Breast Imaging

Example: SoftVue image stacks of sound speed, as shown for cases ranging across the four Breast Imaging Reporting and Data System (BI-RADS) breast density categories ((a), fatty; (b), scattered; (c), heterogeneously dense; (d), extremely dense). Note the quantitative scale indicating that absolute measurements are obtained. Image courtesy of MDPI

Christopher Comstock, M.D., (Memorial Sloan Kettering Cancer Center) is the lead author of a paper in JAMA that reports that abbreviated breast MRI detected significantly more (almost 2 and a half times as many) breast cancers than digital breast tomosynthesis (3-D mammography) in average-risk women with dense breasts. Photo courtesy of Memorial Sloan Kettering Cancer Center

Mammograms of a 49-year-old woman with invasive lobular carcinoma on the right-side breast. A small mass with micro-calcifications on the right-side breast was detected correctly by AI with an abnormality score of 96%. This case was recalled by 7 out of 14 radiologists (4 breast radiologists and 3 general radiologists) initially (without AI) and all 14 radiologists recalled this case correctly with the assistance of AI.

A 50-y-old postmenopausal woman with fibroadenoma (arrows) in left breast. (A) Unenhanced fat-saturated T1-weighted MRI shows extreme amount of FGT (ACR d). (B) Moderate BPE is seen on dynamic contrast-enhanced MRI at 90 s. (C) Mean ADC of breast parenchyma of contralateral breast on diffusion-weighted imaging with ADC mapping is 1.5 × 10?3 mm2/s. (D) On 18F-FDG PET/CT, lesion is not 18F-FDG-avid, and BPU of normal breast parenchyma is relatively high, with SUVmax of 3.2. Photo courtesy of K Pinker, et al., Medical University of Vienna, Vienna, Austria