See the Real-World Impact of AI in Radiology

In a recent interview, Phillip Koo, MD, discussed emerging trends with AI, theranostics and empowered patients, and how these developments may lead to challenges and potential opportunities for radiologists and nuclear medicine physicians.

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

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.

While a new article raises provocative questions about the capability of photon-counting CT (PCCT) to perhaps replace diagnostic ICA, the real revolution with this modality is going beyond stenosis measurement to a renewed focus on the disease of atherosclerosis.

Catch up on the latest imaging research presented at the recent American Society for Radiation Oncology (ASTRO) Annual Meeting.

Tightness of the high-convexity sulci (THC) on brain MRI was associated with nearly threefold higher odds of cognitive decline over five to seven years of follow-up, according to a new prospective study involving over 2,100 community-dwelling senior citizens.

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.