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Rationale and Objectives: To investigate consistency of the orders of performance levels when interpreting mammograms under three different reading paradigms., Materials and Methods: We performed a retrospective observer study in which nine experienced radiologists rated an enriched set of mammography examinations that they personally had read in the clinic ("individualized") mixed with a set that none of them had read in the clinic ("common set"). Examinations were interpreted under three different reading paradigms: binary using screening Breast Imaging Reporting and Data System (BI-RADS), receiver-operating characteristic (ROC), and free-response ROC (FROC). The performance in discriminating between cancer and noncancer findings under each of the paradigms was summarized using Youden's index/2+0.5 (Binary), nonparameteric area under the ROC curve (AUC), and an overall FROC index (JAFROC-2). Pearson correlation coefficients were then computed to assess consistency in the ordering of observers' performance levels. Statistical significance of the computed correlation coefficients was assessed using bootstrap confidence intervals obtained by resampling sets of examination-specific observations., Results: All but one of the computed pair-wise correlation coefficients were larger than 0.66 and were significantly different from zero. The correlation between the overall performance measures under the Binary and ROC paradigms was the lowest (0.43) and was not significantly different from zero (95% confidence interval -0.078 to 0.733)., Conclusion: The use of different evaluation paradigms in the laboratory tends to lead to consistent ordering of the overall performance levels of observers. However, one should recognize that conceptually similar performance indexes resulting from different paradigms often measure different performance characteristics and thus disagreements are not only possible but frequently quite natural.

The task of searching and detecting multiple abnormalities depicted on an image, or a series of images, is a common problem in different areas such as military target detection or diagnostic medical imaging. A free response receiver operating characteristic (FROC) approach for assessing performance in many of these scenarios entails marking the locations of suspected abnormalities and indicating a level of suspicion at each of the marked locations. One of the important characteristics of a system being evaluated under the FROC paradigm is its performance in the conventional ROC domain, namely classifying a subject (or a unit of interest) as "negative" or "positive" in regard to the presence of the abnormality (or any of the abnormalities) of interest. With FROC data we can compare subjects by specifying a function of multiple scores within a subject. This approach allows formulating subject-based ROC type indices that can be estimated using existing ROC concepts. In this article we focus on indices that reflect the ability of the system to discriminate between actually negative and actually positive subjects. We consider a previously proposed index that is based on the comparison of the highest scores on subjects and two new indices that are based on potentially more stable comparison functions, namely comparison of average scores and stochastic dominance. Based on these indices we develop nonparametric procedures for comparing subject-based discriminative ability of diagnostic systems being evaluated under the FROC paradigm. We also investigate the properties of the statistical procedures in a simulation study.

Rationale and Objectives: The aim of the study is to develop a permutation test to compare receiver operating characteristic (ROC) curves of two diagnostic modalities in a multireader paired design., Materials and Methods: A statistical test for comparing two diagnostic modalities is developed based on all possible exchanges of the set of reader-ratings between the two modalities. An exact permutation test is formed by determining the frequency of the most extreme values of the statistic estimating the average difference in the areas under the ROC curves (AUCs). An asymptotic version of the test is constructed by obtaining the exact permutation variance and appealing to the asymptotic normality of the nonparametric estimator of the average difference in areas. Computer simulations were conducted to validate the type I error for small sample sizes., Results: The new test provides a permutation approach for comparing ROC curves in a multireader paired-design setting in which effects of the readers are considered to be fixed. The type I error of the asymptotic test is close to the true value, even for samples as small as 20 normal and 20 abnormal cases. The test is designed to be sensitive to alternatives in which the AUCs of the two diagnostic modalities differ., Conclusions: The proposed test provides a powerful method for comparing two diagnostic modalities in a multireader paired-study design when the primary interest is to detect difference in average AUCs.

Rationale and Objectives: The aim of the study is to assess variance components in observer performance studies and the possible impact on study results and conclusions., Materials and Methods: Two previously performed retrospective receiver operating characteristic-type observer performance studies to evaluate the performance of seven radiologists in detecting interstitial disease on conventional posteroanterior chest films and nine radiologists in detecting interstitial disease on a high-resolution workstation were reanalyzed by using the Beiden, Wagner, and Campbell nine-component model to estimate the different variance components. We estimated case-, reader-, and mode-related components of the variance for the group as a whole and after excluding (round robin) each reader. Overall variance was evaluated, and the effect of individual readers on overall study conclusions was assessed., Results: Overall results and conclusions of the reanalysis agreed with the original one in that, as a group, radiologists performed significantly better when using conventional films (P < .05) in both studies. Reader variability was large compared with all other components, and in one study, it was substantially larger for the workstation reading mode. Reader variability was affected substantially by one observer in each study, and in one study, reader-by-mode variability was affected by another reader who performed better on the workstation., Conclusion: Estimates of variance components can shed light on the appropriateness of study design, as well as the sensitivity of results to the inclusion (or exclusion) of individual observers.

Rationale and Objectives: We sought to develop a new index that incorporates utility-weights when assessing the overall performance of a diagnostic system and to provide a statistical test for comparing two indices in a paired study design., Materials and Methods: The area under the receiver operating characteristic (ROC) curve (AUC) was used as the basis for constructing a new index. The index we propose represents a weighted average of class-specific AUCs each of which relates to a class of pairs of actually negative (normal) and actually positive (abnormal) cases with a specific predetermined utility (or clinical importance). For each pair of normal-abnormal cases, the utility is defined a priori and based on external (covariate) information. In the proposed approach utility-weights represent the relative importance (utility) of discriminating between different types of normal and abnormal cases (pairs of the same type are combined in the classes termed utility-classes). We also describe a simple nonparametric procedure for comparing the proposed indices as computed from paired data. Computer simulations were conducted to evaluate the behavior of the type I error of the proposed test in the simple albeit important instance of two utility-classes., Results: The new index provides an extension of the commonly used area under the ROC curve. It allows for incorporation of utility-weights into the analysis and reduces to the conventional AUC index when all assigned utility-weights are equal to unity. Computer simulations indicate that in the considered scenario of two utility-classes, the type I error of the proposed test is comparable to that of the conventional nonparametric test for equality of AUC indices., Conclusions: The proposed index and the statistical test provide a practical approach of incorporating utilities when comparing diagnostic systems.