AI predicts malignancy on breast ultrasound

An AI model can accurately predict malignancy on breast ultrasound based on BI-RADS assessment, according to research published December 11 in Academic Radiology.  A team led by Nilgun Guldogan, MD, from Acibadem Altunizade Hospital in Istanbul, Turkey, found that an AI method showed comparable performance to that of radiologists and can help avoid unnecessary biopsies and follow-up exams. “By considering AI-assigned BI-RADS 2 as safe, we could potentially avoid 11% of benign lesion biopsies and 46.2% of follow-ups,” the Guldogan team wrote. Previous studies have demonstrated how AI can be applied to breast ultrasound. These studies have shown how AI aids in image interpretation, reduce false-positive cases, and potentially help decrease the workload of radiologists. Guldogan and colleagues evaluated the performance of a commercially available AI system (Koios DS Study Tool, version 2.3.0, Koios Medical) for BI-RADS category assessment in breast masses detected on breast ultrasound. The researchers included data from 715 breast masses detected in 530 women. Of the total masses included, 134 were malignant while 581 were benign. In their multicenter study, the researchers included three breast imaging centers from the same institution and nine breast radiologists. One radiologist performed an ultrasound exam, obtaining two orthogonal views of each detected lesion. From there, a second radiologist retrospectively reviewed the images, being blinded to the patient’s cl...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Subspecialties Womens Imaging Breast Breast Imaging Source Type: news