Full-field digital mammograms (right mediolateral oblique view)

Full-field digital mammograms (right mediolateral oblique view) in a 59-year-old woman show (A) the screening mammogram obtained during the study period and (B) the screening mammogram obtained in the subsequent screening round. The first screening mammogram (A) had a very low combined risk score (lowest 0.1%) as determined by the combination model with texture risk and the examination score. The woman was not recalled and did not receive a breast cancer diagnosis throughout the 5-year follow-up. Image courtesy of Radiological Society of North America 


August 29, 2023 — Combining artificial intelligence (AI) systems for short- and long-term breast cancer risk results in an improved cancer risk assessment, according to a study published in Radiology, a journal of the Radiological Society of North America (RSNA). 

Most breast cancer screening programs take a one-size-fits-all approach and follow the same protocols when it comes to determining a woman’s lifetime risk of developing breast cancer. Using mammography-based deep learning models may improve the accuracy of breast cancer risk assessment and can also lead to earlier diagnoses.  

“About 1 in 10 women develop breast cancer throughout their lifetime,” said study author Andreas D. Lauritzen, Ph.D., from the Department of Computer Science at the University of Copenhagen in Denmark. “In recent years, AI has been studied for the purpose of diagnosing breast cancer earlier by automatically detecting breast cancers in mammograms and measuring the risk of future breast cancer.” 

A variety of AI tools exist to aid in detecting cancer risk. Diagnostic AI models are trained to detect suspicious lesions on mammograms and are well suited to estimate short-term breast cancer risk. 

More suitable for long-term breast cancer risk are texture AI models, capable of identifying breast density. Women with dense breast tissue are at higher risk of developing breast cancer and may benefit from supplemental MRI screening. 

“It is important to enable reliable and robust assessment of breast cancer risk using information from the screening mammogram,” Dr. Lauritzen said. 

For this study, Dr. Lauritzen and his research team sought to identify whether a commercially available diagnostic AI tool and an AI texture model, trained separately and then subsequently combined, may improve breast cancer risk assessment. 

The researchers used the diagnostic AI tool Transpara and a texture model that was developed by the researchers. A Dutch training set of over 39,000 exams was used to train the models. The short- and long-term risk models were combined using a three-layer neural network. 

The combined AI model was tested on a study group of more than 119,000 women who were included in a breast cancer screening program in the Capital Region of Denmark between November 2012 and December 2015. The average age of the women was 59 years. 

Compared to the diagnostic and texture models alone, the combined AI model showed an overall improved risk assessment for both interval and long-term cancer detection. Interval cancers are those that are found between routine screenings. 

The model also enabled identification of women at high risk for breast cancer. Women identified by the combined model as having the 10% highest combined risk accounted for 44.1% of interval cancers and 33.7% of long-term cancers. 

Using AI to identify a women’s breast cancer risk from a single mammogram will not only result in earlier cancer detection but can also improve the strain on the health care system due to the worldwide shortage of specialized breast radiologists. 

“Current state-of-the-art clinical risk models require multiple tests such as blood work, genetic testing, mammogram and filling out extensive questionnaires, all of which would substantially increase the workload in the screening clinic,” Dr. Lauritzen said. “Using our model, risk can be assessed with the same performance as the clinical risk models but within seconds from screening and without introducing overhead in the clinic.” 

For more information: www.rsna.org 

Find more RSNA conference coverage here 

 

Related Breast Density Content:  

VIDEO: FDA Update on the US National Density Reporting Standard - A Discussion on the Final Rule   

One on One … with Wendie Berg, MD, PhD, FACR, FSBI   

Task Force Issues New Draft Recommendation Statement on Screening for Breast Cancer   

Creating Patient Equity: A Breast Density Legislative Update   

FDA Needs to Ensure that Information on Dense Breast Notifications are Clear and Understandable to all Members of the Public   

AI Provides Accurate Breast Density Classification   

VIDEO: The Impact of Breast Density Technology and Legislation   

VIDEO: Personalized Breast Screening and Breast Density   

VIDEO: Breast Cancer Awareness - Highlights of the NCoBC 2016 Conference   

Fake News: Having Dense Breast Tissue is No Big Deal   

The Manic World of Social Media and Breast Cancer: Gratitude and Grief   

 

Related Breast Imaging Content:  

Breast Cancer Risk Calculator Can Assess Risk of Advanced Breast Cancer  

Uncertainty About Breast Cancer Risk and Screening Choices and Perceived Risk Heighten with Breast Density Awareness Following Mammography  

Creating Patient Equity: A Breast Density Legislative Update  

FDA Needs to Ensure that Information on Dense Breast Notifications are Clear and Understandable to all Members of the Public  

AI Provides Accurate Breast Density Classification  

VIDEO: The Impact of Breast Density Technology and Legislation  

VIDEO: Personalized Breast Screening and Breast Density  

VIDEO: Breast Cancer Awareness - Highlights of the NCoBC 2016 Conference  

Fake News: Having Dense Breast Tissue is No Big Deal  

The Manic World of Social Media and Breast Cancer: Gratitude and Grief 


Related Content

News | Artificial Intelligence

February 29, 2024 — AIxSCAN, Inc., a Sunnyvale, CA-based developer of a next generation artificial intelligence (AI) ...

Time February 29, 2024
arrow
News | Artificial Intelligence

February 28, 2024 — iCAD, Inc., a global leader in clinically proven AI-powered solutions that enable medical providers ...

Time February 28, 2024
arrow
News | Women's Health

February 27, 2024 — Hologic, Inc. continues to deliver on its commitment to advancing women’s health by unveiling new ...

Time February 27, 2024
arrow
News | Artificial Intelligence

February 27, 2024 — As artificial intelligence (AI) is increasingly used in radiology, researchers caution that it’s ...

Time February 27, 2024
arrow
Feature | HIMSS | Christine Book

February 26, 2024 — This year’s Healthcare Information and Management Systems Society HIMSS Global Conference and ...

Time February 23, 2024
arrow
News | Breast Imaging

February 23, 2024 — ScreenPoint Medical is showcasing its industry leading Transpara Breast AI at the 2024 European ...

Time February 23, 2024
arrow
News | Breast Imaging

February 22, 2024 — The FAST-Forward randomized trial from the UK found that ultrahypofractionated whole breast ...

Time February 22, 2024
arrow
Feature | HIMSS | By Christine Book

February 22, 2024 — With just weeks to go before HIMSS 2024, the Global Conference and Exhibition of the Healthcare ...

Time February 22, 2024
arrow
News | Artificial Intelligence

February 22, 2024 — Hartford HealthCare has announced the unveiling of its Center for AI Innovation in Healthcare ...

Time February 21, 2024
arrow
Videos | Information Technology

Industry trade shows and conferences seem to be making their comeback in 2024. And the Healthcare Information and ...

Time February 21, 2024
arrow
Subscribe Now