Identical-test Roe and Metz simulation model for validating multi-reader methods of analysis for comparing different radiologic imaging modalities.

Identical-test Roe and Metz simulation model for validating multi-reader methods of analysis for comparing different radiologic imaging modalities.
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相同的测试 Roe 和 Metz 模拟模型,用于验证多读取器分析方法,以比较不同的放射成像模式。

DOI:
10.1117/12.2612691
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发表时间:
2022
期刊:
Proceedings of SPIE--the International Society for Optical Engineering
影响因子:
--
通讯作者:
Hillis,StephenL
Hillis,StephenL
中科院分区:
--
文献类型:
--
作者:
Hillis,StephenL

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用于模拟多读卡(MRMC)数据(模拟诊断成像研究的疾病置信度评级)的最常用模型是Roe和梅斯模型,该模型由Roe和梅斯于1997年提出,后来由Hillis(2012)、修道院et al(2013)以及Gallas和Hillis(2014)推广。所有这些模型都基于每个读者的潜在副正态模型生成连续的疾病置信度评级,其中正常和异常评级分布之间的分离在读者之间变化。许多研究已经使用这些模型来评估MRMC分析和样本量方法。在这些论文中建议的用于评估I型错误的模型是“空”模型,其中对于每个测试,跨读取器的预期AUC相同。然而,对于已经提出的空模型,如果两个检验相同,则存在其他不存在的差异。上面引用的论文都没有讨论如何制定一个空模型,也是一个“相同的测试”模型,其中两个测试在所有方面都是相同的。本文的目的是展示如何制定一个相同的测试模型,并讨论这个模型的重要性。使用相同的测试模型,我通过模拟的重要性Obuchowski-Rocket模型的约束,以避免负方差估计,这是以前没有经验证明的结果。
The most frequently used model for simulating multireader multicase (MRMC) data that emulate confidence-of-disease ratings from diagnostic imaging studies has been the Roe and Metz model, proposed by Roe and Metz in 1997 and later generalized by Hillis (2012), Abbey et al (2013) and Gallas and Hillis (2014). All of these models generate continuous confidence-of-disease ratings based on an underlying binormal model for each reader, with the separation between the normal and abnormal rating distributions varying across readers. Numerous studies have used these models for evaluating MRMC analysis and sample size methods. The models suggested in these papers for assessing type I error have been ”null” models, where the expected AUC across readers is the same for each test. However, for the null models that have been suggested, there are other differences that would not exist if the two tests were identical. None of the papers cited above discuss how to formulate a null model that is also an “identical-test” model, where the two tests are identical in all respects. The purpose of this paper is to show how to formulate an identical-test model and to discuss the importance of this model. Using the identical-test model, I show through simulations the importance of the Obuchowski-Rockette model constraints to avoid a negative variance estimate, a result which had not previously been empirically demonstrated.
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