MRI作为乳腺癌诊断和预后的生物标志物。

BJR open Pub Date : 2022-01-01 DOI:10.1259/bjro.20220002
Francesca Galati, Veronica Rizzo, Rubina Manuela Trimboli, Endi Kripa, Roberto Maroncelli, Federica Pediconi
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引用次数: 5

摘要

乳腺癌(BC)是西方国家最常见的女性浸润性癌症,也是世界范围内癌症相关死亡的主要原因。如今,肿瘤异质性是BC的一个众所周知的特征,因为它包括几种具有不同形态特征、临床病程和治疗反应的疾病实体。因此,随着分子生物学技术的传播和对BC发展背后的生物过程知识的不断增长,成像生物标志物作为组织标志的非侵入性信息的重要性逐渐增加。迄今为止,乳房磁共振成像(MRI)在乳房成像实践中被认为是不可或缺的,具有广泛认可的适应症,如高风险女性的BC筛查,局部区域分期和新辅助治疗(NAT)监测。此外,基于基因组学和分子生物学特征的发展,乳房MRI越来越多地用于评估病理过程的形态学特征,还用于表征靶向治疗的个体表型。本综述的目的是探讨乳腺多参数MRI在提供成像生物标志物方面的作用,从而改善乳腺良性和恶性病变的区分,并在监测和预测治疗反应方面对BC患者进行定制管理。最后,我们讨论了乳房MRI生物标志物如何为人工智能(AI)应用提供最肥沃的土壤之一。在个性化医疗时代,随着组学技术、机器学习和大数据技术的发展,成像生物标志物的作用为BC的诊断和治疗带来了新的机遇。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

MRI as a biomarker for breast cancer diagnosis and prognosis.

MRI as a biomarker for breast cancer diagnosis and prognosis.

MRI as a biomarker for breast cancer diagnosis and prognosis.

MRI as a biomarker for breast cancer diagnosis and prognosis.

Breast cancer (BC) is the most frequently diagnosed female invasive cancer in Western countries and the leading cause of cancer-related death worldwide. Nowadays, tumor heterogeneity is a well-known characteristic of BC, since it includes several nosological entities characterized by different morphologic features, clinical course and response to treatment. Thus, with the spread of molecular biology technologies and the growing knowledge of the biological processes underlying the development of BC, the importance of imaging biomarkers as non-invasive information about tissue hallmarks has progressively grown. To date, breast magnetic resonance imaging (MRI) is considered indispensable in breast imaging practice, with widely recognized indications such as BC screening in females at increased risk, locoregional staging and neoadjuvant therapy (NAT) monitoring. Moreover, breast MRI is increasingly used to assess not only the morphologic features of the pathological process but also to characterize individual phenotypes for targeted therapies, building on developments in genomics and molecular biology features. The aim of this review is to explore the role of breast multiparametric MRI in providing imaging biomarkers, leading to an improved differentiation of benign and malignant breast lesions and to a customized management of BC patients in monitoring and predicting response to treatment. Finally, we discuss how breast MRI biomarkers offer one of the most fertile ground for artificial intelligence (AI) applications. In the era of personalized medicine, with the development of omics-technologies, machine learning and big data, the role of imaging biomarkers is embracing new opportunities for BC diagnosis and treatment.

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