Breast cancer remains the most commonly diagnosed malignancy and a leading cause of cancer-related mortality among women worldwide. Neoadjuvant chemotherapy (NAC) is increasingly used, particularly in aggressive subtypes such as HER2-positive and triple-negative breast cancer, where achieving a pathological complete response (pCR) is strongly associated with improved outcomes. Early and accurate assessment of therapeutic response is therefore essential to enable timely treatment adaptation. Conventional imaging methods—including magnetic resonance imaging (MRI), computed tomography (CT), mammography, and B-mode ultrasound—mainly detect macroscopic tumor shrinkage and often lagging behind biological alterations, as they rely primarily on size-based assessment. Quantitative ultrasound (QUS) is an emerging, non-invasive technique that analyzes raw radiofrequency (RF) ultrasound data to extract spectral, scattering, and attenuation parameters, allowing detailed characterization of tumor microstructure. When combined with parametric mapping, texture analysis, and advanced radiomic or deep learning approaches, QUS can capture subtle tissue alterations at an early stage of therapy and help predict pathological response before conventional imaging detects morphologic change. Integration with molecular and clinical data further enhances predictive performance, enabling adaptive and personalized treatment strategies. This narrative review summarizes current evidence on the clinical utility of QUS in monitoring NAC response in breast cancer, outlines the methodological foundations of this technology, and discusses key challenges to its broader implementation—particularly the need for standardized acquisition and processing protocols, robust interpretive algorithms and large, prospective, multicenter validations to confirm its impact on clinical decision-making and patient outcomes, and to accelerate its translation into precision oncology practice.
乳腺癌仍是全球女性中最常被诊断的恶性肿瘤及癌症相关死亡的主要原因。新辅助化疗的应用日益广泛，尤其在HER2阳性和三阴性乳腺癌等侵袭性亚型中，实现病理完全缓解与改善预后密切相关。因此，早期准确评估治疗反应对于及时调整治疗方案至关重要。传统影像学方法——包括磁共振成像、计算机断层扫描、乳腺X线摄影和B型超声——主要检测宏观肿瘤缩小，且常滞后于生物学改变，因其主要依赖基于尺寸的评估。定量超声是一种新兴的无创技术，通过分析原始射频超声数据提取频谱、散射和衰减参数，实现对肿瘤微观结构的详细表征。当结合参数成像、纹理分析及先进的影像组学或深度学习方法时，定量超声能在治疗早期捕捉细微的组织改变，并在传统影像检测到形态学变化前帮助预测病理反应。与分子和临床数据的整合进一步提升了预测性能，有助于实现适应性及个体化治疗策略。本文综述了定量超声在监测乳腺癌新辅助化疗反应中临床应用的现有证据，概述了该技术的方法学基础，并讨论了其广泛实施面临的主要挑战——特别是需要标准化的采集与处理方案、稳健的解读算法以及大规模前瞻性多中心验证，以确认其对临床决策和患者结局的影响，并加速其向精准肿瘤学实践的转化。
肿瘤(癌症)患者之家