ScreenPoint Medical presents Transpara® Breast AI to improve cancer detection and support single-reader screening on the ECR

Vienna (ots/PRNewswire) AI-powered screening delivers real-world clinical results in research studies presented at ECR

ScreenPoint Medical will present its industry-leading Transpara Breast AI at the European Congress of Radiology (ECR) 2024, taking place from February 28th to March 3rd, 2024 (Stand #AI-31 in Expo Hall X1). Transpara offers radiologists a “second pair of eyes” to detect cancer earlier and reduce recurrence 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 four talks and three posters presented at ECR 2024:

In the first randomized controlled trial of its kind, researchers analyzed cancer detection rates and the types of cancers detected across the MASAI study population. AI-assisted screening resulted in significant and substantial improvements compared to double reading without AI. These results can be viewed 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, 2 p.m.).

In another prospective clinical trial, researchers examined whether AI could safely reduce workload by Low risk human reading cases excluded and the remaining cases were read twice. The presentation is called: “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 a.m.). The results show that the AI-based categorization in which mammograms with low Eliminating risk from human evaluation will result in a significant reduction in breast cancer screening workload without compromising performance.

Other 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, 1. März, 8 Uhr).
  • „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, 3. März, 11.30 Uhr).

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 pleased that users and researchers continue to see the value of Transpara in improving the mammography screening process. It is important to note that these studies reflect the global consistency of Transpara’s performance. In fact, there are now retrospective, prospective and randomized controlled studies all showing that Transpara enables radiologists to effectively detect early-stage cancer while maintaining consistent recall rates. “Women shouldn’t have to compromise,” said Mark Koeniguer, CEO of ScreenPoint Medical.

Transpara is FDA approved and has European approval (CE Mark) for both abnormality detection and density assessment in 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 detected earlier with Transpara, while improving reading workflow.

About ScreenPoint Medical

ScreenPoint Medical translates cutting-edge machine learning research into technology that can be used by radiologists to workflow at screening, the decision making and the Risk assessment to improve breast cancer. Transpara is trusted by radiologists around the world as it was developed by machine learning and imaging analysis experts and updated with feedback from globally recognized breast imaging physicians. All evidence can be found at: screenpoint-medical.com

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Questions & Contact:

Chris K. Joseph,
510.435.4031,
chris@ckjcomm.com

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