Nina Kottler, MD, MS on Adoption and Impact of AI in Radiology

Offering ergonomic controls and AI-enabled features, the remote-controlled Luminos Q.namix R system and the Luminos Q.namix T platform with tableside control reportedly facilitate workflow efficiencies for complex radiography and fluoroscopy examinations.

In the first of a multi-part podcast episode, Stamatia Destounis, MD, Emily Conant, MD and Habib Rahbar, MD, share their insights on the role of abbreviated breast MRI in breast screening.

The use of adjunctive bpMRI-based AI led to 10 percent and greater increases in lesion-level PPV for csPCa and PCa with a threshold of PI-RADS > 3.

In a second part of a new podcast episode on recently published research on projected radiation-induced cancers from computed tomography (CT) scans, Mahadevappa Mahesh, MS, Ph.D., and Joseph Cavallo, M.D., offer current perspectives on cardiac CT dosing, AI advances and the importance of teamwork in ensuring appropriate dosing for CT.

Noting a 7.4 percent incidence of motion artifacts on brain MRI scans for suspected stroke patients, the authors of a new study found that motion artifacts can reduce radiologist and AI accuracy for detecting hemorrhagic lesions.

In external validation findings from a 29-study meta-analysis, MRI-based AI had a pooled AUC of 85 percent for preoperative prediction for microvascular invasion in patients with hepatocellular carcinoma.