ScreenPoint Medical’s Transpara solution is now accessible on Fujifilm’s ASPIRE Cristalle mammography system with digital breast tomosynthesis to enhance reading accuracy for radiologists.
Powered by Fusion AI for 2D and 3D mammography, Transpara is expected to help ASPIRE Cristalle users to identify lesions earlier, and in the long-term, reduce breast cancer mortality rates.
“As AI continues to advance, it has the potential to reshape modern healthcare and breast cancer screenings. It has the potential to improve radiologist's workflow by flagging priority cases and directing mammographers to suspect areas. With the power of AI, these exams would automatically move up in the queue so readers can review and diagnose them immediately to prescribe fast next steps and accurate care,” Christine Murray, women's health product manager for Fujifilm Medical Systems U.S.A., told HCB News.
The ASPIRE Cristalle with DBT solution is designed to enhance image quality by adding additional compression and intelligent image processing. It can do this at low doses for every breast type, including implants.
ScreenPoint Medical’s solution complements this optimization through its three main components:
Transpara Perception Aid for directly marking findings that may be significant abnormalities
Transpara Decision Support to help radiologists identify and query suspicious regions
Transpara Score to categorize mammograms in ten equally-sized groups that separate cancerous findings from normal exams
In clinical studies, Transpara identified up to 35% of exams with interval cancers found on earlier mammograms and labeled up to 70% of exams as most likely normal. This reduces workload for radiologists.
Studies have also shown that AI for breast cancer screening reduces radiologist workload by up to 70% without decreasing cancer detection. As a result, the technology is expected to help reduce the more than 270,000 women diagnosed with breast cancer each year in the U.S. and 40,000 who die from it annually.
“Radiologists in mammography today deserve — and need — to be equipped with the clinical decision support tools they need to improve mammography quality and to identify breast cancer faster and earlier than ever before,” said Murray. “Advanced AI-based solutions, combined with state of the art mammography systems, are poised to help radiologists identify potential cancers faster by bringing attention to significant abnormalities, which in turn increases the chances of more women surviving breast cancer.”
