Diagnostic Imaging's Weekly Scan: July 10-July 16

Multicenter research revealed that a combined model of clinical factors and ultrasound-based radiomics exhibited greater than a 23 percent higher per patient-level accuracy rate for identifying HER2 breast cancer than a clinical model.

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.

Researchers noted the combination of AI and bpMRI had an average AUC of 91 percent for csPCa detection in contrast to 78 percent for unassisted radiologist interpretation in a recent meta-analysis.

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 use of ivonescimab was correlated with a median 5.3-month improvement in progression-free survival (PFS) over pembrolizumab in patients with PD-L1 positive non-small cell lung cancer, according to CT and MRI findings from a phase 3 randomized multicenter trial.

While high-resolution ultrasound offered nearly 10 percent higher specificity in the detection of upper extremity peripheral neuropathy, magnetic resonance neurography provided a nearly 23 percent higher sensitivity rate in a recent study.