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 (T-b=-0.439, P=0.001), uniform density (T-b=-0.527, P<0.001), non-dense breasts (T-b=-0.736, P<0.001), symmetrical mammographic features (T-b=-0.474, P=0.001) and overlapped density (T-b=0.630, P<0.001) had a moderate to strong correlation with the difficulty to make normal' decisions. Cases with regular ductal pattern (T-b=0.447, P=0.002), uniform density (T-b=0.550, P<0.001), non-dense breasts (T-b=0.748, P<0.001) and symmetrical mammographic features (T-b=0.460, P=0.001) were considered to be more suitable for single reading, whereas cases with overlapped density were not (T-b=-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.