Technology

Use of the mammography AI software had a nearly equivalent false positive rate as unassisted radiologist interpretation and resulted in a 44 percent reduction in screen reading workload, according to findings from a randomized controlled trial involving over 105,000 women.

For women with intermediate risk and a personal history of breast cancer, an emerging AI system offered an 81 percent AUC for breast cancer detection, according to new research.

The artificial intelligence (AI)-enabled software Lumina 3D reportedly provides reconstructions of computed tomography angiography (CTA) images of the head and neck in minutes.

Catch up on the top radiology content of the past week.

Catch up on the most well-viewed video interviews from Diagnostic Imaging in January 2025.

Catch up on the most-well viewed radiology content in January 2025.

For patients with newly diagnosed obstructive coronary artery disease (CAD), a multimodal machine learning model offered an 86 percent AUC for predicting MACE, which was 10 percent higher than CCTA alone and over 35 percent higher than the Framingham Risk Score.

Designed for advanced OB-GYN applications, the Samsung Z20 ultrasound platform reportedly provides a combination of artificial intelligence (AI) tools and enhanced ergonomics.

An array of AI-powered features and automated tools may lead to improved workflow and image quality with the Voluson Expert 22, 20 and 18 ultrasound systems.

Catch up on the top AI-related news and research in radiology over the past month.

Catch up on the top radiology content of the past week.

The latest ultrasound software update from Clarius includes new artificial intelligence (AI) capabilities, coding assistance and a variety of advances tailored to different fields of medicine.

Emerging research suggests that a deep learning model may offer 92 percent sensitivity in lung tumor detection on CT scans and up to a 59 percent reduction in tumor segmentation time.

Catch up on the top radiology content of the past week.

In sequential breast cancer screening with digital breast tomosynthesis (DBT), true positive examinations had more than double the AI case score of true negative examinations and the highest positive AI score changes from previous exams, according to new research.

Catch up on the top radiology content of the past week.

The IQ-UIP AI software may bolster computed tomography diagnosis of usual interstitial pneumonia (UIP), which is reportedly misdiagnosed in over 50 percent of cases.

In a study of over 463,000 women who had screening mammography exams, adjunctive AI led to a 17.6 percent higher detection rate for breast cancer and a three percent increase in positive predictive value for recalls.

In a recent interview, Arlene Sussman, M.D., discussed her experience in leading vRad’s teleradiology breast imaging service, how to foster personalized care in breast cancer screening, utilizing AI to help mitigate daunting worklists and improving access to subspecialty care.

Survey results revealed that 71 percent of clinicians preferred adjunctive AI in facilitating triage of brain MRI scans and 58 percent were comfortable utilizing AI triage without input from radiologists.

Catch up on the top radiology content of the past week.

Adjunctive AI offered greater than seven percent increases in sensitivity, specificity, and accuracy for ultrasound detection of ovarian cancer in comparison to unassisted clinicians who lacked ultrasound expertise, according to findings from new international multicenter research.

Touching on a variety of topics in radiology, here are the top five most well-viewed content from Diagnostic Imaging in 2024.

Catch up on the most viewed content on AI in radiology from 2024.

Catch up on the most well-read computed tomography (CT) articles from 2024.

Catch up on the most-well viewed radiology content in December 2024.

Catch up on the top AI-related news and research in radiology over the past month.

Catch up on the most well-read ultrasound content from 2024.

Catch up on the most well-read mammography articles from 2024.

Convolutional neural network-enabled segmentation of brain MRI offered a 25.7 percent higher specificity than a radiomic model for differentiating radionecrosis and metastatic progression in patients treated with stereotactic radiosurgery for brain metastases.