Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
Department of Radiology, Te Toka Tumai Auckland (Auckland District Health Board), Auckland, New Zealand.
Semin Musculoskelet Radiol. 2024 Oct;28(5):594-609. doi: 10.1055/s-0044-1788887. Epub 2024 Oct 15.
Body composition is now recognized to have a major impact on health and disease. Imaging enables its analysis in an objective and quantitative way through diverse techniques such as dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging, and ultrasonography. This review article first surveys the methodological aspects underpinning the use of these modalities to assess body composition, highlighting their strengths and limitations as well as the set of parameters that they measure and their clinical relevance. It then provides an update on the main applications of body composition imaging in current practice, with a focus on sarcopenia, obesity, lipodystrophies, cancer, and critical care. We conclude by considering the emerging role of artificial intelligence in the analysis of body composition, enabling the extraction of numerous metrics with the potential to refine prognostication and management across a number of pathologies, paving the way toward personalized medicine.
人体成分现在被认为对健康和疾病有重大影响。通过多种技术，如双能 X 射线吸收法、计算机断层扫描、磁共振成像和超声检查，影像学可以客观、定量地对其进行分析。本文首先综述了这些方法在评估人体成分方面的应用所依据的方法学方面，强调了它们的优缺点以及它们所测量的参数集及其临床意义。然后，本文介绍了人体成分成像在当前实践中的主要应用，重点是肌少症、肥胖、脂肪营养不良、癌症和重症监护。最后，我们考虑了人工智能在人体成分分析中的新兴作用，它可以提取大量指标，有可能改善多种疾病的预后和管理，为个性化医疗铺平道路。
