Technology

Advanced imaging with photon-counting CT and AI detection of subtle calcification may lead to a reevaluation of the power of zero with coronary artery calcium (CAC) scoring.

General radiologist assessment of mammograms with adjunctive AI led to a significant increase in cancer detection rate akin to that of breast imaging specialists, according to new research.

Catch up on the latest imaging research from the recent Society of Cardiovascular Computed Tomography (SCCT) conference.

In cases involving false negative suggestions from adjunctive AI for screening mammogram review, researchers found that unassisted radiologists had a 32 percent higher sensitivity rate than those who utilized AI.

Deep learning-based motion correction with the CLEAR Motion software reportedly bolsters cardiac imaging quality while the PIQE 1024 Deep Learning Reconstruction software offers equivalent SNR to photon-counting CT for high-resolution views of objects less than 0.5 mm.

The newly FDA-cleared PACS Viewer from CliniComp reportedly allows direct review and analysis of imaging within a patient’s chart.

In a recent interview, Nina Kottler, MD, offered her perspective on findings from a recent report on AI in health care, AI integration challenges and what the future holds with AI in radiology.

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

Emerging research demonstrates that those with total plaque volume > 750 mm3 have an 18.6 percent risk of MACE at four years in comparison to a 1.4 percent MACE risk for those with no plaque.

Catch up on the most-well viewed radiology content in June 2026.

Catch up on the most well-viewed video interviews from Diagnostic Imaging in June 2026.

In order to fully take advantage of the capabilities of AI, this author emphasizes key principles and a framework for converting isolated technology solutions into reliable components of radiology workflows and operations.

Catch up on a variety of FDA news in radiology from the past week.

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

The new functionalities for the AI-enabled Breast Suite software include automated identification of breast arterial calcifications and integration of prior mammograms.

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

The First Read software provides preliminary drafting of radiology reports based on AI assessment of chest X-rays.

The Oncology Virtual Expert AI software reportedly provides semi-automated segmentation maps of brain tumors based on standard brain MRI scans.

The newly launched HOPPR Presto Agent reporting platform can be integrated into existing radiology systems and AI models without the need for new software.

In a recent interview, Constance Lehman, MD, PhD, discussed newly published research demonstrating the dynamic capability of AI-based risk scores, drawn from screening mammograms, to facilitate risk-adaptive screening.

The VascularAssist Occlusion Triage software reportedly demonstrated over a 90 percent sensitivity for detecting peripheral artery disease (PAD) on CT in clinical performance testing.

For pancreatic cancers less than or equal to 20 mm, a deep learning model offered a nearly 45 percent higher sensitivity rate with non-contrast CT in comparison to unassisted radiologist interpretation.

While use of an AI software demonstrated significantly higher accuracy in evaluating BI-RADS 2 presentations and no significant difference with radiologists in BI-RADS 4 assessments of breast ultrasound in a sub-analysis, researchers noted the exclusion of galactoceles, fluid collections and skin lesions that are commonly found in pregnant and lactating women.

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

In a recent interview, Nina Kottler, MD, discussed the challenges with traditional radiology reporting, its impact on cognitive load and the recently launched AI-enabled platform Mosaic Reporting.