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RELEASE: ScreenPoint Medical and Volpara Health AI Predicts Long-Term Breast Cancer Risk

-Artificial intelligence from ScreenPoint Medical and Volpara Health demonstrates its ability to predict long-term breast cancer risk.

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RELEASE: ScreenPoint Medical and Volpara Health AI Predicts Long-Term Breast Cancer Risk

-Artificial intelligence from ScreenPoint Medical and Volpara Health demonstrates its ability to predict long-term breast cancer risk

Research from the Mayo Clinic and UCSF reveals that the combination of Transpara ® Exam Score with Volpara TruDensity ® can predict the long-term risk of invasive breast cancer

NIJMEGEN, The Netherlands and WELLINGTON, New Zealand, May 23, 2023 /PRNewswire/ -- Researchers from the Mayo Clinic (Rochester, MN) and the University of California, San Francisco confirmed that the combination of artificial intelligence imaging algorithms ( IA) and breast volume density may help predict the long-term risk of breast cancer, particularly invasive disease. The study, titled "Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer," was recently published in the Journal of Clinical Oncology.

The study was designed to determine whether an AI algorithm could contribute to the prediction of long-term risk of interval and advanced cancers. The researchers used images from 2,412 women with invasive breast cancer and 4,995 matched controls who had received digital mammograms between 2 and 5.5 years before their cancer diagnosis. The performance of conventional assessment measures (traditional radiologist interpretation and BI-RADS® density categories) was compared with the ability of newer AI-powered techniques (precise volumetric density measurements and image-based malignancy risk scores). ) for the prediction of long-term risk of advanced and interval cancers.

Results of the investigation:

The Transpara AI score improves long-term risk prediction when combined with clinical risk factors, including breast density, for general invasive, screen-detected, advanced, and non-advanced cancers. For interval cancers, TruDensity measures remained the most important for discrimination, even years before the cancer.

AI software used in this study

Transpara Exam Score is an image-based risk tool that rates exams using a 10-point scale and is used for simultaneous reading of mammograms. The higher the score, the higher the risk of cancer on the mammogram. Clinical research conducted with Transpara shows that scores between 1 - 7 (low risk) have a negative predictive value of 99.97%. The Volpara TruDensity AI algorithm uses a combination of X-ray physics and machine learning to generate an accurate volumetric measure of breast composition to eliminate variability that can arise from human interpretation.

"Although we have known for decades that density and breast cancer risk are correlated, recent research has really boosted our ability to better understand the effects of density combined with imaging-based risk to drive personalized medicine for women." explained Professor Nico Karssemeijer, PhD, Chief Scientific Officer at Screenpoint Medical, and a faculty member at Radboud University.

Used by leading centers around the world, Transpara has been used to analyze more than 4 million mammograms. Research shows that up to 45% of interval cancers can be detected earlier using Transpara, while helping to reduce workload and optimize workflow.

"Breast density is a critical factor in breast cancer risk assessment, and an objective, volumetric measurement of density is critical. Through the power of AI, we can uncover valuable information that helps clinicians identify people at risk for cancer and tailor personalized screening and prevention strategies," said Ralph Highnam, PhD, director of Science and Innovation at Volpara Health.

Volpara's software is used to assess the breast density of more than 6 million women a year. TruDensity has been shown to reduce reader variability. Radiologists agree with Volpara's assessment of non-dense (a or b) or dense (c or d) 96% of the time.

"Early imaging-based risk identification may provide a more effective pathway to screening and care for high-risk women. This approach should not only save lives, but allow women to experience as little disruption to their lives as possible when necessary." to pay attention to them. Today's screening requires this kind of focused and personalized approach. We hope that the work we are doing will enable women and their professionals to provide the right care at the right time," added Professor Karssemeijer.

About ScreenPoint Medical

ScreenPoint Medical translates cutting-edge machine learning research into technology accessible to radiologists to improve screening workflow, decision confidence, and breast cancer risk assessment. Radiologists around the world trust Transpara because it has been developed by experts in machine learning and image analysis and updated with user feedback from renowned breast imaging specialists.

See all the evidence at: https://screenpoint-medical.com/published-evidence/peer-reviewed-publications

About Volpara Health (ASX: VHT)

Volpara Health makes software to save families from cancer. Healthcare professionals use Volpara to better understand cancer risk, help patients make self-care decisions, and guide recommendations for additional imaging, genetic testing, and other interventions. Our AI-based image analysis enables radiologists to accurately quantify breast tissue and helps technicians produce mammograms with optimal image quality, positioning, compression, and dose. In an industry facing growing staff shortages, our software streamlines operations and provides key performance insights that support continuous quality improvement.

For more information, visit volparahealth.com

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