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 hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Stand-Alone AI Technology Reduces Radiologists’ Screening Mammography Workloads by 90%

By MedImaging International staff writers
Posted on 20 Dec 2021
Print article
Illustration
Illustration

The use of artificial intelligence (AI) as a stand-alone reader for digital mammography (DM) or digital breast tomosynthesis (DBT) breast screening could ease radiologists’ workload while maintaining quality, according to new research.

Researchers from the Hospital Universitario Reina Sofía (Cordova, Spain) conducted a study to retrospectively evaluate the stand-alone performance of an AI system as an independent reader of DM and DBT screening examinations. Consecutive screening-paired and independently read DM and DBT images were collected and an AI system computed a cancer risk score (range, 1–100) for the DM and DBT examinations independently. AI stand-alone performance was measured using the area under the receiver operating characteristic curve (AUC) and sensitivity and recall rate at different operating points selected to have non-inferior sensitivity compared with the human readings (non-inferiority margin, 5%). The recall rate of AI and the human readings were compared using a McNemar test.

A total of 15 999 DM and DBT examinations (113 breast cancers, including 98 screen-detected and 15 interval cancers) from 15 998 women were evaluated. AI achieved an AUC of 0.93 (95% CI: 0.89, 0.96) for DM and 0.94 (95% CI: 0.91, 0.97) for DBT. For DM, AI achieved non-inferior sensitivity as a single (58.4%; 66 of 113; 95% CI: 49.2, 67.1) or double (67.3%; 76 of 113; 95% CI: 58.2, 75.2) reader, with a reduction in recall rate (P < .001) of up to 2% (95% CI: −2.4, −1.6). For DBT, AI achieved non-inferior sensitivity as a single (77%; 87 of 113; 95% CI: 68.4, 83.8) or double (81.4%; 92 of 113; 95% CI: 73.3, 87.5) reader, but with a higher recall rate (P < .001) of up to 12.3% (95% CI: 11.7, 12.9).

The researchers concluded that AI could replace radiologists’ readings in breast screening, achieving a non-inferior sensitivity, with a lower recall rate for DM but a higher recall rate for DBM.

Related Links:
Hospital Universitario Reina Sofía 

40/80-Slice CT System
uCT 528
Ultra-Flat DR Detector
meX+1717SCC
New
Ultrasound Needle Guide
Ultra-Pro 3
New
Radiation Shielding
Oversize Thyroid Shield

Print article

Channels

MRI

view channel
Image: Comparison showing 3T and 7T scans for the same participant (Photo courtesy of P Simon Jones/University of Cambridge)

Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients

Approximately 360,000 individuals in the UK suffer from focal epilepsy, a condition in which seizures spread from one part of the brain. Around a third of these patients experience persistent seizures... Read more

Ultrasound

view channel
Image: Oloid-shaped magnetic endoscope (Photo courtesy of STORM Lab/University of Leeds)

Tiny Magnetic Robot Takes 3D Scans from Deep Within Body

Colorectal cancer ranks as one of the leading causes of cancer-related mortality worldwide. However, when detected early, it is highly treatable. Now, a new minimally invasive technique could significantly... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.