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John R. Fischer, Senior Reporter | August 22, 2022
Volpara has teamed up with Microsoft to speed up development of its cardiac solution that identifies and quantifies breast arterial calcifications for indications of future heart disease risk. (Photo courtesy of Volpara)
Volpara Health Technologies is leveraging Microsoft’s Azure Machine Learning to speed up development of a new solution that incorporates its mammography technology to detect and quantify breast arterial calcifications (BAC) and prevent heart disease in women.
Using Volpara’s quantitative and objective breast density scoring AI technology, the solution will create a composition map to identify BAC on scans. Microsoft Azure Machine Learning, part of the Azure AI platform, is a cloud service used to rapidly build, train and deploy models. It will be used to improve the BAC model and data processing.
The launch of the cardiac decision support tool would mark Volpara’s entrance into the $146.4 billion cardiovascular disease market. “Though we are in the early stages of BAC product development, this collaboration will accelerate our efforts as we advance science together,” said Volpara’s co-founder and chief science and innovation officer Ralph Highnam, who will oversee the BAC project.
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The BAC product would enable women to learn more about and take steps to protect their cardiovascular health during regular breast screenings. Findings can be delivered to the provider or through Volpara’s partner network with the Volpara Breast Health Platform, an intelligent screening software that provides clinical decision support and personalizes detection.
Volpara received a patent for its BAC detection and quantification method from the U.S. Patent and Trademark Office in February 2022. With access to more than 35% of the U.S. breast screening market, Volpara already has the installation base to deploy the solution.
The company has used Microsoft’s SaaS and cloud products to develop other solutions, including the most recent FDA-cleared version of its core AI algorithm. The technology has assessed breast composition in more than 14.5 million women, to date, through Volpara’s analysis of more than 67 million mammography and tomosynthesis images.
This collection of scans is one of the world’s largest de-identified image data sets and will be used in the BAC project.
"Integrating Azure Machine Learning as a service with Volpara's solution allows providers to connect data and look for meaningful signals through predictive analytics. Through this technology, physicians can identify cardiac risk in patients who may not be aware that they're at higher risk, empowering them and their provider to take proactive steps toward their health,” said Tom McGuinness, corporate vice president of global healthcare and life sciences at Microsoft.
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