Artificial intelligence in breast surgery: Current applications, challenges, and future perspectives

Area of Science:

• Surgical Oncology
• Medical Imaging
• Artificial Intelligence

Background:

• Breast cancer surgery is evolving with technological advancements.
• Artificial intelligence (AI) offers potential for improved precision and personalization in surgical care.
• Current applications of AI span the entire surgical continuum for breast cancer.

Purpose of the Study:

• To review AI applications in breast cancer surgery across preoperative, intraoperative, and postoperative stages.
• To identify advancements and challenges in integrating AI into surgical practice.
• To highlight the potential of multimodal AI approaches in breast cancer care.

Main Methods:

• A narrative review methodology was employed.
• A structured literature search was conducted across PubMed, Scopus, and Web of Science.
• Studies published over the last 15 years focusing on AI in breast cancer surgery were included.

Main Results:

• AI aids preoperative planning through enhanced tumor detection, segmentation, and margin assessment.
• Intraoperative AI improves accuracy via real-time image guidance and robotic assistance.
• Postoperative AI facilitates complication prediction, recurrence monitoring, and personalized follow-up.

Conclusions:

• AI integration across the surgical continuum promises enhanced accuracy, reduced complications, and improved patient-centered care in breast cancer surgery.
• Challenges such as data standardization, interpretability, ethics, and clinical integration require further attention.
• Interdisciplinary collaboration is crucial for realizing the full clinical potential of AI in surgical oncology.