HALIFAX, NS, Nov. 9, 2022 /PRNewswire/ -- Densitas® Inc., a global provider of A.I. solutions for digital mammography and breast screening, announced that three quality improvement studies will be presented at the Radiological Society of North America (RSNA) 2022 Annual Scientific Meeting in Chicago.
In breast cancer screening, diagnostic confidence and breast cancer detection are predicated on having high quality images. Prior audits have shown that as many as 50% of mammograms do not meet image quality standards, 80% of which are due to poor positioning.
The three Quality Improvement Report presentations evaluate the densitas® intelliMammo(TM) A.I. tool for mammography quality improvement.
Information on the abstracts is as follows:
Can A.I. Support Mammography Image Quality Improvement? Primary Author: Georgia Spear, MD Date/Time: Tuesday, November 29, 2022/ 9:00am - 9:30am (Central) Location: Learning Center - QI DPS
Evidence-based assessment of quality improvement in positioning requires benchmarking of population-level error rates against which quality improvement initiatives can be evaluated. Non-subjective and standardized quality assessment is foundational to benchmarking. As a first step towards establishing population-based benchmarks of mammography positioning error rates at NorthShore University HealthSystem, this study seeks to validate the ability of an A.I. tool that generates standardized positioning quality assessments to capture the expected associations between positioning errors and varying patient and acquisition parameters. The results of the study show that breast density, breast volume, breast area, breast thickness, and compression pressure were associated with numerous positioning errors.
Investigating the Feasibility of Using A.I. For Population-Level Mammography Image Quality Improvement Initiatives at Leeds Teaching Hospitals NHS Trust Primary Author: Nisha Sharma, MBChD, FRCR Date/Time: Wednesday, November 30, 2022/ 12:45pm - 1:15pm (Central) Location: Learning Center - QI DPS
The study investigates the current state of mammography image quality in breast imaging services at Leeds Teaching Hospitals NHS Trust and presents results on the reliability and reproducibility of A.I.-generated, population-based error rates and agreement between radiographers and the A.I. tool. The results of the study show that agreement between radiographers and the A.I. tool was excellent to nearly perfect, and A.I.-generated positioning error rates were consistent with reported error rates in the literature.
Driving mammography Image Quality Improvement Using A.I. in Guyana During the COVID-19 Pandemic Primary Author: Mohamed Abdolell, MSc Date/Time: Sunday, November 27, 2022/ 12:15 pm - 12:45 pm (Central) Location: Learning Center - QI DPS
This study evaluates the impact of the adoption of an A.I. tool on mammography image quality in Georgetown General Hospital, Guyana, a radiologically underserved low- and middle-income country. The results of the study show that after adoption of the A.I. tool, positioning error rates decreased substantially and MIT-radiologist communications improved to guide effective remote mammography positioning training.
Densitas® will demonstrate intelliMammo(TM) at the upcoming Radiological Society of North America (RSNA) annual meeting, November 27-30, 2022 (Booth #2605, South Hall Level 3).
Densitas® is a global leader in artificial intelligence solutions for breast cancer screening, focused on quality, safety, efficiency, and precision breast health. Densitas® designs intuitive solutions that boost the ability of hospitals and imaging centers that perform mammography to improve efficiencies, meet FDA/ACR compliance requirements, and support early breast cancer detection and treatment. For more information, visit www.densitashealth.com.
Media Contact: Densitas®, Jessie Allen, firstname.lastname@example.org, 902-292-7159