Classification of normal screening mammograms is strongly influenced by perceived mammographic breast density.

INTRODUCTION: To investigate how breast screen readers classify normal screening cases using descriptors of normal mammographic features and to assess test cases for suitability for a single reading strategy. METHODS: Fifteen breast screen readers interpreted a test set of 29 normal screening cases and classified them by firstly rating their perceived difficulty to reach a 'normal' decision, secondly identifying the cases' salient normal mammographic features and thirdly assessing the cases' suitability for a single reading strategy. RESULTS: The relationship between the perceived difficulty in making 'normal' decisions and the normal mammographic features was investigated. Regular ductal pattern (Tb = -0.439, P = 0.001), uniform density (Tb = -0.527, P < 0.001), non-dense breasts (Tb = -0.736, P < 0.001), symmetrical mammographic features (Tb = -0.474, P = 0.001) and overlapped density (Tb = 0.630, P < 0.001) had a moderate to strong correlation with the difficulty to make 'normal' decisions. Cases with regular ductal pattern (Tb = 0.447, P = 0.002), uniform density (Tb = 0.550, P < 0.001), non-dense breasts (Tb = 0.748, P < 0.001) and symmetrical mammographic features (Tb = 0.460, P = 0.001) were considered to be more suitable for single reading, whereas cases with overlapped density were not (Tb = -0.679, P < 0.001). CONCLUSION: The findings suggest that perceived mammographic breast density has a major influence on the difficulty for readers to classify cases as normal and hence their suitability for single reading.