CAMRT 2024: Population-Based Mammography Quality Using AI (2) Enhancing Breast Cancer Detection: The Impact of Breast Tomosynthesis on Screening Programs

CAMRT 2024: Population-Based Mammography Quality Using AI (2) Enhancing Breast Cancer Detection: The Impact of Breast Tomosynthesis on Screening Programs

No continuing education credits

1) Population-Based Mammography Quality Using AI

Presenter: Stephanie Schofield, RTR, Nova Scotia Health Authority

Positioning is the number one reason for failure of accreditation in Mammography. Understanding daily performance is crucial for continuous quality improvement.

Learning Objectives:
– Review the current CAR MAP guidelines for image quality, comparing this to routine quality assessments in mammography.
– Discuss the need for image quality feedback to technologists that is consistent, objective and non-punitive.
– Review how AI can be used to monitor, report and improve image quality.

2) Enhancing Breast Cancer Detection: The Impact of Breast Tomosynthesis on Screening Programs

Presenter: Linda Vair, RTR, ACR, CBIS, Assistant Director of Medical Imaging, Horizon Health Network

Learning Objectives:
– Understand the significant role of Digital Breast Tomosynthesis (DBT) in breast imaging, including advantages over traditional 2D mammography
– Evaluate current guidelines and recommendations regarding the use of DBT in breast cancer screening
– Discuss the clinical evidence supporting the effectiveness of DBT in improving breast cancer detection rates