Siemens Healthineers has introduced a new software solution that speeds up the entire reading workflow for breast imaging: Mammovista B.smart. Also new is the Teamplay Mammo Dashboard, a tool for dashboard-based visualization of key performance indicators (KPIs) in the breast imaging process that serves to optimize workflows. With these two new solutions, the company is extending its digital offerings for breast care. Mammovista B.smart was developed from scratch to support maximum reading performance across multiple imaging modalities. During the process of reading mammography images, AI-supported(1) workflows highlight abnormalities in breast tissue and offer a so-called "confidence score" that shows the algorithm's assessment of the probability of cancerous tissue. By implementing evidence-based AI, a significant increase in accuracy as well as a 35% (2) reduction in workload can be achieved. The new Mammovista B.smart user interface was designed based on user feedback; among other things, it reduces the number of clicks required for specific tasks wherever possible. All features, including a significant reduction in image loading time, support radiologists with their increased workloads that are the result of expanded breast-care screening programs and the need to manage greater complexity in multimodality diagnostics. "In breast imaging, it's not unusual for a radiologist to have to read datasets from up to 100 patients in one hour. Therefore, saving even a few seconds per case due to faster loading and pre-analysis using AI has significant positive impact and increases diagnostic accuracy," says Carsten Bertram, Head of X-ray Products at Siemens Healthineers.
The second innovation, Teamplay Mammo Dashboard, is a dashboard running on the Siemens Healthineers Teamplay Digital Health Platform that was specifically designed for breast care centers. Teamplay Mammo Dashboard provides an intuitive overview of specific institution, modality, and examination KPIs to reveal potential workflow optimizations. The KPIs tracked include radiation dose, device utilization, and other parameters, making important steps of the mammography examination process transparent while identifying possible bottlenecks. This enables institutions to increase workflow efficiency and standardization in imaging. With this newest addition to the Teamplay performance management applications based on the Teamplay Digital Health Platform, Siemens Healthineers continues to streamline operations unlocking potential productivity gains, making the most of the data acquired and providing tangible recommendations for improvements.
About Siemens Healthineers AG
Siemens Healthineers AG (listed in Frankfurt, Germany: SHL) is shaping the future of Healthcare. As a leading medical technology company headquartered in Erlangen, Germany, Siemens Healthineers enables healthcare providers worldwide through its regional companies to increase value by empowering them on their journey towards expanding precision medicine, transforming care delivery, improving the patient experience, and digitalizing healthcare. Siemens Healthineers is continuously developing its product and service portfolio, with AI-supported applications and digital offerings that play an increasingly important role in the next generation of medical technology. These new applications will enhance the company's foundation in in-vitro diagnostics, image-guided therapy, and in-vivo diagnostics. Siemens Healthineers also provides a range of services and solutions to enhance healthcare providers' ability to provide high-quality, efficient care to patients. In fiscal 2020, which ended on September 30, 2020, Siemens Healthineers, which has approximately 54,000 employees worldwide, generated revenue of €14.5 billion and adjusted EBIT of €2.2 billion.
1. Next-Gen AI is an option and available with Transpara® powered by FusionAI™, ScreenPointMedical.
2. Using AI to triage which screening mammograms benefit from a double reading strategy. C Balta, PhD, Nijmegen, Netherlands; A Rodriguez-Ruiz; C Mieskes; N Karssemeijer, PhD; S H Heywang-Koebrunner, MD. RSNA 2020
