From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.).
Radiographics. 2023 Jul;43(7):e220178. doi: 10.1148/rg.220178.
Fatty liver disease has a high and increasing prevalence worldwide, is associated with adverse cardiovascular events and higher long-term medical costs, and may lead to liver-related morbidity and mortality. There is an urgent need for accurate, reproducible, accessible, and noninvasive techniques appropriate for detecting and quantifying liver fat in the general population and for monitoring treatment response in at-risk patients. CT may play a potential role in opportunistic screening, and MRI proton-density fat fraction provides high accuracy for liver fat quantification; however, these imaging modalities may not be suited for widespread screening and surveillance, given the high global prevalence. US, a safe and widely available modality, is well positioned as a screening and surveillance tool. Although well-established qualitative signs of liver fat perform well in moderate and severe steatosis, these signs are less reliable for grading mild steatosis and are likely unreliable for detecting subtle changes over time. New and emerging quantitative biomarkers of liver fat, such as those based on standardized measurements of attenuation, backscatter, and speed of sound, hold promise. Evolving techniques such as multiparametric modeling, radiofrequency envelope analysis, and artificial intelligence-based tools are also on the horizon. The authors discuss the societal impact of fatty liver disease, summarize the current state of liver fat quantification with CT and MRI, and describe past, currently available, and potential future US-based techniques for evaluating liver fat. For each US-based technique, they describe the concept, measurement method, advantages, and limitations. RSNA, 2023 Quiz questions for this article are available through the Online Learning Center.
全球范围内，脂肪肝疾病的患病率居高不下且呈上升趋势，与不良心血管事件和更高的长期医疗费用相关，还可能导致与肝脏相关的发病率和死亡率。因此，迫切需要准确、可重复、易于获取且非侵入性的技术，以用于在普通人群中检测和量化肝脏脂肪，并用于监测高危患者的治疗反应。CT 可能在机会性筛查中发挥潜在作用，磁共振质子密度脂肪分数（MRI-PDFF）为肝脏脂肪定量提供了高度准确性；然而，鉴于全球患病率较高，这些成像方式可能不适合广泛的筛查和监测。US 作为一种安全且广泛可用的方式，非常适合作为筛查和监测工具。虽然肝脏脂肪的既定定性征象在中重度脂肪变性中表现良好，但这些征象在分级轻度脂肪变性时的可靠性较低，并且可能无法可靠地检测随时间的细微变化。肝脏脂肪的新出现和新兴定量生物标志物，例如基于衰减、反向散射和声速标准化测量的标志物，具有广阔的应用前景。多参数建模、射频包络分析和基于人工智能的工具等新兴技术也即将出现。作者讨论了脂肪肝疾病的社会影响，总结了 CT 和 MRI 肝脏脂肪定量的现状，并描述了过去、目前可用的和潜在的未来基于 US 的肝脏脂肪评估技术。对于每种基于 US 的技术，作者均描述了其概念、测量方法、优点和局限性。RSNA，2023 本文的测验问题可通过在线学习中心获取。
