The Reading Room Podcast: Emerging Concepts in Breast Cancer Screening and Health Equity Implications, Part 1

Employing advanced deep learning convolutional neural networks, ProFound Detection Version 4.0 reportedly offers a 50 percent improvement in detecting cancer in dense breasts in comparison to the previous version of the software.

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 breast-enhanced masses, Kaiser scoring (KS) demonstrated a 20 percent higher AUC than BI-RADS classification for contrast-enhanced mammography (CEM) and was comparable to KS for breast MRI.

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.

Therapixel’s MammoScreen suite has received 510(k) FDA clearances for a breast density assessment feature and updated software that includes automated pre-reporting, which reportedly expedites reporting of mammography findings.

The combination of FDA-cleared AI software for mammography triage with a medical grade edge AI platform may allow the embedding of enhanced AI detection capability within existing mammography devices.