COLORADO SPRINGS, Colo., April 16, 2025 /PRNewswire/ -- ScreenPoint Medical will showcase innovative new capabilities of its industry leading Breast AI, Transpara®, at the 2025 Society of Breast Imaging Symposium, April 24-27, 2025 (Booth #330). The most clinically validated AI for breast cancer detection on the market, Transpara provides radiologists with a 'second pair' of eyes to help detect cancers earlier and reduce recall rates.

ScreenPoint will highlight its latest advancements, including Transpara 2.1, an update and improved breast cancer detection d algorithm that further refines Transpara's industry-leading performance. This includes compatibility with options for breast density (BI-RADS like and volumetric) and temporal comparison with multiple prior exams. This robust temporal comparison capability will be the first of its kind in the market, and will allow suspicious areas on a current study to be analyzed against up to 3 priors over 6 years. The Transpara 2.1 algorithm is both CE-marked and FDA cleared.

"We are excited about the significant improvement of Transpara performance when priors are used, especially when more priors with a longer time interval are included, which is in line with radiologists' experience. Our solution is designed for screening and diagnostic use to truly improve clinical workflow," said Professor Nico Karssemeijer, PhD, co-founder and Chief Scientific Officer of ScreenPoint Medical.
The clinical and workflow benefits of Transpara for improving the mammography screening process are the subject of several presentations by Alejandro Rodriguez Ruiz, PhD and Dr. Rachel F. Brem at SBI:

In the study, "Validation of a Novel Image-based AI Breast Cancer Risk Model for Mammography Screening," (Thursday, April 24, 2025, 2:45 – 3:45 PM), researchers validated the performance of Transpara Risk, an image-based AI breast cancer risk model. Results showed high risk assessment performance and robustness across screening sites and imaging system vendors and could potentially be used to support personalized breast cancer screening strategies by selecting high-risk women for supplemental imaging.

The study "Multi-site Validation of a Novel AI System for Cancer Detection in Abbreviated Breast MRI," (Thursday, April 24, 2025, 2:45 – 3:45 PM), validated the performance of AI for breast cancer detection in abbreviated DCE-MRI across multiple institutions. Results showed that the AI system for abbreviated DCE-MRI shows potential for decision support in detecting breast cancer and particularly for accurate identification of very likely normal exams.

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