In this study, the feasibility and accuracy of PET-CT-based radiomics in preoperative prediction of clinical and pathological stages for esophageal cancer (EC) patients was investigated using a sample of 100 EC patients. The authors observed accurate prediction ability with combined PET and CT radiomics in the prediction of T stage, lymph node metastasis (LNM), and pstage, showing that PET-CT-based radiomics is a promising tool to improve the diagnosis and management of patients with EC. Key points: PET-CT radiomics achieved the best performance for Node and pathological stage prediction. CT radiomics achieved the best AUC for T stage prediction. PET-CT radiomics is feasible and promising to stratify stages for EC preoperatively. Article: Preoperative prediction of clinical and pathological stages for patients with esophageal cancer using PET/CT radiomics Authors: Xiyao Lei, Zhuo Cao, Yibo Wu, Jie Lin, Zhenhua Zhang, Juebin Jin, Yao Ai, Ji Zhang, Dexi Du, Zhifeng Tian, Congying Xie, Weiwei Yin & Xiance Jin
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
28. April 2025
