Halifax, N.S., Oct 28, 2021 - Densitas® Inc., a global provider of A.I. technologies for digital mammography and breast screening, signed an agreement with RAD-AID International to deploy densitas® intellMammo™ A.I. software platform at Georgetown Public Hospital (GPHC) in Guyana.
The age-adjusted breast cancer death rate in Guyana for 2018 was 24.36 per 100,000 women, compared to 17.49 in the United States. To address this disparity, Guyana launched its first public sector breast screening program in 2019 at GPHC with assistance from RAD-AID International. Mammography exams in the program are performed using a digital mammography unit at GPHC by one lead radiologic technologist who has been trained by RAD-AID. RAD-AID is further supporting the training of other breast imaging technologists in Guyana to scale up the program’s impact in the public sector. Radiology attendings and residents at GPHC are receiving daily PACS-based interpretative support and education by RAD-AID’s breast imaging volunteers. RAD-AID has also implemented breast health outreach training curriculum for nurses, physicians, technologists and patient-navigators to help women engage these new vital services.
In partnership with RAD-AID International and GPHC, Densitas® has deployed intellMammo™ as part of a collaborative initiative to support breast cancer screening effectiveness and efficiency. The initiative aims to improve early detection by supporting training and education for effective and sustainable breast screening practices.
“In an environment with limited radiological resources, effective patient and process management improves precision breast health through A.I. driven clinical decision support” says Mo Abdolell, CEO of Densitas®. “When integrated into healthcare systems, especially in under-resourced regions, A.I. can level the playing field by providing sustainable and scalable solutions at a population level that can reduce healthcare disparities and support better quality care.
Densitas®’ novel solution for technologist training identifies positioning errors and integrates training materials for easy access while the patient is still in the exam room. The deployment will empower technologists with mammography-specific workflows and advanced analytics for comprehensive and continuous quality assurance processes to improve efficiency and performance. This has the potential to significantly impact quality of care, particularly in understaffed and/or under-resourced regions.
“We thank Densitas® for collaborating with us at RAD-AID to help low-resource hospitals safely and effectively test, engage, and adopt A.I.,” says Daniel Mollura, President and CEO of RAD-AID International. “In understaffed regions where skilled radiologic technologists, breast-health nurses, and radiologists are scarce, RAD-AID’s collaboration with Densitas® helps hospitals to increase the quality, safety, and efficiency of medical imaging in highly needed breast cancer screening programs.”
About RAD-AID International
RAD-AID is a charitable nonprofit global health organization, founded in 2008, serving over 85 resource-poor hospital partners in 38 low and middle-income countries (LMICs). RAD-AID has a diverse interdisciplinary composition of over 14,000 volunteer radiology professionals, including radiologists, nurses, technologists, physicists, engineers, and information technology specialists. Through outreach, radiology education, and equipment donations for medical imaging, RAD-AID advances radiology to support health services.
Visit RAD-AID.org to learn more.
Densitas® is a global leader in artificial intelligence solutions for breast cancer screening, focused on quality, safety, efficiency, and precision breast health. Our products equip mammography facilities with solutions for improving mammography quality, operational efficiencies, clinical care team burnout, compliance with MQSA EQUIP and breast density inform legislation, patient-specific rapid risk assessment, and tailored radiological technologist training protocols. Densitas® solutions align with value-based care delivery models by providing standardized metrics and quantitative performance indicators delivered through a continuous quality assurance platform powered by advanced A.I. analytics to cost-effectively manage the care delivery.