Objective Comparison of Quantitative Imaging Modalities Without the Use of a Gold Standard

Abstract

Imaging is often used for the purpose of estimating the value of some parameter of interest. For example, a cardiologist may measure the ejection fraction (EF) of the heart in order to know how much blood is being pumped out of the heart on each stroke. In clinical practice, however, it is difficult to evaluate an estimation method because the gold standard is not known, e.g., a cardiologist does not know the true EF of a patient. Thus, researchers have often evaluated an estimation method by plotting its results against the results of another (more accepted) estimation method, which amounts to using one set of estimates as the pseudogold standard. In this paper, we present a maximum likelihood approach for evaluating and comparing different estimation methods without the use of a gold standard with specific emphasis on the problem of evaluating EF estimation methods. Results of numerous simulation studies will be presented and indicate that the method can precisely and accurately estimate the parameters of a regression line without a gold standard, i.e., without the x-axis.

Acknowledgements

The authors thank Dr. Dennis Patton from the University of Arizona for his helpful discussions on the various modalities used to estimate ejection fractions. This work was supported by NSF grant 9977116 and NIH grants P41 RR14304, KO1 CA87017-01, and RO1 CA 52643.