We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App


ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.
15 Nov 2021 - 18 Nov 2021

Mammography AI Could Sharply Reduce Radiology Workload

By MedImaging International staff writers
Posted on 12 Jul 2021
Print article
Image: Transpara AI can reduce mammography workload (Photo courtesy of ScreenPoint Medical)
Image: Transpara AI can reduce mammography workload (Photo courtesy of ScreenPoint Medical)
Using artificial intelligence (AI) in breast cancer screening could reduce the workload of radiologists by up to 70% without reducing cancer detection rates, according to a new study.

The study, by researchers at Maimonides Institute for Biomedical Research (IMIBIC; Córdoba, Spain) and ScreenPoint Medical (Nijmegen, the Netherlands), compared a simulated AI triaging strategy using ScreenPoint’s Transpara AI software with double or single reading by radiologists in a retrospective analysis of 15,987 digital breast tomosynthesis (DBT) and digital mammography (DM) images from the Córdoba Tomosynthesis Screening Trial.

The examinations included 98 screening-detected and 15 interval cancers. The results showed that in comparison with double reading of DBT images, AI with DBT would result in 72.5% less workload, non-inferior sensitivity, and a and 16.7% lower recall rate. Similar results were obtained for AI with DM; compared to the original double reading of DM images, AI with DM would result in 29.7% less workload, 25% higher sensitivity, and 27.1% lower recall rate. The study was published on May 4, 2021, in Radiology.

“DBT images can take twice as long for radiologists to read compared with DM. However, with AI, it may be possible to move from using digital mammograms to digital breast tomosynthesis,” said lead author radiologist José Luis Raya-Povedano, MD, of the IMIBIC Breast Cancer Unit. “The workflow of breast cancer screening programs could be improved, given the high workload and the high number of false-positive and false-negative assessments.”

Transpara is based on FusionAI, a combination of pathology, clinical imaging, X-ray physics, and deep learning (DL) techniques, designed to improve mammography reading accuracy, help interpretation of suspicious areas, increase confidence for normal and suspicious cases, and speed up reading of 2D and 3D mammograms.

Related Links:
Maimonides Institute for Biomedical Research
ScreenPoint Medical

Print article



view channel
Image: Mindray TE7 Max Ultrasound System (Photo courtesy of Mindray)

Mindray's New TE7 Max Ultrasound System Expands Possibilities for Point of Care

Mindray North America (Mahwah, NJ, USA) has launched its new TE7 Max ultrasound system that maximizes the potential of ultrasound in the Point of Care (POC) market. The TE7 Max has a 21.... Read more

Imaging IT

view channel

Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology

The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read more

Industry News

view channel

Intelerad Acquires Cloud Specialist Ambra Health to Form Global Enterprise Imaging Giant

Intelerad Medical Systems (Raleigh, NC, USA), a leading provider of medical image management solutions, has acquired Ambra Health (New York, NY, USA), maker of a leading cloud-based medical image management... Read more
Copyright © 2000-2021 Globetech Media. All rights reserved.