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Gail Model Improves the Diagnostic Performance of the Fifth Edition of Ultrasound BI-RADS for Predicting Breast Cancer: A Multicenter Prospective Study.

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机构： [a]Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China [b]Department of Ultrasound, the Second Affiliated Hospital of Harbin Medical University, Harbin, China [c]Department of Ultrasound, the second Affiliated Hospital of Chongqing Medical University, Chongqing Key laboratory of Ultrasound Molecular Imaging, Chongqing, China [d]Department of Ultrasound, Shengjing Hospital of China Medical University, Shenyang, China [e]Department of Medical Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China [f]Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China [g]Department of Ultrasonography, Henan Provincial People′s Hospital, Zhengzhou , China [h]Department of Ultrasound, Shanxi Academy of Medical Science, Dayi Hospital of Shanxi Medical University, Taiyuan, China [i]Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China [j]Department of Ultrasound, the Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China [k]Department of Medical Ultrasound, the Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China [l]Department of Ultrasound, Ruijin Hospital, Shanghai Jiaotong University, School of Medicine, Shanghai, China [m]Department of Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, China [n]Department of Ultrasound, Qilu Hospital, Shandong University, Jinan, China [o]Department of Ultrasound, the Third Xiangya Hospital of Central South University, Changsha, China [p]Department of Ultrasound, the Second Affiliated Hospital of Nanchang University, Nanchang, China [q]Department of Ultrasound Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China [r]Department of Ultrasonography, the Affiliated Hospital of Guizhou Medical University, Guiyang, China [s]Department of Ultrasound, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China [t]Department of Ultrasound, the First Hospital of Shanxi Medical University, Taiyuan, China [u]Department of Ultrasound, the Second Hospital of Dalian Medical University, Dalian, China

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关键词： Breast cancerBreast lesionBreast Imaging Reporting and Data System (BI-RADS)ElastographyGail model

摘要：

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 p < 0.001). 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, p < 0.001; AUC 0.98 vs 0.55, p < 0.001) and demonstrated a higher specificity than the BI-RADS (91.3% vs 59.4%, p < 0.001). 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. Copyright © 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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出版当年[2021]版：

大类 | 3 区医学

小类 | 3 区核医学

最新[2025]版：

大类 | 2 区医学

小类 | 2 区核医学

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出版当年[2020]版：

Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

最新[2023]版：

Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子： 3.8 最新[2023版] 3.7 最新五年平均 3.173 出版当年[2020版] 2.751 出版当年五年平均 2.488 出版前一年[2019版] 5.482 出版后一年[2021版]

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第一作者机构： [a]Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China

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Gail Model Improves the Diagnostic Performance of the Fifth Edition of Ultrasound BI-RADS for Predicting Breast Cancer: A Multicenter Prospective Study.

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