Ultrasound elastography: advances and challenges in early detection of breast cancer

• Published in: Frontiers in oncology Vol. 15; p. 1589142
• Main Authors: Zhou, Jianmin, Zhang, Yanchun, Shi, Shaohua
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 26.06.2025
• Subjects: artificial intelligence; breast cancer; diagnostic imaging; early detection; Oncology; screening; ultrasound elastography; breast cancer; screening; early detection; ultrasound elastography; artificial intelligence; diagnostic imaging
• DOI: 10.3389/fonc.2025.1589142
• ISSN: 2234-943X

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.