Practical Application of AI in Breast Imaging

Artificial Intelligence (AI) in the field of Radiology is rapidly evolving from an interesting research concept to an essential new tool in the radiologist’s toolkit. Radiologists and imaging practices need to fully understand the strengths and limitations of AI in order to successfully integrate AI into the radiologist’s workflow.

MRI Online is pleased to bring you this unique Mastery Course (earn 1.75 radiology CME credits) from Dr Roger Yang on the Practical Application of Artificial Intelligence (AI) in Breast Imaging.

This breast radiology course takes a pragmatic, practice-based approach through the eyes of a radiologist who has implemented AI at their practice.

In the first half of the course, Dr Yang addresses head-on the various perspectives on use of AI in Radiology, including patient, physician, media, and ethical viewpoints. He then goes in-depth on the practical application of AI for the radiologist, including the following topics:

• Considerations when selecting and installing a mammography AI product in your practice
• Comparisons of CAD vs AI and concurrent use of AI in the mammography workflow
• Practical approaches to using AI in worklist triage
• Efficacy of AI applied to breast ultrasound in differentiation between benign and malignant lesions

In the second half of the course, Dr Yang walks through real-world examples and showcases the results from CAD, AI, and the radiologist in the same case. Key images of the result with and without AI and CAD are also provided for the learner.

Case examples include:

• Normal mammograms with dense breast tissue and fatty breast tissue
• Breast malignancies and traditional CAD
• AI use…
  • in a case of complex tissue and calcifications
  • at a lumpectomy site
  • in a case of fibroadenoma
  • in a case of papilloma
  • in a case of malignancy with subtle cancer
  • in a case of malignancy with architectural distortion
  • in a case of DCIS calcifications
• …and more!

This course will show you how AI is being effectively used in Breast Imaging practice today. When appropriately implemented, AI has the power to help the radiologist identify suspicious lesions more quickly. Combined with the radiologist’s knowledge of the patient’s clinical history and prior scans, AI can aid the accuracy and efficiency of breast cancer screening and help address health disparity gaps in interpretation variability across practices.

Disclaimer: The presenter will instruct with real-world cases using the software available in their practice. Other products are available and may also be considered.