Diagnostic Imaging's Weekly Scan: June 25-July 1

In sequential breast cancer screening with digital breast tomosynthesis (DBT), true positive examinations had more than double the AI case score of true negative examinations and the highest positive AI score changes from previous exams, according to new research.

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.

Employing baseline MRI and clinical data, an emerging deep learning model was 32 percent more likely to predict the progression of low-risk prostate cancer (PCa) to clinically significant prostate cancer (csPCa), according to new research.

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.

The appropriate use criteria (AUC) reflect updates to the 2013 AUC for amyloid PET and new criteria for tau PET in the diagnosis and monitoring of patients with mild cognitive impairment (MCI).

In patients with high-risk, hormone sensitive prostate cancer who had no evidence of metastasis on conventional imaging, PSMA PET revealed polymetastatic disease in 24 percent of patients and M1 disease staging in 46 percent of patients.