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放射学研究统计学

Statistics for Radiology Research.

作者信息

Obuchowski Nancy A, Subhas Naveen, Polster Joshua

机构信息

Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio.

Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic Foundation, Cleveland, Ohio.

出版信息

Semin Musculoskelet Radiol. 2017 Feb;21(1):23-31. doi: 10.1055/s-0036-1597252. Epub 2017 Mar 2.

Abstract

Biostatistics is an essential component in most original research studies in imaging. In this article we discuss five key statistical concepts for study design and analyses in modern imaging research: statistical hypothesis testing, particularly focusing on noninferiority studies; imaging outcomes especially when there is no reference standard; dealing with the multiplicity problem without spending all your study power; relevance of confidence intervals in reporting and interpreting study results; and finally tools for assessing quantitative imaging biomarkers. These concepts are presented first as examples of conversations between investigator and biostatistician, and then more detailed discussions of the statistical concepts follow. Three skeletal radiology examples are used to illustrate the concepts.

摘要

生物统计学是大多数影像学原创研究中的重要组成部分。在本文中,我们讨论现代影像学研究中用于研究设计和分析的五个关键统计概念:统计假设检验,尤其侧重于非劣效性研究;成像结果,特别是在没有参考标准的情况下;在不消耗所有研究效能的情况下处理多重性问题;置信区间在报告和解释研究结果中的相关性;以及最后用于评估定量成像生物标志物的工具。这些概念首先以研究者与生物统计学家之间对话的形式呈现示例,然后对这些统计概念进行更详细的讨论。使用三个骨骼放射学示例来说明这些概念。

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