"The present study validated the feasibility of using MRI-based radiomics to identify a disease prone to missed diagnosis and misdiagnosis," experts involved in the study said.

Post-treatment changes may mask some of the subtle, early signs of recurring breast cancer on traditional mammography, an Academic Radiology editorial explains.

Assessing more than 11,000 patients with lesions designated as BI-RADS 4, radiologists using digital breast tomosynthesis found no significant diagnostic advantages over standard 2D mammography.

Imaging features were also examined as predictive time to resolution factors, with cortical thickness of the nodes being of particular interest.

Providers screening women with dense breasts and benign breast disease should consider individualized mammogram protocols for these patients, authors of the study suggested.

Combining ensemble AI models with reads from breast radiologists of mixed experience levels can help health systems consistently diagnose malignant architectural distortion on mammography.

Researchers have developed a prediction model that takes into account both imaging (post-NAC breast MRI) and clinical-pathologic features when forecasting patients' overall survival.

Of the 51 plans, just 31% were consistent with the USPSTF recommendations pertaining to the starting age and frequency of screening women who are at average risk of developing breast cancer.