Breast imaging advances with new AI, MR and ultrasound solutions

Breast imaging advances with new AI, MR and ultrasound solutions

by Lisa Chamoff, Contributing Reporter | July 01, 2019
Women's Health
From the July 2019 issue of HealthCare Business News magazine


The fast engine allows the scanner to acquire data at up to 20,000 frames per second, which Souquet said can provide a base for using emerging AI technology in ultrasound.

The company also improved the user interface of the system. Instead of the trackball, it added a SonicPad touchpad, which Souquet said enables the technologist to stay focused on the image they are creating.

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“Everything is done on the pad itself,” Souquet said.

The new user interface can speed up the exam by 30 percent and reduce the technologist’s hand movement by 70 percent, reducing musculoskeletal injuries to the sonographer.

Volpara
At last year’s RSNA, the company announced a product called VolparaLive! that guides the radiologic technologist on proper positioning during a mammography exam.

“It’s basically a virtual coach,” said Belimar Velazquez, director of marketing at Volpara.

Another product, called VolparaEnterprise, tracks the quality of the mammogram based on technologists' positioning and compression over a period of time. VolparaLive! keeps track of the positioning and compression, providing feedback to the technologist before the patient leaves the exam room.

“It reduces patient anxiety because you're not calling them back for a technical recall if there are any quality issues,” Velazquez said.

The instruction is not seen by the patient and “the patients don’t even know this is taking place,” Velazquez said.

VolparaLive! has been in alpha and beta testing, with the first customer expected to go live in the beginning of June of this year.

Additionally, with the FDA requirement that all women are notified of breast density to determine if they require supplemental screening, the company has seen a resurgence of interest in its VolparaDensity product, which uses machine learning to analyze mammograms and provide breast density assessments. The product received FDA clearance in 2010, with the first installation taking place in 2011.

The company continues to improve the product’s algorithm, with more updates coming soon, Velazquez said.

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