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.
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The three Quality Improvement Report presentations evaluate the densitas® intelliMammo™ 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.