ScreenPoint Medical Showcases Transpara® Breast AI Designed to Improve Cancer Detection and Support Single Reader Screening at ECR
AI-Supported Screening Delivering Real-World Clinical Results in Research Studies being Presented at ECR
VIENNA, Feb. 21, 2024 /PRNewswire/ -- ScreenPoint Medical is showcasing its industry leading Transpara Breast AI at the 2024 European Congress of Radiology (ECR) meeting, February 28-March 3, 2024 (Booth #AI-31 in Expo Hall X1). Transpara provides radiologists with a 'second pair' of eyes to help detect cancers earlier and reduce recall rates.
Transpara continues to deliver proven clinical and workflow benefits in mammography screening in global practice and clinical research. These benefits are the subject of 4 presentations and 3 posters to be presented at ECR 2024:
In the first-of-its-kind randomized controlled trial, researchers analyzed cancer-detection rates and the types of detected cancers in the full MASAI-trial study population. AI-supported screening resulted in significant and substantial improvements compared to double reading without AI. These results can be seen at: "Cancer detection in relation to type and stage in the randomized Mammography Screening with Artificial Intelligence trial (MASAI)" (RPS-2002, ACV Research Stage 2, March 2, 2pm).
In another prospective clinical trial, researchers evaluated AI for safe workload reduction by excluding low risk cases for human reading and applying double reading to the rest. This presentation can be seen is: "Is it worth reading low-risk breast cancer screening mammograms as determined by an artificial intelligence (AI) system? A prospective, population-based study for DM and DBT (AITIC trial)" (RPS-1202, ACV Research Stage 1, March 1, 8 am). Results demonstrated that AI-based triaging, excluding low risk mammograms from human reading, leads to a substantial reduction in reading workload in breast cancer screening without negatively affecting performance.
Additional presentations include:
- "How much has AI improved over the last five years? A benchmark evaluation of different versions of an AI mammography interpretation system" (RPS-1202, ACV Research Stage 1, March 1, 8 am).
- "Are AI-detected interval cancers actionable for recall in a real screening setting? An informed review of 120 interval cancer cases with high AI scores in breast screen Norway (RPS-2405, ACV Research Stage 1, March 3, 11.30am).
E-posters include:
- "Enhancing Mammography Screening Sensitivity with AI-Assistance: Evidence from a Vietnamese Study Cohort"
- "AI breast cancer detection as decision-support tool in mammography: what is the added value in a clinical population?"
- "Using AI to automatically compute volumetric breast density and BIRADS density grade in mammography and breast tomosynthesis images."
"We are glad that users and researchers continue to see value from Transpara in improving the mammography screening process. It's important to note that these studies reflect global consistency in Transpara's performance. In fact, we now have retrospective, prospective and randomized controlled trials all showing that Transpara provides radiologists with the ability to effectively detect cancer early while keeping recall rates consistent. Women should not have to compromise," said Mark Koeniguer, ScreenPoint Medical CEO.
Transpara is FDA cleared and has European regulatory approval (CE Mark) for both abnormality detection and density assessment for use with 2D and 3D mammography from multiple manufacturers. Used by hundreds of leading centers in more than 30 countries, Transpara is designed to work concurrently with radiologists. Research shows that up to 45% of interval cancers can be found earlier using Transpara, while helping to improve reading workflow.
About ScreenPoint Medical
ScreenPoint Medical translates cutting edge machine learning research into technology accessible by radiologists to improve screening workflow, decision confidence and breast cancer risk assessment. Transpara is trusted by radiologists globally because it has been developed by experts in machine learning and image analysis and updated with user feedback from world-renowned breast imagers. See all the proof at: screenpoint-medical.com
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