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Classification of normal screening mammograms is strongly influenced by perceived mammographic breast density
Author(s) -
Ang Zoey ZY,
Rawashdeh Mohammad A,
Heard Rob,
Brennan Patrick C,
Lee Warwick,
Lewis Sarah J
Publication year - 2017
Publication title -
journal of medical imaging and radiation oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.31
H-Index - 43
eISSN - 1754-9485
pISSN - 1754-9477
DOI - 10.1111/1754-9485.12576
Subject(s) - medicine , mammography , mammographic density , breast density , bi rads , audiology , breast cancer , cancer
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.