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Top 5 Positioning Challenges in Mammography

Lisa Johnston PhD – Technical Product Manager – Published on October 11, 2018

Breast imaging managers naturally seek the high-quality images that aid in the early detection of breast cancer. By understanding the positioning issues that affect image quality, they can guide their team to improved performance. Improper positioning and compression, which the FDA attributes as the cause of most clinical image deficiencies, can lead to artifacts and missing breast tissue, potentially resulting in missed cancers and reduced sensitivity.

The best solution is to understand the specific challenges each technologist faces, but it is also important to understand the big picture. In other words, what are the most common positioning issues in mammography? For that, we need data.

Data from Over 1 Million Mammograms

To identify the key positioning issues affecting mammographic quality, Volpara Solutions performed a quantitative analysis of the Volpara®Analyticscloud-based database, which now includes over 1 million mammography studies from around the globe.

The analysis showed the most common positioning issues for the MLO view:

  • Adequate pectoral muscle
  • Inframammary fold (IMF)
  • Pectoralis Muscle to posterior nipple line (PNL)

Likewise, it showed the two most common positioning issues for the CC view:

  • PNL Length
  • Excessive Exaggeration

Experienced technologists or breast imaging managers may have suspected that these positioning characteristics would be in the “top hit list.” But having objective analysis over a large data set confirms what is noted anecdotally.

Over the next several weeks, we will share some tips from the experts that can help your technologists address these positioning challenges.

In addition, Volpara will introduce the VolparaLive! system at RSNA. Mammography’s first real-time decision support system available at the point of care, the VolparaLive! system automatically analyzes patient positioning and compression, immediately providing feedback that helps technologists decide if they need to repeat an image before the patient leaves the room. While the ultimate goal is to enhance cancer detection through improved mammographic quality, receiving immediate feedback should also lead to reduced technical recalls, an enhanced technologist experience and an even better patient experience.