Image IQ: Screening Ultrasound for Dense Breasts

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.

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.

In a multicenter study of over 370 women who had surgery for ovarian cystic lesions without acute symptoms, researchers found that 42 percent of the resected lesions were deemed to have an O-RADS ultrasound risk score of 2, which has less than a one percent chance of malignancy.

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.

In a study looking at the impact of experience and case volume of breast screening radiologists, researchers found that reviewing more than 150 cases per week was necessary to achieve an 80 percent rate of true-positive assessments for malignant calcifications.

Mean artificial intelligence (AI) scoring for breasts developing cancer was double that of contralateral breasts at initial biennial screening and was 16 times higher at the third biennial screening, according to a study involving over 116,000 women with no prior history of breast cancer.