Diagnostic Imaging’s Weekly Scan: April 19 — April 25

Welcome to Diagnostic Imaging’s Weekly Scan, which offers an opportunity to catch up on the most well-viewed radiology content of the past week.

In a recent interview with Diagnostic Imaging, Andrew Del Gaizo, MD, and Nicholas Galante, MD, shared their thoughts and perspectives on increasing imaging volume, the sunsetting of PowerScribe 360, AI hype and promise, and potential opportunities in radiology.

An emerging deep learning model demonstrated an 81.2 percent specificity rate and an 82.9 percent negative predictive value (NPV) for PI-RADS > 4 lesions on biparametric prostate MRI, according to a new study involving over 400 patients.

In another recent interview with Diagnostic Imaging, Sujith Kalathiveetil, MD, FACC, discussed the evolution of coronary computed tomography angiography (CCTA), AI-enabled tools and the potential for future innovations with CCTA.

AI software identified breast cancer missed by radiologists on one prior screening DBT exam in 26.8 percent of patients and on three prior screening DBT exams in 11 percent of patients, according to a study involving over 300 women that was presented at the Society of Breast Imaging (SBI) Symposium.

PlaqueSegNet, an emerging deep learning model for coronary plaque quantification based off CCTA exams, offered a greater than 90 percent intraclass correlation coefficient agreement with intravascular ultrasound (IVUS) and expert readers across four separate datasets, according to a study published in Radiology earlier this week.