Application of dual-energy CT in differential diagnosis of lung metastases and benign nodules in breast cancer
10.3760/cma.j.cn112149-20211227-01149
- VernacularTitle:双能量CT鉴别诊断乳腺癌肺转移瘤和肺良性结节的研究
- Author:
Guihan LIN
1
;
Weibo MAO
;
Weiyue CHEN
;
Chunmiao CHEN
;
Xue CHENG
;
Xianghua HU
;
Jiansong JI
Author Information
1. 温州医科大学附属第五医院放射科 浙江省影像诊断与介入微创研究重点实验室
- Keywords:
Tomography, X-ray computed;
Breast neoplasms;
Dual-energy CT;
Lung metastasis
- From:
Chinese Journal of Radiology
2022;56(11):1209-1214
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the application value of dual-energy CT in the differential diagnosis of lung metastases and benign nodules in breast cancer.Methods:The 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 (λ HU) and normalized effective atomic number (nZ eff) in arterial and venous phases] were analyzed and measured. The χ 2 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. Results:There were statistically significant differences between lung metastases and benign nodules in longest diameter, ?CT, NIC, λ HU and nZ eff in arterial and venous phases (all P<0.05). LASSO regression and binary logistic regression analysis showed that the venous phase λ HU (OR=59.413, 95%CI 14.233-248.002, P<0.001) and the venous phase nZ eff (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 λ HU 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 λ HU and the venous phase nZ eff 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). Conclusion:Dual-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 λ HU and venous phase nZ eff, the diagnostic efficiency is further improved.
