Sample size in ROC studies may be significantly reduced by including only difficult cases in the image set, but variability across studies may be a possible obstacle in the development of such a methodology due to case selection. To assess this situation, 300 cases used in a previous large ROC study, which included nine observers, were independently classified as subtle or typical by two experienced readers. Data from the previous study were reanalyzed using data sets consisting only subtle or typical images as designated by each classifier. Results showed a marked decrease in observer performance from the original study's results when only the subtle cases of either classifier were included in the analyses. For 12 of 15 possible comparisons (3 imaging modes and 3 diseases for subtle cases of either classifier were included in the analyses. For 12 of 15 possible comparisons (3 imaging modes and 3 diseases for subtle cases, 3 modes and 2 diseases for typical cases), the Spearman rho correlation coefficient between the performance indices computed for each reader for the subsets classified as subtle and typical was high and significant (P < 0.05). The results obtained in this preliminary study are encouraging and point out areas that warrant further investigation.