Transforming the Mammography Enterprise.

Densitas® Inc., a global provider of A.I. technologies for digital mammography and breast screening, announced today their partnership with Mammography Educators to offer the first artificial intelligence powered telehealth technologist training platform to support business continuity in mammography facilities.

Densitas® Inc., a leading provider of A.I. technologies for digital mammography and breast screening, announced today that NorthShore University HealthSystem (NorthShore), will deploy the densitas® intelliMammo™ platform across its mammography facilities. With this deployment, breast density, clinical image quality, and breast cancer risk assessments will be automatically generated for every mammogram taken throughout the health system.

AI has the potential to deliver significant benefits to populations and health systems when used appropriately.

However, the development and application of AI poses unique challenges that require a thoughtful response to ensure appropriateness of use.

Two well-known and widely used lifetime breast cancer risk assessment tools include the Tyrer-Cuzick model version 8, and the Gail Model.

However the more recent short-term risk models that have emerged that use artificial intelligence to provide actionable information at point-of-care may be poised to finally move the needle in precision breast cancer risk assessment.

Automated short-term risk models provide actionable information in contrast to their lifetime risk counterparts which rely on long-term and less accurate outputs that do not inform immediate action in patient care.

Think of breast cancer screening as a funnel: 90% of women participating in breast screening have only a screening mammogram, and the remaining 10% go on to diagnostic mammography.

Efficient patient and process management are critical in determining the effectiveness of breast cancer screening and are impacted by a woman’s breast density, her breast cancer risk, and the clinical image quality of her mammogram. Optimizing patient and process management in screening mammography impacts the effectiveness of diagnostic mammography and can cost-effectively improve breast cancer screening service delivery quality and clinical outcomes, supporting value-based healthcare models.

Artificial intelligence continues to be one of the hottest topics in radiology, promising transformative solutions for breast cancer screening. However, making sense of how A.I. fits into your current breast screening workflows can feel like a complex undertaking. At Densitas® we have committed to help you navigate through the discourse on how A.I. can assist you and augment your mammography practice, providing actionable insights for improved operational efficiencies and better reporting workflows. In a time where COVID-19 has created a growing backlog of delayed screening mammography services, clinical care teams are experiencing burnout and are looking for workflow efficiencies to manage their increasing workload.