Image IQ: 9-year-old Male with Abdominal Pain

Emerging breast ultrasound research showed the use of computer-aided diagnosis (CAD), powered by deep learning, led to 24 percent and 36.9 percent improvements in accuracy and specificity, respectively, in the use of BI-RADS classifications by radiologists without breast ultrasound expertise.

In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.

Adjunctive use of an artificial intelligence (AI) software demonstrated nearly equivalent sensitivity and over 28 percent higher accuracy in comparison to radiologist assessment of breast ultrasound images for breast lesions, according to new research presented at the recent Society of Breast Imaging (SBI) conference.

Dr. Laurence Klotz discusses micro-ultrasound as a faster, less invasive, more cost-effective screening strategy compared to mpMRI in this podcast.

Lamenting a lack of control over imaging requests from referring clinicians, this author suggests that a more collaborative approach between referrers and radiologists may facilitate more efficient use of imaging.

The BD Prevue™ II Peripheral Vascular Access System reportedly offers real-time needle depth markers that may reduce multiple needlestick attempts and allow easier placement of intravenous (IV) access in high-risk patients.