AI Tool Improves Accuracy of Breast Cancer Imaging

A computer program trained to see patterns among thousands of breast ultrasound images can aid physicians in accurately diagnosing breast cancer, a new study shows.

When tested separately on 44,755 already completed ultrasound exams, the artificial intelligence (AI) tool improved radiologists' ability to correctly identify the disease by 37 percent and reduced the number of tissue samples, or biopsies, needed to confirm suspect tumors by 27 percent.

Led by researchers from the Department of Radiology at NYU Langone Health and its Laura and Isaac Perlmutter Cancer Center, the team’s AI analysis is believed to be the largest of its kind, involving 288,767 separate ultrasound exams taken from 143,203 women treated at NYU Langone hospitals in New York City between 2012 and 2018. The team’s report publishes online Sept. 24 in the journal Nature Communications.

"Our study demonstrates how artificial intelligence can help radiologists reading breast ultrasound exams to reveal only those that show real signs of breast cancer and to avoid verification by biopsy in cases that turn out to be benign," says study senior investigator Krzysztof Geras, PhD.

Ultrasound exams use high-frequency sound waves passing through tissue to construct real-time images of breast or other tissues. Although not generally used as a breast cancer screening tool, it has served as an alternative (to mammography) or follow-up diagnostic test for many women, says Geras, an assistant professor in the Department of Radiology at NYU Grossman School of Medicine and a member of the Perlmutter Cancer Center.

Ultrasound is cheaper, more widely available in community clinics, and does not involve exposure to radiation, the researchers say. Moreover, ultrasound is better than mammography for penetrating dense breast tissue and distinguishing packed but healthy cells from compact tumors.

However, the technology has also been found to result in too many false diagnoses of breast cancer, producing anxiety and unnecessary procedures for women. Some studies have shown that a majority of breast ultrasound exams indicating signs of cancer turn out to be noncancerous after biopsy.

"If our efforts to use machine learning as a triaging tool for ultrasound studies prove successful, ultrasound could become a more effective tool in breast cancer screening, especially as an alternative to mammography, and for those with dense breast tissue," says study co-investigator and radiologist Linda Moy, MD. "Its future impact on improving women's breast health could be profound," adds Moy, a professor at NYU Grossman School of Medicine and a member of the Perlmutter Cancer Center.

Geras cautions that while his team's initial results are promising, his team only looked at past exams in their latest analysis, and clinical trials of the tool in current patients and real-world conditions are needed before it can be routinely deployed. He also has plans to refine the AI software to include additional patient information, such as a woman's added risk from having a family history or genetic mutation tied to breast cancer, which was not included in their latest analysis.

For the study, over half of ultrasound breast examinations were used to create the computer program. Ten radiologists then each reviewed a separate set of 663 breast exams, with an average accuracy of 92 percent. When aided by the AI model, their average accuracy in diagnosing breast cancer improved to 96 percent. All diagnoses were checked against tissue biopsy results.

The latest statistics from the American Cancer Society estimate that one in eight women (13 percent) in the U.S. will be diagnosed with breast cancer over their lifetime, with more than 300,000 positive diagnoses in 2021 alone.

Shen Y, Shamout FE, Oliver JR, Witowski J, Kannan K, Park J, Wu N, Huddleston C, Wolfson S, Millet A, Ehrenpreis R, Awal D, Tyma C, Samreen N, Gao Y, Chhor C, Gandhi S, Lee C, Kumari-Subaiya S, Leonard C, Mohammed R, Moczulski C, Altabet J, Babb J, Lewin A, Reig B, Moy L, Heacock L, Geras KJ.
Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams.
Nat Commun. 2021 Sep 24;12(1):5645. doi: 10.1038/s41467-021-26023-2

Most Popular Now

AI Catches One-Third of Interval Breast …

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published...

Great plan: Now We need to Get Real abou…

The government's big plan for the 10 Year Health Plan for the NHS laid out a big role for delivery. However, the Highland Marketing advisory board felt the missing implementation...

Researchers Create 'Virtual Scienti…

There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an...

From WebMD to AI Chatbots: How Innovatio…

A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care...

New AI Tool Accelerates mRNA-Based Treat…

A new artificial intelligence (AI) model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various...

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

AI could Help Emergency Rooms Predict Ad…

Artificial intelligence (AI) can help emergency department (ED) teams better anticipate which patients will need hospital admission, hours earlier than is currently possible, according to a multi-hospital study by the...

Head-to-Head Against AI, Pharmacy Studen…

Students pursuing a Doctor of Pharmacy degree routinely take - and pass - rigorous exams to prove competency in several areas. Can ChatGPT accurately answer the same questions? A new...

NHS Active 10 Walking Tracker Users are …

Users of the NHS Active 10 app, designed to encourage people to become more active, immediately increased their amount of brisk and non-brisk walking upon using the app, according to...

New AI Tool Illuminates "Dark Side…

Proteins sustain life as we know it, serving many important structural and functional roles throughout the body. But these large molecules have cast a long shadow over a smaller subclass...

Deep Learning-Based Model Enables Fast a…

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for definitive diagnosis. However, conventional...