR, 2.735; 95% CI, 1.359-5.504; P = .005) favored the diagnosis of malignancy. CONCLUSION: In pGGNs, a well-defined lesion border and a larger average CT value can be valuable discriminators to distinguish between MLs and BLs. In PSNs, a larger size, well-defined border, and spiculated margin had greater predictive value for malignancy.
INTRODUCTION: We retrospectively investigated the high-resolution computed tomography features that distinguish benign lesions (BLs) from malignant lesions (MLs) appearing as persistent solitary subsolid nodules (SSNs). MATERIALS AND METHODS: In 2015, the data from patients treated in our department with persistent solitary SSNs 5 to 30 mm in size were analyzed retrospectively. The demographic data and HRCT findings were analyzed and compared between those with BLs and MLs. RESULTS: Of the 1934 SSNs, 94 were BLs and 1840 were MLs. One half of the MLs (920 SSNs) were randomly selected and analyzed. The BLs were classified into 2 subgroups: 28 pure ground-glass nodules (pGGNs) and 66 part-solid nodules (PSNs). After matching in each group, 56 pGGNs and 132 PSNs in the ML group were selected. In the pGGN subgroup, multivariate analysis found that a well-defined border (odds ratio [OR], 4.320; 95% confidence interval [CI], 1.534-12.168; P = .006; area under the curve, 0.705; 95% CI, 0.583-0.828; P = .002) and a higher average CT value (OR, 1.007; 95% CI, 1.001-1.013; P = .026; area under the curve, 0.715; 95% CI, 0.599-0.831; P = .001) favored the diagnosis of malignancy. In the PSN subgroup, multivariate analysis revealed that a larger size (OR, 1.084; 95% CI, 1.015-1.158; P = .016), a well-defined border (OR, 3.447; 95% CI, 1.675-7.094; P = .001), and a spiculated margin (OR, 2.735; 95% CI, 1.359-5.504; P = .005) favored the diagnosis of malignancy. CONCLUSION: In pGGNs, a well-defined lesion border and a larger average CT value can be valuable discriminators to distinguish between MLs and BLs. In PSNs, a larger size, well-defined border, and spiculated margin had greater predictive value for malignancy.
Authors: Constance de Margerie-Mellon; Ritu R Gill; Pascal Salazar; Anastasia Oikonomou; Elsie T Nguyen; Benedikt H Heidinger; Mayra A Medina; Paul A VanderLaan; Alexander A Bankier Journal: Sci Rep Date: 2020-09-03 Impact factor: 4.379