DeepHealth, a subsidiary of RadNet, has received expanded FDA clearance for its SmartMammo Dx AI algorithm, now compatible with GE HealthCare's Senographe Pristina mammography systems. This follows initial clearance for Hologic systems in 2021. Separately, ScreenPoint Medical's Transpara 2.1 Breast AI gained FDA clearance for its updated algorithm, enhancing breast density assessment and temporal comparison capabilities.
SmartMammo Dx Expansion
SmartMammo Dx identifies suspicious soft tissue lesions and calcifications in digital breast tomosynthesis (DBT) mammograms, assigning specific suspicion levels. According to DeepHealth, the software has demonstrated a 23% higher detection rate of breast cancer in women with dense breasts and a 20% higher detection rate in African American women. Kees Wesdorp, the president and CEO of DeepHealth, stated, "This FDA clearance allows us to expand access to high-quality breast cancer screening to more patients."
Transpara 2.1 Advances
ScreenPoint Medical's Transpara 2.1 offers an updated algorithm based on insights from global users, compatible with breast density (BIRADS and volumetric) and temporal comparison. The temporal comparison feature allows analysis of suspicious areas against up to three prior studies over six years. Professor Nico Karssemeijer, co-founder and Chief Scientific Officer of ScreenPoint Medical, noted, "We are very excited about the significant improvement of Transpara performance when priors are used, especially when more priors with a longer time interval are included."
Clinical Evidence and Impact
Multiple studies presented at the Radiological Society of North America (RSNA) meeting highlighted the benefits of Transpara. A study from UMass Memorial Health found that using Transpara scoring to prioritize reading reduced turnaround time in breast cancer detection and diagnosis. Another study in Germany showed that Transpara increased the cancer detection rate, specifically for invasive cancers. Additionally, research indicated that Transpara performs well in both dense and non-dense breasts.
Additional Detection Success
ScreenPoint Medical's Mammography Screening with Artificial Intelligence (MASAI) study of 105,000 women found that Transpara increased cancer detection by 29% and reduced screen-reading workload for radiologists by 44%. Dr. Kristina Lång, lead study researcher from Lund University, commented, "Our findings indicate that AI-supported screening can significantly enhance the early detection of clinically relevant breast cancers while reducing the workload for radiologists."
