摘要
乳腺癌是女性最为常见的恶性肿瘤之一,腋窝淋巴结的转移情况对疾病分期、治疗手段的选择以及预后判断具有重要意义。现阶段临床多采用超声或前哨淋巴结活检来评价腋窝淋巴结有无转移,但上述方法存在不足之处或伴随并发症的发生。MRI近年来越来越多地运用于乳腺癌腋窝淋巴结转移的无创诊断。本文将回顾通过MRI直接评价乳腺癌腋窝淋巴结转移(而非通过肿瘤本身的MRI相关特征预测腋窝淋巴结转移)的文献,并将MRI的相关特征用于诊断乳腺癌腋窝淋巴结转移的准确性进行综述。本文发现,目前的研究结果之间存在差异,使用MRI多参数联合或可提高诊断准确性,并且影像组学的出现也为诊断带来了新的机遇。
Breast cancer has become one of the most common malignant tumors in women.The status of axillary lymph nodes metastases helps determine stages and surgical/postsurgical management of the disease,and remains one of the most important prognostic factors in breast cancer.At present,ultrasound or sentinel lymph node biopsy is often used to evaluate axillary lymph node metastases,but the above methods have shortcomings or may accompany complications.Magnetic resonance imaging(MRI)has been increasingly used in the noninvasive diagnosis of axillary lymph node metastases in breast cancer in recent years.We reviewed studies evaluating the use of MRI in detecting metastatic axillary lymph nodes in breast cancer patients(studies employing MRI characteristics of breast cancer to predict axillary lymph nodes metastases were not included),and summarized the diagnostic accuracy of MRI in discriminating metastatic axillary lymph nodes from nonmetastatic axillary lymph nodes.We found that results of studies were not consistent,and the diagnostic accuracy could be increased by combining morphological,dynamic and/or functional features on MRI;furthermore,the radiomics research would be of great potential and value in identifying metastatic lymph nodes.
作者
张欣
罗红兵(综述)
张剑辉
刘圆圆(审校)
Zhang Xin;Luo Hongbing;Zhang Jianhui;Liu Yuanyuan(Department of Breast Surgery,Sichuan Cancer Hospital&Institute,Sichuan Cancer Center,School of Medicine,University of Electronic Science and Technology of China,Chengdu 610041,Sichuan,China;Department of Medical Imaging,Sichuan Cancer Hospital&Institute,Sichuan Cancer Center,School of Medicine,University of Electronic Science and Technology of China,Chengdu 610041,Sichuan,China)
出处
《肿瘤预防与治疗》
2020年第3期269-274,共6页
Journal of Cancer Control And Treatment
基金
四川省医学科研课题(编号:S17067)。
