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.