Aidoc and Transpara by Screenpoint: What You Need to Know – Healthcare AI

Breast most cancers is the second commonest most cancers in girls within the U.S. (pores and skin cancers are first), accounting for round 30% of all new feminine cancers yearly.¹ And 2025 will probably be no exception. The American Most cancers Society estimates practically 317,000 new circumstances of invasive breast most cancers and about 59,000 new circumstances of ductal carcinoma in situ (DCIS), with greater than 42,000 estimated deaths.¹

So, how are these cancers detected? Nearly all of breast most cancers within the U.S. is recognized following an irregular screening. 

Traditionally, mammography concerned two, 2D views of every breast. Whereas mammography continues to be a trusted technique for each screening and diagnostic functions in detecting breast malignancies, tomosynthesis is now the dominant mannequin for each screening and diagnostic exams. With tomosynthesis, a number of angles are considered across the breast to assist see round dense breast tissue, making it extra time-consuming, but simpler, than conventional 2D mammography. 

As with all imaging assessments, some malignancies will not be detected, even by skilled readers. And a few benign findings could also be mistaken for malignancies, resulting in pointless further assessments and stress for sufferers. 

That’s why Aidoc has partnered with ScreenPoint Medical to supply Transpara for breast imaging options, offering a transformative strategy to AI breast most cancers detection and analysis.

About Aidoc and Transpara by Screenpoint

Transpara is absolutely built-in into present radiology workflows by Aidoc’s aiOS™ platform and desktop utility, enabling superior orchestration methods and offering a unified interface for all AI outcomes. This breast AI helps screening and diagnostic evaluations for 2D mammograms and tomosynthesis (also called 3D mammograms). 

Transpara: Scientific Proof

Transpara’s efficacy has been proven in a wide range of analysis research, from small pattern dimension research to one of many largest high-rigor research carried out on AI. 

• Transpara is uniquely studied.
  Transpara is the primary and solely breast AI to be studied in a randomized managed trial.³
• With Transpara, 29% extra cancers have been discovered.
  Within the Mammography Screening with Synthetic Intelligence (MASAI) trial, 105,934 girls have been randomly assigned to the intervention or management group. Nineteen girls have been excluded from the evaluation. They discovered that with Transpara, 29% extra cancers have been discovered.³
• Substantial time financial savings reported with Transpara.
  In a U.S. examine utilizing tomosynthesis, readers reported substantial time financial savings — notably on low threat circumstances.⁴ And in one other examine, Transpara carried out persistently no matter dense breast tissue — the tissue which makes it hardest for radiologists to learn.⁵

This AI-assisted breast most cancers screening software is changing into an ordinary of care with increased charges of most cancers detection, sooner and extra environment friendly reading¹²³⁴⁵ in addition to the peace of thoughts that comes with assured readings, no matter tissue density.

Transpara: Capabilities and Screening Suggestions

Transpara is FDA cleared for detection, and when a lesion is recognized, it discreetly notifies the studying radiologist by the workflow-enhanced utility. For circumstances with threat at or above typical inhabitants threat, Transpara will mark as much as two areas of concern per breast and assign an general examination rating based mostly on the very best space of concern. 

Transpara identifies soft-tissue lesions and calcifications, assigning a rating to each areas and the examination as a complete representing the chance of malignancies.* Transpara additionally gives an general examination rating when nothing is detected. The low class rating is necessary in ruling out low threat exams, and has been proven to avoid wasting roughly 26% of radiologist time when studying tomosynthesis research.²

Breast most cancers screening is advisable for girls aged 40-74 with common threat, in keeping with the US Preventative Companies Activity Pressure (USPSTF) suggestions for 2024. Whereas the USPSTF recommends biennial screening, many insurance coverage acknowledge the advantages of early detection and supply annual screening protection.

Powering a Unified Healthcare AI Expertise
Aidoc’s partnership with ScreenPoint underscores a dedication to collaboration that ensures healthcare organizations can entry probably the most superior AI-driven options from a single, unified platform. 

With 18 FDA-cleared algorithms and quite a few strategic partnerships with main builders, Aidoc’s vendor-neutral aiOS™ allows seamless integration of each Aidoc and third-party algorithms — delivering a coordinated, end-to-end AI ecosystem. By unifying know-how throughout the enterprise, 

Concerned about being a part of the way forward for radiology?
Learn how Aidoc and Screenpoint might help.

*Transpara isn’t designed to detect abnormalities on artificial, stereostatic, spot compressed or different diagnostic/non-standard views. It’s additionally not designed to course of views that include implants, a pacemaker or inside breast markers.

Citations

1. American Most cancers Society. https://www.most cancers.org/most cancers/varieties/breast-cancer/about/how-common-is-breast-cancer.html 
2. van Winkel, S.L., Rodríguez-Ruiz, A., Appelman, L. et al. Influence of synthetic intelligence help on accuracy and studying time in breast tomosynthesis picture interpretation: a multi-reader multi-case examine. Eur Radiol 31, 8682–8691 (2021).
3. Hernstrom, V., Josefsson, V., Sartor, H., Schmidt, D., Larsson, A., Hofvid, S., et al. (2025). Screening efficiency and traits of breast most cancers detected within the Mammography Screening with Synthetic Intelligence trial (MASAI): a randomised, managed, parallel-group, non-inferiority, single-blinded, screening accuracy examine. The Lancet Digital Well being  https://www.thelancet.com/journals/landig/article/PIIS2589-7500(24)00267-X/fulltext 
4. van Winkel, S.L., Rodríguez-Ruiz, A., Appelman, L. et al. Influence of synthetic intelligence help on accuracy and studying time in breast tomosynthesis picture interpretation: a multi-reader multi-case examine. Eur Radiol 31, 8682–8691 (2021). https://doi.org/10.1007/s00330-021-07992-w 
5. Koch, H.W., Larsen, M., Bartsch, H. et al. Synthetic intelligence in BreastScreen Norway: a retrospective evaluation of a cancer-enriched pattern together with 1254 breast most cancers circumstances. Eur Radiol 33, 3735–3743 (2023).