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Generalized Obuchowski-Rockette Methodology for Analysis of Radiologic Diagnostic Imaging Studies

用于分析放射诊断成像研究的广义 Obuchowski-Rockette 方法

基本信息

批准号：
10172897
负责人：
Stephen Lawrence Hillis
金额：
$ 49.44万
依托单位：
UNIVERSITY OF IOWA
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2023-05-31
项目状态：
已结题

项目摘要

Project Summary Limitations in current statistical analysis methodology for radiologic diagnostic imaging studies greatly restrict a researcher's choices of study designs and types of analyses. Therefore there is a critical need to cre- ate a more encompassing multi-reader diagnostic-study analysis methodology that does not limit the ability of researchers to answer research questions because of strict study-design constraints and few analysis options. Our long-term goal is to develop statistical methodology and software appropriate for diagnostic radio- logical imaging studies that accounts for both patient and reader variability. Our objective here is to further de- velop Obuchowski-Rockette (OR) methodology (and related Dorfman-Berbaum-Metz) software in a way that allows for many more types of analyses and study designs. Specifically, we will pursue four specific aims: (1) Develop a generalized OR methodology that accommodates the same types of designs and analysis models that can currently be used with conventional analysis-of-variance (ANOVA) and linear regression methodology. (2) Provide illustrative examples showing how the generalized OR methodology can be applied to situations where the present OR methodology is not applicable. These include unbalanced designs, regression analyses, multivariate analyses, ANCOVA analyses, partially-paired-reader data, and missing-cases data. (3) Empirically validate the OR methodology for each example in Aim 2 through simulations. (4) Develop R, MATLAB and SAS software code for implementing the generalized OR methodology. Expected outcomes include a generalized OR methodology that has the same analysis and design op- tions as conventional linear regression and ANOVA methodology, in contrast to present OR methodology. The methodology will apply to any type of reader performance outcome, including ROC, FROC, region-of-interest (ROI) and location ROC (LROC), with conclusions generalizing to both cases and readers. Other expected outcomes include illustrative examples of applications of the methodology that were not previously possible, R, MATLAB and SAS code for implementing the methodology, and a thorough validation of the methodology. This research is significant because it will liberate the diagnostic-radiology researcher from the strict analysis and design limitations of the present methodology, thus enhancing the researcher's ability to assess the usefulness of imaging modalities and the effects of reader and case attributes on reader performance in an efficient and meaningful manner. It will be innovative because it will enable new NIH-pertinent horizons that presently are unattainable because of limited analysis methodology. Presently researchers in diagnostic radi- ology are greatly constrained in the research questions that they can investigate by the stringent limitations of the OR (and related DBM) analysis methods. The proposed methodology, by expanding the scope of analyses, will greatly expand the possible scope of diagnostic radiology research questions that can be investigated.

项目摘要目前放射诊断影像研究统计分析方法的局限性很大限制研究人员对研究设计和分析类型的选择。因此，迫切需要重新考虑-- 采用更全面的多读者诊断性研究分析方法，不会限制由于严格的研究设计限制和很少的分析选择，研究人员无法回答研究问题。我们的长期目标是开发适用于诊断无线电的统计方法和软件- 合理的影像研究，同时考虑了患者和读者的可变性。我们的目标是进一步去- 支持Obuchowski-Rockette(OR)方法论(以及相关的Dorfman-Berbaum-Metz)软件允许进行更多类型的分析和研究设计。具体来说，我们会追求四个具体目标：(一) 开发适用于相同类型的设计和分析模型的通用OR方法它目前可用于传统的方差分析(ANOVA)和线性回归方法。 (2)提供说明性例子，说明如何将广义OR方法应用于各种情况目前的OR方法不适用的。这些包括不平衡设计、回归分析、多变量分析、ANCOVA分析、部分配对读者数据和失踪案例数据。(3)经验上的通过模拟验证目标2中每个例子的OR方法。(4)开发了R、MatLab和用于实现通用OR方法的SAS软件代码。预期结果包括具有相同分析和设计操作的通用OR方法传统的线性回归和方差分析方法，而不是目前的OR方法。这个方法将适用于任何类型的读卡器性能结果，包括ROC、FROC、感兴趣区域 (ROI)和位置ROC(LROC)，结论适用于案例和读者。其他预期结果包括以前不可能的方法应用的说明性实例，R，用于实现该方法学的MatLab和SAS代码，并对该方法学进行了彻底的验证。这项研究具有重要的意义，因为它将把诊断放射学的研究人员从严格的分析和设计现有方法的局限性，从而提高研究人员评估成像模式的有用性以及阅读者和案例属性对阅读器性能的影响高效而有意义的方式。它将是创新的，因为它将使与NIH相关的新视野由于有限的分析方法，目前还无法实现。目前，在诊断辐射方面的研究人员科学在研究问题上受到极大的限制，他们可以研究的问题受到 OR(及相关DBM)分析方法。拟议的方法，通过扩大分析范围，将极大地扩大诊断放射学研究的可能范围，即可调查的问题。