关键词: 营养筛查, 营养不良, 肌少症, 影像组学

Abstract: Application of radiomics in perioperative nutritional assessment        SHENG Xian. The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325015, China
Abstract    The nutritional assessment during the perioperative period plays a crucial role in surgical management. A comprehensive evaluation method is essential to screen and identify patients who require additional nutritional intervention, thereby improving long-term prognosis. The existing perioperative nutritional assessment involves considering subjective feelings, objective laboratory tests, body composition indicators, and dietary survey results to diagnose malnutrition. However, this evaluation process is relatively complex and cumbersome. Radiomics is a technique that utilizes computer analysis of medical imaging data, encompassing both classical methods from traditional data processing, such as feature extraction from images and predictive modeling, as well as newer methods using deep learning for image recognition and processing in recent years. This allows for in-depth mining of a patient's body composition information, thereby achieving a more objective and comprehensive personalized nutritional assessment. Common radiomics techniques include image segmentation, feature extraction, and machine learning methods which can extract abundant information from medical images to support accurate nutrition assessment during the perioperative period. However, radiomics faces challenges such as data privacy and ethical issues, technical standardization, as well as data analysis challenges in perioperative nutrition assessment. Future research should focus on addressing these issues to promote the application of radiomics in perioperative nutrition management and provide better-personalized care and treatment plans for patients.

Key words: nutritional screening, malnutrition, sarcopenia, radiomics