por Lisa Chamoff
, Contributing Reporter | July 01, 2019
From the July 2019 issue of HealthCare Business News magazine
“We don’t dictate how the code is used,” said Kevin Harris, chief executive officer of CureMetrix. “They can send suspicious cases to specialists, read them in the morning with fresh eyes, or before a woman leaves the office.”
The software can be set to a sensitivity of 99 percent and internal studies have shown that doctors may be able to read through their worklist up to 40 percent faster.
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The company developed the AI technology by collecting more than two million images from around the world.
“We’ve taken a much more scientific approach to doing this, which is playing out in the results,” Harris said.
At last year's RSNA, Densitas debuted its densitasquality solution, which is a fully automated, AI-based evaluation of mammographic image quality with a focus on positioning errors, aimed at supporting imaging centers that are required to meet the recently enforced Enhancing Quality Using the Inspection Program (EQUIP) guidelines as part of annual MQSA inspections.
The solution gives assessments of various different criteria relating to proper positioning.
"Every mammogram that is acquired is processed by our algorithms," said Mohamed Abdolell, chief executive officer of Densitas. "It's the only solution out there that's AI based."
The solution presents results related to positioning errors at the point of care to technologists, so they can avoid recalling a patient for repeats of their mammography exams due to positioning errors.
"That's a major opportunity to really move the needle in delivering improved quality of care," Abdolell said.
In April 2018, the company received FDA clearance for densitasdensity, an AI-powered software for breast density assessment.
Abdolell said the software is unique in that it processes the "for presentation" images that are routinely archived in the PACS.
Integrating seamlessly with the clinical workflow, the zero-click multi-vendor-compatible software evaluates breast density in current and prior images of the same patient, generating automated density reports to be included and viewed in studies when mammograms are displayed on the radiologist's workstation.
"Unlike other commercially available technologies, densitasdensity enables the customer to perform retrospective analysis from all the routinely archived images on their PACS," Abdolell said. "Other solutions typically require the raw images to be routed from the scanner, and those images are routinely discarded and so cannot be evaluated retrospectively. As a result, if a customer switches from one algorithm or scanner vendor/model to another, they can apply densitasdensity to those prior images. If the customer uses different algorithms for current and past images, the results would be inconsistent."