Liu Yan, Jha Abhinav K
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA.
Proc SPIE Int Soc Opt Eng. 2024 Feb;12929. doi: 10.1117/12.3006888. Epub 2024 Mar 29.
Objective evaluation of quantitative imaging (QI) methods with patient data, while important, is typically hindered by the lack of gold standards. To address this challenge, no-gold-standard evaluation (NGSE) techniques have been proposed. These techniques have demonstrated efficacy in accurately ranking QI methods without access to gold standards. The development of NGSE methods has raised an important question: how accurately can QI methods be ranked without ground truth. To answer this question, we propose a Cramér-Rao bound (CRB)-based framework that quantifies the upper bound in ranking QI methods without any ground truth. We present the application of this framework in guiding the use of a well-known NGSE technique, namely the regression-without-truth (RWT) technique. Our results show the utility of this framework in quantifying the performance of this NGSE technique for different patient numbers. These results provide motivation towards studying other applications of this upper bound.
使用患者数据对定量成像（QI）方法进行客观评估虽然很重要，但通常因缺乏金标准而受到阻碍。为应对这一挑战，人们提出了无金标准评估（NGSE）技术。这些技术已证明在无法获取金标准的情况下，能够有效地对QI方法进行准确排名。NGSE方法的发展引发了一个重要问题：在没有地面真值的情况下，QI方法的排名能有多准确。为回答这个问题，我们提出了一个基于克拉美罗界（CRB）的框架，该框架在没有任何地面真值的情况下量化了QI方法排名的上限。我们展示了该框架在指导一种著名的NGSE技术（即无真值回归（RWT）技术）使用方面的应用。我们的结果表明，该框架在量化这种NGSE技术针对不同患者数量的性能方面具有实用性。这些结果为研究这个上限的其他应用提供了动力。
