Clinical image quality criteria for full field digital mammography: a first practical application.
In order to quantify the clinical quality of full-field digital mammography, a set of image quality parameters is developed. The set consisted of 12 image quality criteria and 8 physical characteristics of the image. The first set interrogates the visibility of anatomical structures and typical characteristics of a digital image, such as noise and saturation of dark and white areas. The second set of criteria evaluates contrast, sharpness and confidence with the representation of masses, microcalcifications and the image. The use of these criteria is reported in a retrospective study, in which the impact of dose on the radiological quality of digital mammograms is evaluated. Fifty patients acquired in a low-dose mode were retrieved and compared with 50 patients acquired in a dose mode that was set 41% higher. The dose affects, more than expected, contrast and sharpness of the image, whereas the visibility of the anatomical structures remains unchanged. With these parameters, quantification of the image quality is possible; however, because of subjectivity of the parameters, only intra-observer comparison and evaluation of the individual parameters rather than the overall results are advised. Together with physical tests of image quality, critical radiological evaluation of the quality should be included in the acceptance process of digital mammography.
Van Ongeval
Chantal
C
Department of Radiology, UZ Leuven, campus Gasthuisberg, 3000 Leuven, Belgium. chantal.vanongeval@uzleuven.be
Van Steen
André
A
Geniets
Catherine
C
Dekeyzer
Frederik
F
Bosmans
Hilde
H
Marchal
Guy
G
D001941:Breast Diseases / Q000000981:diagnostic imaging* / Q000473:pathology; D002114:Calcinosis / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods / Q000592:standards*; D011785:Quality Assurance, Health Care; D011856:Radiographic Image Enhancement / Q000379:methods* / Q000592:standards*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods / Q000592:standards