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影像组学在预测乳腺癌分子分型的应用进展
Advances in the Application of Radiomics in Predicting Molecular Typing of Breast Cancer

DOI: 10.12677/WJCR.2024.141007, PP. 41-47

Keywords: 影像组学,机器学习,乳腺癌,分子分型
Radiomics
, Machine Learning, Breast Cancer, Molecular Typing

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Abstract:

乳腺癌分子亚型的准确诊断对于指导医生制定个体化治疗方案具有重要意义。目前临床主要通过病理组织进行免疫组化分析获取乳腺癌分子分型,然而取样和分析可能存在一定的局限性。影像组学技术由于其将医学图像转换为用于定量研究的高维数据的能力而成为替代方案,提供了对肿瘤的非侵入性和全面评估。本文就影像组学在预测乳腺癌分子分型中的应用进展予以综述。
Accurate diagnosis of molecular subtypes of breast cancer is of great significance to guide doctors to make individualized treatment plan. At present, the molecular classification of breast cancer is mainly obtained through immunohistochemical analysis of pathological tissues, but there may be some limitations in sampling and analysis. Radiomics technology has emerged as an alternative due to its ability to convert medical images into high-dimensional data for quantitative studies, providing a non-invasive and comprehensive assessment of tumors. This article reviews the application of radiomics in predicting molecular typing of breast cancer.

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