| 自动乳腺全容积成像结合超声乳腺影像报告和数据系统分类诊断常规超声征象不典型的乳腺癌 |
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| 引用本文： | 李可基,龚业琼,申俊玲,吴晓莉,戴兴,赖萍.自动乳腺全容积成像结合超声乳腺影像报告和数据系统分类诊断常规超声征象不典型的乳腺癌[J].中国介入影像与治疗学,2018,15(8):477-480. |
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| 作者姓名： | 李可基 龚业琼 申俊玲 吴晓莉 戴兴 赖萍 |
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| 作者单位： | 攀枝花市中心医院超声科 |
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| 摘 要： | 目的探讨自动乳腺全容积成像(ABVS)联合乳腺影像报告和数据系统(BI-RADS)分类对常规超声恶性征象不典型(BI-RADS分类3类及4A类)乳腺癌的诊断价值。方法对常规超声BI-RADS分类3类及4A类的832例患者共876个乳腺肿块行ABVS。结合ABVS冠状位图像特点对乳腺肿块重新进行BI-RADS分类。与术后病理结果对照,比较常规超声BI-RADS分类与ABVS结合BI-RADS分类为3类、4A类肿块中恶性率的差异;并以BI-RADS分类≥4B类为恶性肿块诊断标准,评价ABVS结合BI-RADS分类诊断乳腺恶性肿块的效能。结果常规超声BI-RADS分类为3类肿块558个,恶性率4.30%(24/558),4A类肿块318个,恶性率11.01%(35/318)。结合ABVS冠状位图像特点重新分类后,3类肿块455个,恶性率0.66%(3/455);4A类肿块176个,恶性率4.55%(8/176);4B类肿块218个,恶性率14.22%(31/218);4C类肿块27个,恶性率62.96%(17/27)。ABVS结合BI-RADS分类为3类、4A类肿块的恶性率明显低于常规超声分类为3类、4A类肿块(χ~2=11.447、5.951,P=0.001、0.015)。ABVS结合BI-RADS分类对恶性肿块的诊断敏感度、特异度及准确率分别为81.36%(48/59)、75.89%(620/817)及76.26%(668/876)。结论 ABVS结合BI-RADS分类对常规超声恶性征象不典型的乳腺癌具有重要诊断价值。
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| 关 键 词： | 乳腺肿瘤 超声检查 自动乳腺全容积成像 乳腺影像报告和数据系统 |
| 收稿时间： | 2017/12/18 0:00:00 |
| 修稿时间： | 2018/3/19 0:00:00 |
Automated breast volume scanner combined with breast imaging reporting and data system for diagnosing atypical breast cancer with untypical features of conventional ultrasonography |
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| LI Keji,GONG Yeqiong,SHEN Junling,WU Xiaoli,DAI Xing and LAI Ping.Automated breast volume scanner combined with breast imaging reporting and data system for diagnosing atypical breast cancer with untypical features of conventional ultrasonography[J].Chinese Journal of Interventional Imaging and Therapy,2018,15(8):477-480. |
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| Authors: | LI Keji GONG Yeqiong SHEN Junling WU Xiaoli DAI Xing and LAI Ping |
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| Institution: | Department of Ultrasound, Center Hospital of Panzhihua, Panzhihua 617067, China,Department of Ultrasound, Center Hospital of Panzhihua, Panzhihua 617067, China,Department of Ultrasound, Center Hospital of Panzhihua, Panzhihua 617067, China,Department of Ultrasound, Center Hospital of Panzhihua, Panzhihua 617067, China,Department of Ultrasound, Center Hospital of Panzhihua, Panzhihua 617067, China and Department of Ultrasound, Center Hospital of Panzhihua, Panzhihua 617067, China |
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| Abstract: | |
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| Keywords: | Breast neoplasms Ultrasonography Automated breast volume scanner Breast imaging reporting and data system |
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