Application of dual-energy CT in differential diagnosis of lung metastases and benign nodules in breast cancer
Lin Guihan, Mao Weibo, Chen Weiyue, Chen Chunmiao, Cheng Xue, Hu Xianghua, Ji Jiansong
Abstract
ObjectiveTo investigate the application value of dual-energy CT in the differential diagnosis of lung metastases and benign nodules in breast cancer.
MethodsThe data of 96 patients with pathology-confirmed breast cancer at the Fifth Affiliated Hospital of Wenzhou Medical University from March 2017 to June 2021 were analyzed retrospectively. All patients received dual-energy chest CT scans within 2 weeks before surgery. All 96 patients were female, aged 31-84 (56±12) years. A total of 207 pulmonary nodules from 96 patients were classified into 81 lung metastases and 126 benign nodules according to pathological findings. Conventional CT features [longest diameter, boundary, location and CT value difference between arterial and venous phases (ΔCT) of nodules] and dual-energy CT parameters [standardized iodine concentration (NIC), slope of energy spectrum (λHU) and normalized effective atomic number (nZeff) in arterial and venous phases] were analyzed and measured. The χ2 test, independent samples t test and Kruskal-Wallis rank-sum test were used to analyze the differences of conventional CT features and dual-energy CT parameters between lung metastases and benign nodules. First, the least shrinkage and selection operator (LASSO) regression method was used to screen conventional CT features and dual-energy CT parameters, and then logistic regression analysis was performed to screen out independent risk factors for lung metastases. Receiver operating characteristic (ROC) curves were used to evaluate the efficacy of CT parameters alone and logistic model in differentiating lung metastases from benign lung nodules.
ResultsThere were statistically significant differences between lung metastases and benign nodules in longest diameter, ∆CT, NIC, λHU and nZeff in arterial and venous phases (all P<0.05). LASSO regression and binary logistic regression analysis showed that the venous phase λHU (OR=59.413, 95%CI 14.233-248.002, P<0.001) and the venous phase nZeff (OR=4.508, 95%CI 2.787-7.290, P<0.001) were independent risk factors for predicting lung metastases. Among them, the venous phase λHU had the highest diagnostic efficiency, with an area under curve (AUC) of 0.794 and an accuracy of 74.88%. The AUC of the logistic model constructed by combining the venous phase λHU and the venous phase nZeff could reach 0.958, and the accuracy was improved to 92.27%, which was significantly higher than the efficacy of the two alone (Z=6.02, 9.54, all P<0.001).
ConclusionDual-energy CT has great application value in the identification of lung metastases and benign nodules in patients with breast cancer, especially when combined with venous phase λHU and venous phase nZeff, the diagnostic efficiency is further improved.
Key words:
Tomography, X-ray computed; Breast neoplasms; Dual-energy CT; Lung metastasis
Contributor Information
Lin Guihan
Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Zhejiang Province, Lishui 323000, China
2 Department of Pathology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China
Mao Weibo
Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Zhejiang Province, Lishui 323000, China
2 Department of Pathology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China
Chen Weiyue
Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Zhejiang Province, Lishui 323000, China
2 Department of Pathology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China
Chen Chunmiao
Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Zhejiang Province, Lishui 323000, China
2 Department of Pathology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China
Cheng Xue
Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Zhejiang Province, Lishui 323000, China
2 Department of Pathology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China
Hu Xianghua
Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Zhejiang Province, Lishui 323000, China
2 Department of Pathology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China
Ji Jiansong
Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Zhejiang Province, Lishui 323000, China
2 Department of Pathology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China