Diagnostic Imaging's Top 5 Articles of 2022

For women with intermediate risk and a personal history of breast cancer, an emerging AI system offered an 81 percent AUC for breast cancer detection, 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.

A predictive model for non-small cell lung cancer (NSCLC) recurrence, based on clinical parameters and CT findings, demonstrated an 85.2 percent AUC and 83.3 percent sensitivity rate, according to external validation testing in a new study.

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.

For those without low skeletal muscle mass on CT and myosteatosis, obese patients have a 23 percent lower risk of death than non-obese patients after undergoing curative resection for non-small cell lung cancer, according to newly published research.

For patients with newly diagnosed obstructive coronary artery disease (CAD), a multimodal machine learning model offered an 86 percent AUC for predicting MACE, which was 10 percent higher than CCTA alone and over 35 percent higher than the Framingham Risk Score.