Technology

The future of AI in radiology lies in its potential capability to forge connections and enhance efficiencies for enterprise-wide workflows.

Assessing breast MRI scans, pathology and clinical data, the AI-powered TumorSight Risk software reportedly provides five- and 10-year risk for breast cancer recurrence for women with HR+, HER2-negative stage I-IIIA breast cancer.

An AI model for prostate MRI offered an 89 percent AUC for prostate cancer detection in external validation testing, according to a newly published international multicenter study.

In the latest episode of her Breast Imaging in Focus series, Manisha Bahl, MD, MPH, FSBI, discusses new research comparing mammography-based AI models for breast cancer detection and short-term risk prediction.

The use of adjunctive CT bone reading software in women with breast cancer detected between 8 to 22 percent more metastatic lesions for reviewing radiologists and reduced CT interpretation time by 50 percent or more, according to a new study.

How will generative AI software be evaluated by the FDA in the future? What’s next for point-of-care ultrasound? What steps have been successful in facilitating adoption of AI applications across enterprise systems? Leaders in radiology and health care will be discussing these topics and more at the upcoming HLTH USA conference.

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

The cloud-based NextMR platform reportedly provides automated 3D bone images of conventional spine MRI images in less than 60 seconds.

The AI-powered SwiftSight Body Composition software reportedly provides automated quantification of muscle and adipose tissue after a brief MRI scan.

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

In a recent interview with Diagnostic Imaging, Joseph Cavallo, MD, MBA, offered insights on post-deployment monitoring with AI, the potential for improved workflow efficiency and the ongoing challenge of balancing essential clinical skills and AI literacy in the training of radiology residents and fellows.

Does fractional flow reserve (FFR) or quantitative plaque burden from CCTA provide greater prognostic insight into coronary disease?

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

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

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.

In a recent interview, Shadpour Demehri, MD, discussed new research examining connections between deep learning assessment of bone mineral density on chest CT, brain MRI data and the potential for enhanced risk stratification in patients with diabetes.

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

A deep learning model developed for predicting BI-RADS assessments from dynamic contrast-enhanced (DCE) breast MRI had over a 14 percent lower AUC than radiologist evaluation in external validation testing.

The CARE Chest X-Ray (CXR) Triage software reportedly bolsters consistent flagging of suspicious chest X-rays for lung collapse and pneumomediastinum across reviewing readers of different experience levels.

In a study involving over 700 participants who had chest CT and brain MRI, those with diabetes and lower vertebral bone mineral density (vBMD) had a nearly five percent faster total accumulation of white matter hyperintensity (WMH) in comparison to those without diabetes.

Newly cleared findings for the adjunctive AI platform a2z-Abdo-Triage include acute appendicitis, renal traumatic injury, ureteral stone and retroperitoneal hematoma.

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.

Reportedly one of the first FDA-cleared chest X-ray AI software platforms derived from a foundation model, the Chest Xray software facilitates detection and localization of lung nodules, pneumothorax, mediastinal abnormalities and other thoracic abnormalities.