US | Breast
10:30 - 11:30
(Room 0.14)
About the speaker:
Dr. Silvia Pérez Rodrigo, MD
Head of the Breast Radiology Section
MD Anderson Cancer Center
Madrid, Spain
Professional Biography:
Dr. Silvia Pérez Rodrigo is a breast radiologist and Head of Breast Imaging Department in MD Anderson Cancer Center, Madrid, Spain.
Since 2010, her clinical work and research are dedicated exclusively to diagnostic and interventional breast radiology, with a particular interest in interventional, AI, MRI and postoperative, oncoplastic and reconstructive changes where she is a key opinion leader. Dr. Pérez received her MD degree from the Autónoma University of Madrid and completed his residency at the Hospital Universitario Alcorcón Madrid, Department of Radiology, doing a special training in breast interventional in Hospital Ramón y Cajal. Posteriorly she was a visiting fellow at the Department of Radiology at Memorial Sloan-Kettering Cancer Center, New York, USA.
Dr. Pérez Rodrigo serves on various committees for national and international radiology and senology societies, first and foremost the Spanish Breast Imaging Society (SEDIM) and European Society of Breast Imaging (EUSOBI) where she is a member of the executive board.
Presentation: When Ultrasound Meets AI: The Future of Breast Imaging
Abstract:
Artificial intelligence (AI) is rapidly transforming breast ultrasound, offering new opportunities to improve lesion characterization, diagnostic confidence, and workflow efficiency. Current AI-based software solutions support radiologists through automated lesion detection, standardized BI-RADS assessment, risk stratification, and decision-support tools, demonstrating promising results in sensitivity, specificity, and interobserver agreement.
However, the clinical performance of AI is closely linked to image quality, underscoring the fundamental role of high-end ultrasound systems in breast cancer diagnosis. Advances in transducer technology, spatial resolution, Doppler sensitivity, elastography, and image post-processing remain essential to maximize both human and artificial interpretation.
This presentation provides an up-to-date review of available AI software for breast ultrasound, summarizing current evidence, clinical results, and limitations. In parallel, it highlights the importance of state-of-the-art ultrasound platforms, with a focus on the latest high-end Canon systems, as the cornerstone for accurate imaging, reliable AI integration, and optimal patient care.
Learning objectives:
- Understand the current capabilities and clinical evidence of artificial intelligence in breast ultrasound.
- Recognize the critical role of high-end ultrasound technology in achieving accurate diagnosis and effective AI implementation