The authors of this study aimed to evaluate how artificial intelligence computer-aided detection (AI-CAD) differentiates lesions presenting as calcifications, subsequently comparing its performance to that of an experienced breast radiologist. The authors discovered that AI-CAD showed similar diagnostic performances to the radiologists regarding calcifications detected in mammography. Key points Among calcifications with same morphology or BI-RADS assessment, those with positive AI-CAD scores had significantly higher PPVs. AI-CAD showed similar diagnostic performance to an experienced radiologist in assessing lesions detected as calcifications only on mammography. Among malignant calcifications, calcifications with positive AI-CAD scores showed higher rates of invasive cancers than calcifications with negative scores (all p > 0.05). Article: AI-CAD for differentiating lesions presenting as calcifications only on mammography: outcome analysis incorporating the ACR BI-RADS descriptors for calcifications Authors: Jiyoung Yoon, Hye Sun Lee, Min Jung Kim, Vivian Youngjean Park, Eun-Kyung Kim & Jung Hyun Yoon

Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations
Deep‑learning reconstruction (DLR) shifts CT image formation from a hardware‑limited process to a data‑driven one. In our real‑world cohort of >10,000 body scans, we observed a

