Sullivan Daniel C, Obuchowski Nancy A, Kessler Larry G, Raunig David L, Gatsonis Constantine, Huang Erich P, Kondratovich Marina, McShane Lisa M, Reeves Anthony P, Barboriak Daniel P, Guimaraes Alexander R, Wahl Richard L
From the Department of Radiology, Duke University Medical Center, Box 2715, Durham, NC 27710 (D.C.S., D.P.B.); Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Public Health, University of Washington, Seattle, Wash (L.G.K.); Department of Informatics, ICON Medical, Washington, Pa (D.L.R.); Center for Statistical Sciences, Brown University, Providence, RI (C.G.); National Cancer Institute, Bethesda, Md (E.P.H., L.M.M.); Center for Devices and Radiological Health, U.S. Food and Drug Administration, White Oak, Md (M.K.); Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY (A.P.R.); Department of Radiology, Oregon Health & Science University, Portland, Ore (A.R.G.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (R.L.W.).
Radiology. 2015 Dec;277(3):813-25. doi: 10.1148/radiol.2015142202. Epub 2015 Aug 12.
Although investigators in the imaging community have been active in developing and evaluating quantitative imaging biomarkers (QIBs), the development and implementation of QIBs have been hampered by the inconsistent or incorrect use of terminology or methods for technical performance and statistical concepts. Technical performance is an assessment of how a test performs in reference objects or subjects under controlled conditions. In this article, some of the relevant statistical concepts are reviewed, methods that can be used for evaluating and comparing QIBs are described, and some of the technical performance issues related to imaging biomarkers are discussed. More consistent and correct use of terminology and study design principles will improve clinical research, advance regulatory science, and foster better care for patients who undergo imaging studies.
尽管成像领域的研究人员一直积极致力于开发和评估定量成像生物标志物(QIBs),但QIBs的开发和应用却因技术性能和统计概念的术语或方法使用不一致或不正确而受到阻碍。技术性能是对测试在受控条件下的参考对象或受试者中的表现的评估。在本文中,回顾了一些相关的统计概念,描述了可用于评估和比较QIBs的方法,并讨论了与成像生物标志物相关的一些技术性能问题。更一致和正确地使用术语和研究设计原则将改善临床研究,推动监管科学,并为接受成像研究的患者提供更好的护理。