This study integrated the clinical data and radiomics signature generated by a support vector machine to establish a radiomics nomogram for prediction of induction chemotherapy response and survival in nasopharyngeal carcinoma patients. The results proved that multiparametric MRI-based radiomics could be helpful for personalized risk stratification in patients receiving induction chemotherapy. Key points MRI Radiomics can predict IC response and survival in non-endemic NPC. Radiomics signature in combination with clinical data showed excellent predictive performance. Radiomics signature could separate patients into two groups with different prognosis. Article: MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma Authors: Lina Zhao, Jie Gong, Yibin Xi, Man Xu, Chen Li, Xiaowei Kang, Yutian Yin, Wei Qin, Hong Yin, Mei Shi

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

