title: Digital mammography: observer performance study of the effects of pixel size on the characterization of malignant and benign microcalcifications.
abstract: OBJECTIVE
  The authors performed this study to evaluate the effects of pixel size on the characterization of mammographic microcalcifications by radiologists.
  
  
  METHODS
  Two-view mammograms of 112 microcalcification clusters were digitized with a laser scanner at a pixel size of 35 microm. Images with pixel sizes of 70, 105, and 140 microm were derived from the 35-microm-pixel size images by averaging neighboring pixels. The malignancy or benignity of the microcalcifications had been determined with findings at biopsy or 2-year follow-up. Region-of-interest images containing the microcalcifications were printed with a laser imager. Seven radiologists participated in a receiver operating characteristic (ROC) study to estimate the likelihood of malignancy. The classification accuracy was quantified with the area under the ROC curve (Az). The statistical significance of the differences in the Az values for different pixel sizes was estimated with the Dorfman-Berbaum-Metz method and the Student paired t test. The variance components were analyzed with a bootstrap method.
  
  
  RESULTS
  The higher-resolution images did not result in better classification; the average Az with a pixel size of 35 microm was lower than that with pixel sizes of 70 and 105 microm. The differences in Az between different pixel sizes did not achieve statistical significance.
  
  
  CONCLUSIONS
  Pixel sizes in the range studied do not have a strong effect on radiologists' accuracy in the characterization of microcalcifications. The low specificity of the image features of microcalcifications and the large interobserver and intraobserver variabilities may have prevented small advantages in image resolution from being observed.
authors.affiliation: Department of Radiology, University of Michigan Hospital, Ann Arbor 48109-0030,USA.
authors.forename: H P
authors.initials: HP
authors.lastname: Chan
authors.forename: M A
authors.initials: MA
authors.lastname: Helvie
authors.forename: N
authors.initials: N
authors.lastname: Petrick
authors.forename: B
authors.initials: B
authors.lastname: Sahiner
authors.forename: D D
authors.initials: DD
authors.lastname: Adler
authors.forename: C
authors.initials: C
authors.lastname: Paramagul
authors.forename: M A
authors.initials: MA
authors.lastname: Roubidoux
authors.forename: C E
authors.initials: CE
authors.lastname: Blane
authors.forename: L K
authors.initials: LK
authors.lastname: Joynt
authors.forename: T E
authors.initials: TE
authors.lastname: Wilson
authors.forename: L M
authors.initials: LM
authors.lastname: Hadjiiski
authors.forename: M M
authors.initials: MM
authors.lastname: Goodsitt
mesh_terms: D001941:Breast Diseases / Q000000981:diagnostic imaging*; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D002114:Calcinosis / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D015588:Observer Variation; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods*