The use of an adjunctive machine learning model led to 17 and 21 percent improvements in the AUC and sensitivity rate, respectively, for PET/MRI in diagnosing extraprostatic tumor extension in patients with primary prostate cancer.

A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.

Does our pattern recognition expertise in imaging extend to our impressions of tells in the work of our colleagues?

Catch up on the top radiology content of the past week.

In a recent interview at the RSNA conference, Raj Chopra, MD shared his insights on the continued rise of cyberattacks, the impact of these attacks in radiology and keys to prevention and effectively responding to such events.

New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.

The authors of a new study found that deep learning assessment of single-phase CT scans provides comparable within-one stage accuracies to multiphase CT for detecting and staging chronic obstructive pulmonary disease (COPD).

For patients with suspected or known coronary artery disease (CAD) without percutaneous coronary intervention (PCI), researchers found that those with a normal CTA-derived quantitative flow ratio (CT-QFR) had a 22 percent higher MACE-free survival rate.

In an interview at the RSNA conference, Sundus Lateef, MD, discussed the rise of silicosis and associated CT findings in a recent study of engineered stone countertop workers.

In a new point-counterpoint discussion published in the American Journal of Roentgenology, researchers debate the merits and limitations of the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1.

In patients with PI-RADS 3 lesion assessments, the combination of AI and prostate-specific antigen density (PSAD) level achieved a 78 percent sensitivity and 93 percent negative predictive value for clinically significant prostate cancer (csPCa), according to research presented at the Radiological Society of North American (RSNA) conference.

In research involving over 2,200 women who had SPECT MPI exams, researchers found that those who had a high score with the COronary Risk Score in WOmen (CORSWO) model had a greater than fourfold higher risk of major adverse coronary events (MACE).

Do we get mired in the rut of generational grumbling, or do we reframe resentments into perspective of what we have overcome?

Catch up on the top radiology content of the past week.

Emerging research from the RSNA conference suggests that two-dimensional mammography would only detect 41 percent of detectable breast cancer.