Diagnostic Imaging's Weekly Scan: September 15 — September 21

In a multicenter study involving over 1,000 patients, a deep learning software offered comparable sensitivity and specificity for Gleason grade group > 2 tumors in comparison to radiologist interpretation.

In the third episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss the challenges of expanded breast cancer screening amid a backdrop of radiologist shortages and ever-increasing volume on radiology worklists.

In patients who had at least four cycles of 177Lu-PSMA-I&T for mCRPC, new research shows that a 10 percent or greater decrease in total kidney volume on CT at six months has a 90 percent AUC for predicting estimated glomerular filtration rates (eGFRs) of 30 percent or greater at one year.

In the second episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss recent studies published by the Journal of the American Medical Association (JAMA) that suggested moving to more of a risk-adapted model for mammography screening.

In a recent literature review, researchers offered insights on current considerations with prostate MRI and discussed keys to effective use of the modality in screening for prostate cancer.

Researchers found that the use of seven-minute threefold parallel imaging-accelerated deep learning 3T MRI had 89 percent sensitivity for supraspinatus-infraspinatus tendon tears and 93 percent sensitivity for superior labral tears.