Zhou Jianmin, Zhang Yanchun, Shi Shaohua
Department of Ultrasound, Yantaishan Hospital, Yantai, Shandong, China.
Front Oncol. 2025 Jun 26;15:1589142. doi: 10.3389/fonc.2025.1589142. eCollection 2025.
This review explores recent advances in ultrasound elastography for breast cancer detection, focusing on technological innovations, clinical validation, and emerging challenges in early diagnosis. We analyze how modern elastographic techniques have evolved to address the critical need for accurate, non-invasive breast cancer screening and characterization. Recent methodological developments in ultrasound elastography have significantly enhanced its diagnostic capabilities, particularly in distinguishing malignant from benign breast lesions. We highlight breakthrough technologies including shear wave elastography, strain ratio measurements, and advanced quantitative methods that provide detailed mechanical characterization of breast tissue. The review specifically addresses how these techniques improve the detection of small, early-stage tumors and reduce false-positive rates in dense breast tissue. Artificial intelligence integration has transformed breast elastography workflow, introducing sophisticated pattern recognition and automated lesion characterization. The review also addresses current challenges, including the need for technical standardization, ensuring consistent reproducibility across different settings, managing economic costs, improving accessibility, and developing comprehensive education and training programs for healthcare providers. We analyze emerging solutions, including novel quality assurance protocols and adaptive imaging techniques that accommodate different breast tissue compositions. On summarizing and critically analyzing clinical evidence and technological developments, this review provides a comprehensive perspective on the current state and future directions of breast ultrasound elastography. The integration of advanced elastographic methods with artificial intelligence and standardized protocols promises to establish ultrasound elastography as an essential tool in early breast cancer detection, potentially improving patient outcomes through earlier intervention.
本综述探讨了超声弹性成像在乳腺癌检测方面的最新进展，重点关注技术创新、临床验证以及早期诊断中出现的挑战。我们分析了现代弹性成像技术如何发展以满足对准确、无创的乳腺癌筛查和特征描述的迫切需求。超声弹性成像最近的方法学发展显著增强了其诊断能力，特别是在区分乳腺恶性病变和良性病变方面。我们重点介绍了包括剪切波弹性成像、应变率测量以及提供乳腺组织详细力学特征的先进定量方法等突破性技术。本综述特别阐述了这些技术如何提高对小的早期肿瘤的检测能力，并降低致密乳腺组织中的假阳性率。人工智能的整合改变了乳腺弹性成像工作流程，引入了复杂的模式识别和自动病变特征描述。本综述还讨论了当前的挑战，包括技术标准化的必要性、确保在不同环境下具有一致的可重复性、管理经济成本、提高可及性以及为医疗服务提供者制定全面的教育和培训计划。我们分析了新兴的解决方案，包括适应不同乳腺组织成分的新型质量保证方案和自适应成像技术。在总结和批判性分析临床证据及技术发展的基础上，本综述全面阐述了乳腺超声弹性成像的现状和未来方向。将先进的弹性成像方法与人工智能及标准化方案相结合，有望使超声弹性成像成为早期乳腺癌检测的重要工具，通过早期干预可能改善患者预后。
