Digital stereotaxy adds to GE digital mammo

Through AI recognition of subtle patterns in breast tissue on screening mammograms, the Clairity Breast software reportedly provides validated risk scoring for predicting one’s five-year risk of breast cancer.

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.

For women with dense breasts and negative mammograms, contrast-enhanced mammography and abbreviated MRI provided respective cancer detection rates of 19.2 per 1000 exams and 17.4 per 1000 exams, 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.

Emerging research suggests that radiomic breast texture features extracted from full-field digital mammography may bolster prognostic assessments of invasive breast cancer risk beyond traditional risk factors.

The use of AI software for digital breast tomosynthesis (DBT) facilitated a higher cancer detection rate and over double the PPV for exams with abnormal interpretation, according to a newly published study.