Utilizing Artificial Intelligence for Early Detection of Breast Cancer

It is widely known that mammography has limitations in detecting all cancers, especially in women with dense breast tissue. This has been a long-standing issue in the medical community, causing concern for both doctors and patients.

Fortunately, there may be a solution on the horizon involving the use of artificial intelligence (AI).

Overview

The AISmartDensity tool can identify women at high risk of missed breast cancer after a negative mammogram.
The AI tool is more effective than doctors at selecting a smaller, high-risk group of women for additional screening such as MRI.
Early results from the ScreenTrustMRI trial indicate that using AI to guide supplemental MRI screenings significantly improves the detection of aggressive breast cancers, particularly in women with dense breast tissue.

When Mammograms Miss Breast Cancer

Many women require additional breast cancer screening through magnetic resonance imaging (MRI) to supplement mammograms and reduce missed cancer cases. However, the cost-effectiveness of MRI screening is hindered by the lack of qualified staff and the high operational costs of equipment, limiting its widespread use.

Excitement surrounds a new tool that can potentially address this challenge...

An Artificial Intelligence (AI) tool has been developed to determine which women should undergo supplemental MRI scans following negative mammograms. This tool identifies women at the highest risk of undetected cancer post-mammography.

The ScreenTrustMRI trial utilized this tool, called AISmartDensity, to evaluate each mammogram. Participants with a negative mammogram and a high AI score (top 6.9%) were invited to join the trial. Upon agreement to participate, women were randomly assigned to receive supplemental MRI or no MRI.

Discovered Four Times More Cancers

Preliminary findings from a randomized trial scheduled for completion in August 2025 reveal that the AI tool has detected numerous cancers that would have otherwise gone undetected.

The primary objective is to identify aggressive cancers that may grow significantly between screenings or have already spread to lymph nodes. This new AI tool has shown remarkable success, nearly quadrupling the detection rate compared to conventional methods, spotting around 64 cancers per 1,000 MRI exams versus the 16-17 cancers detected by traditional means.

Detected More Aggressive Cancers

The use of an AI-based scoring system to select a specific group for supplemental MRI after negative mammography has proven effective in detecting missed cancers, making the process more cost-efficient compared to traditional mammography.

Researchers, led by Frederik Strand, MD, PhD, from Karolinska University Hospital in Stockholm, Sweden, reported a four-fold increase in cancer detection rate using the AI tool compared to standard breast density assessments. The majority of additional cancers detected were invasive, some with multiple foci, indicating timely detection.

Notably, multifocal cancer refers to the presence of multiple tumors in the same region of the breast, usually within the same quadrant.

Addresses Various Diagnostic Challenges

Dr. Strand and colleagues highlight that while mammography has aided in early cancer detection, many cancers found in screened women are interval cancers, detected before the next scheduled screening due to symptoms. The AI tool may facilitate earlier detection by identifying high-risk individuals for screening.

Furthermore, MRI remains more accurate than mammography for women with dense breast tissue. The research team suggests that AI-based imaging analysis could streamline the diagnostic process leading to a cancer diagnosis through MRI.

The ScreenTrustMRI study enrolled 59,354 women evaluated with AISmartDensity in their mammograms. Of these, 3,821 qualified for MRI based on a top 6.9% AISmartDensity score, with 1,315 eventually randomized, and 559 completing the MRI for analysis. The median age of participants was 56, with a small percentage having a history of breast cancer or family history of the disease.

Our Conclusion

While this new AI tool does not address the issue of breast compression during mammograms potentially releasing cancer cells, it does offer a promising alternative to solely relying on mammography for cancer detection. Thermography could also be a beneficial consideration.

Thermography employs infrared technology to record the temperature of the breast's surface, detecting heat patterns and blood flow changes. Elevated temperatures in specific areas may indicate increased blood flow associated with cancerous tissue. By monitoring temperature patterns over time, doctors can identify potential developments indicative of cancer.

Summary

Mammography's limitations in detecting cancers, particularly in women with dense breast tissue, have prompted the use of supplemental MRI screening. The development of AISmartDensity, an AI tool, aims to identify high-risk individuals for further MRI screening following negative mammograms. This AI tool has demonstrated significant improvement over traditional methods, leading to enhanced cancer detection rates. Early findings from the ScreenTrustMRI trial show that utilizing AISmartDensity enhances the detection of invasive cancers, making supplemental MRI screening more cost-effective.

Written by: Susan Parker

Susan Parker is a 49-year-old Senior Manager at a marketing firm. With two older children becoming more independent, she is now focusing on her own health and wellbeing. She’s passionate about natural and holistic health approaches, and values high-quality, trustworthy products. Susan enjoys yoga, gardening, reading, and cooking, and seeks to stay energetic and sharp while balancing a busy career and personal life.