Gail Model Improves the Diagnostic Performance of the Fifth Edition of Ultrasound BI-RADS for Predicting Breast Cancer: A Multicenter Prospective Study
| Autor: | Chun-Song Kang, Bao-Ming Luo, Jia-Wei Tian, Man Chen, Chun-Quan Zhang, Qing Zhou, Yu-Hong Zhang, Jian-Jun Yuan, Ping Zhou, Luying Gao, Yuxin Jiang, Jie Li, Hongyan Wang, Jian-Feng Guo, Wu Chen, Haitao Ran, Weiwei Zhan, Ying Gu, Jianchu Li, Wei-Dong Ren, You-Bin Deng, Yang Gu, Qi Zhou, Cai Chang |
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| Rok vydání: | 2022 |
| Předmět: |
medicine.medical_specialty
Breast imaging Breast Neoplasms BI-RADS Malignancy Sensitivity and Specificity 030218 nuclear medicine & medical imaging Diagnosis Differential 03 medical and health sciences 0302 clinical medicine Breast cancer medicine Humans Radiology Nuclear Medicine and imaging Prospective Studies Prospective cohort study medicine.diagnostic_test business.industry medicine.disease Acoustic shadow 030220 oncology & carcinogenesis Elasticity Imaging Techniques Female Ultrasonography Mammary Radiology Elastography Microcalcification medicine.symptom business |
| Zdroj: | Academic Radiology. 29:S1-S7 |
| ISSN: | 1076-6332 |
| DOI: | 10.1016/j.acra.2020.12.002 |
| Popis: | The sonographic appearance of benign and malignant breast nodules overlaps to some extent, and we aimed to assess the performance of the Gail model as an adjunctive tool to ultrasound (US) Breast Imaging Reporting and Data System (BI-RADS) for predicting the malignancy of nodules.From 2018 to 2019, 2607 patients were prospectively enrolled by 35 health care facilities. An individual breast cancer risk was assessed by the Gail model. Based on B-mode US, color Doppler, and elastography, all nodules were evaluated according to the fifth edition of BI-RADS, and these nodules were all confirmed later by pathology.We demonstrated that the Gail model, age, tumor size, tumor shape, growth orientation, margin, contour, acoustic shadowing, microcalcification, presence of duct ectasia, presence of architectural distortion, color Doppler flow, BI-RADS, and elastography score were significantly related to breast cancer (all p0.001). The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the curve (AUC) for combining the Gail model with the BI-RADS category were 95.6%, 91.3%, 85.0%, 97.6%, 92.8%, and 0.98, respectively. Combining the Gail model with the BI-RADS showed better diagnostic efficiency than the BI-RADS and Gail model alone (AUC 0.98 vs 0.80, p0.001; AUC 0.98 vs 0.55, p0.001) and demonstrated a higher specificity than the BI-RADS (91.3% vs 59.4%, p0.001).The Gail model could be used to differentiate malignant and benign breast lesions. Combined with the BI-RADS category, the Gail model was adjunctive to US for predicting breast lesions for malignancy. For the diagnosis of malignancy, more attention should be paid to high-risk patients with breast lesions. |
| Databáze: | OpenAIRE |
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