Best Practices for AI in Mammography with TomoSPOT, Beekley Skin Marking System for 3D mammography

09/09/2025

Best Practices for AI in Mammography with TomoSPOT, Beekley Skin Marking System for 3D mammography Artificial Intelligence (AI) is one of the hottest topics in healthcare currently. The subject is permeating most industries, and breast imaging is no different. Many may wonder how the use of AI will affect their breast programs current policies and procedures. AI and Skin Markers: Systematic Skin Marking is Essential AI is quickly being adopted to aid radiologists and act as a second set of eyes while reading a mammogram. Implementing AI within your breast center can be very challenging if you use incorrectly shaped skin markers for areas of clinical concern and/or landmarks. Using the incorrect marker may mislead the AI engine. For example, if a pellet or BB marker is placed on a palpable mass in the retroareolar area, the algorithm may assume that the density adjacent to the BB is a nipple out of profile rather than a true lesion that requires follow up. Tomosynthesis excels at visualizing architectural distortion related to a prior surgery. Often, the architectural distortion has not been visualized on previous 2D mammograms, going back five, sometimes ten years.1 If a surgical scar is not marked with a scar marker, the AI engine may flag the area as a potential cancer and interrupt the radiologists workflow as they investigate the patients history and/or years-old images. Ultimately, the patient may be recalled.

The ACRs Data Science Institute: https://www.acr.org/Data-Science-and-Informatics/AI-in-Your-Practice/AI-Use-Cases/Use-Cases/Mammography-Skin-Markers has collected use cases to support the implementation of artificial intelligence within breast centers. They state, “Our use cases help radiologists and allied professionals by ensuring that AI tools provide needed information, can be efficiently implemented into daily workflow, and have the potential to improve the quality and efficiency of patient care.” The mammography skin marker use case: https://www.acr.org/Data-Science-and-Informatics/AI-in-Your-Practice/AI-Use-Cases/Use-Cases/Mammography-Skin-Markers, that AI developers look toward clearly identifies which shape should be used for nipples, scars, and moles. Implementing this type of skin marking system can avoid confusion and potential callbacks.

An Easy, Cost-Effective Solution
Since the Data Science Institute has provided a skin marking use case for the development of AI datasets, the best practice is to follow the ACRs practice parameters and use different and correctly shaped skin markers for mammography. https://beekley.com/breast-health/mammography-skin-markers, For those facilities that have not yet implemented AI making an easy change by implementing skin markers today will be an investment in your future.

Breast imaging centers using the Beekley Skin Marking System for digital and 3D breast tomosynthesis report better communication between patient, technologist, and radiologist; fewer questions, and fewer additional views. TomoSPOT skin markers for 3D mammography, https://beekley.com/mammography-skin-markers/tomospot-for-digital-breast-tomosynthesis

A proactive, routine skin marking protocol in 3D mammography with TomoSPOT has been proven to improve specificity and:

1- Reduce risk of false negatives and false positives

2- Reduce unnecessary additional views and callbacks

3- Provide visual documentation of breast anatomy from year to year and when transferring images

4- Reduce radiologist reading time on average by 1.34 minutes per case

Tomosynthesis Abstract Preview Radiologist Read-Time, https://beekley.com/Portals/0/Resource%20Library/Case%20Studies%20&%20White%20Papers/Mammography/Tomosynthesis%20Abstract%20Preview%20Radiologist%20Read-Time.pdf

Share this article on LinkedIn

Related posts

Featured articles