Detection of simulated microcalcifications in a phantom with digital mammography: effect of pixel size.
OBJECTIVE
To evaluate the effect of pixel size on the detection of simulated microcalcifications in a phantom with digital mammography.


METHODS
A high-spatial-resolution prototype imager that yields variable pixel size (39 and 78 microm) and a clinical full-field digital mammography (FFDM) system that yields a 100-microm pixel size were used. Radiographic images of a contrast-detail (CD) phantom were obtained to perform four-alternative forced-choice observer experiments. Polymethylmethacrylate was added to obtain phantom thicknesses of 45 and 58 mm, which are typical breast thicknesses encountered in mammography. Phantom images were acquired with both systems under nearly identical exposure conditions by using an antiscatter grid. Twelve images were acquired for each phantom thickness and pixel size (for a total of 72 images), and six observers participated in this study. Observer responses were used to compute the fraction of correctly detected disks. A signal detection model was used to fit the recorded data from which CD characteristics were obtained. Repeated-measures analyses with mixed-effects linear models were performed for each of the six observers. All statistical tests were two sided and unadjusted for multiple comparisons. A P value of .05 or less was considered to indicate a significant difference.


RESULTS
Statistical analysis revealed significantly better CD characteristics with 39- and 78-microm pixel sizes compared with 100-microm pixel size for all disk diameters and phantom thicknesses (P<.001). Increase in phantom thickness degraded CD characteristics regardless of pixel size (P<.001).


CONCLUSIONS
On the basis of the conditions of this study, reducing pixel size below 100 mum with low imaging system noise enhances the visual perception of small objects that correspond to typical microcalcifications.
Suryanarayanan
Sankararaman
S
Winship Cancer Institute and Department of Radiology, Emory University School of Medicine, 1701 Uppergate Dr, Bldg C, Suite 5018, Atlanta, GA 30322, USA.
Karellas
Andrew
A
Vedantham
Srinivasan
S
Sechopoulos
Ioannis
I
D'Orsi
Carl J
CJ
D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D002114:Calcinosis / Q000000981:diagnostic imaging*; D006801:Humans; D016014:Linear Models; D008327:Mammography / Q000379:methods*; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D011858:Radiographic Magnification / Q000295:instrumentation*