医学研究与教育 ›› 2024, Vol. 41 ›› Issue (2): 21-28.DOI: 10.3969/j.issn.1674-490X.2024.02.004

• 临床医学 • 上一篇    下一篇

基于MRI影像组学在乳腺癌分子分型的研究进展

李昊1,2,侯岩1,殷小平1,3   

  1. 1.河北大学附属医院放射科, 河北 保定 071000;
    2.河北省保定市第一中心医院超声一科, 河北 保定 071000;
    3.河北省炎症相关肿瘤精确影像学重点实验室, 河北 保定 071000
  • 收稿日期:2023-05-13 出版日期:2024-04-25 发布日期:2024-04-25
  • 通讯作者: 殷小平(1978—),女,河北保定人,主任医师,博士,博士生导师,主要从事人工智能应用及腹部肿瘤影像学诊断。E-mail: yinxiaoping78@sina.com
  • 作者简介:李昊(1989—),女,河北保定人,主治医师,硕士,主要从事乳腺影像学诊断。 E-mail: vickyhbbd77@126.com
  • 基金资助:
    河北省高层次人才资助项目(B20231008)

  • Received:2023-05-13 Online:2024-04-25 Published:2024-04-25

摘要: 乳腺癌严重影响女性身心健康,是女性最常见的恶性肿瘤,其依据病理不同进行分子分型,早期识别病理分型和靶向治疗是改善患者预后的关键。病理虽为金标准也存在一定不足,如操作的有创性、标本取材的局限性以及检测时间要求的限制性。影像组学通过深度挖掘影像图像多维度特征,将肿瘤的异质性进行量化处理,采用一种无创性、简便的方法对肿瘤的生物学特性进行综合评价,在乳腺癌分子分型的发现、预测淋巴结转移、制订治疗方案、评估治疗效果、判断患者预后等方面已得到广泛应用。现拟基于MRI影像组学特征对乳腺癌分子分型的应用现状进行综述。

关键词: 乳腺癌, 分子分型, 影像组学, 磁共振成像

Abstract: Breast cancer is the most common malignant tumor in women, which seriously affects the physical and mental health of women. Molecular classification according to pathology, early identification of pathological classification and targeted therapy play a decisive role in ameliorating prognosis of patients. Although pathology is the gold standard, there are some shortcomings, such as the invasiveness of operation, the limitation of sampling and the limitation of testing time. By deeply mining the multi-dimensional features of the image, radiomics quantifies the heterogeneity of the tumor, and uses a non-invasive and simple method to comprehensively evaluate the biological characteristics of the tumor, it has been widely used in the discovery of molecular classification of breast cancer, prediction of LNM, formulation of treatment plan, evaluation of treatment effect, prognosis of patients and so on. In this paper, the application of molecular typing of breast cancer based on MRI radiomics -本文引用:李昊,侯岩,殷小平.基于MRI影像组学在乳腺癌分子分型的研究进展[J].医学研究与教育,2024,41(2):21-28.DOI:10.3969/j.issn.1674-490X.2024.02.004.·临床医学·基于MRI影像组学在乳腺癌分子分型的研究进展李昊1,2,侯岩1,殷小平1,3(1.河北大学附属医院放射科,河北 保定 071000;2.河北省保定市第一中心医院超声一科,河北 保定 071000;3.河北省炎症相关肿瘤精确影像学重点实验室,河北 保定 071000)摘要:乳腺癌严重影响女性身心健康,是女性最常见的恶性肿瘤,其依据病理不同进行分子分型,早期识别病理分型和靶向治疗是改善患者预后的关键。病理虽为金标准也存在一定不足,如操作的有创性、标本取材的局限性以及检测时间要求的限制性。影像组学通过深度挖掘影像图像多维度特征,将肿瘤的异质性进行量化处理,采用一种无创性、简便的方法对肿瘤的生物学特性进行综合评价,在乳腺癌分子分型的发现、预测淋巴结转移、制订治疗方案、评估治疗效果、判断患者预后等方面已得到广泛应用。现拟基于MRI影像组学特征对乳腺癌分子分型的应用现状进行综述。关键词:乳腺癌;分子分型;影像组学;磁共振成像DOI:10.3969/j.issn.1674-490X.2024.02.004中图分类号:R44 文献标志码:A 文章编号:1674-490X(2024)02-0021-08Advances on MRI radiomics in molecular typing of breast cancerLI Hao1,2, HOU Yan1, YIN Xiaoping1,3(1. Department of Radiology, Affiliated Hospital of Hebei University, Baoding 071000, China; 2. NO.1 Department of Ultrasound, Baoding NO.1 Central Hospital, Baoding 071000, China; 3. Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding 071000, China)Abstract: Breast cancer is the most common malignant tumor in women, which seriously affects the physical and mental health of women. Molecular classification according to pathology, early identification of pathological classification and targeted therapy play a decisive role in ameliorating prognosis of patients. Although pathology is the gold standard, there are some shortcomings, such as the invasiveness of operation, the limitation of sampling and the limitation of testing time. By deeply mining the multi-dimensional features of the image, radiomics quantifies the heterogeneity of the tumor, and uses a non-invasive and simple method to comprehensively evaluate the biological characteristics of the tumor, it has been widely used in the discovery of molecular classification of breast cancer, prediction of LNM, formulation of treatment plan, evaluation of treatment effect, prognosis of patients and so on. In this paper, the application of molecular typing of breast cancer based on MRI radiomics -收稿日期:2023-05-13基金项目:河北省高层次人才资助项目(B20231008)第一作者:李昊(1989—),女,河北保定人,主治医师,硕士,主要从事乳腺影像学诊断。E-mail: vickyhbbd77@126.com通信作者:殷小平(1978—),女,河北保定人,主任医师,博士,博士生导师,主要从事人工智能应用及腹部肿瘤影像学诊断。E-mail: yinxiaoping78@sina.com第2期李昊等:基于MRI影像组学在乳腺癌分子分型的研究进展2024年characteristics is reviewed.

Key words: breast cancer, molecular typing, radiomics, magnetic resonance imaging

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