title: Comparison of tissue equalization, and premium view post-processing methods in full field digital mammography.
abstract: OBJECTIVE
  To retrospectively evaluate the diagnostic abilities of 2 post-processing methods provided by GE Senographe DS system, tissue equalization (TE) and premium view (PV) in full field digital mammography (FFDM).
  
  
  METHODS
  In accordance with the ethical standards of the World Medical Association, this study was approved by regional ethics committee and signed informed patient consents were obtained. We retrospectively reviewed digital mammograms from 101 women (mean age, 47 years; range, 23-81 years) in the modes of TE and PV, respectively. Three radiologists, fully blinded to the post-processing methods, all patient clinical information and histologic results, read images by using objective image interpretation criteria for diagnostic information end points such as lesion border delineation, definition of disease extent, visualization of internal and surrounding morphologic features of the lesions. Also, overall diagnostic impression in terms of lesion conspicuity, detectability and diagnostic confidence was assessed. Between-group comparisons were performed with Wilcoxon signed rank test.
  
  
  RESULTS
  Readers 1, 2, and 3 demonstrated significant overall better impression of PV in 29, 27, and 24 patients, compared with that for TE in 12, 13, and 11 patients, respectively (p<0.05). Significant (p<0.05) better impression of PV was also demonstrated for diagnostic information end points. Importantly, PV proved to be more sensitive than TE while detecting malignant lesions in dense breast rather than benign lesions and malignancy in non-dense breast (p<0.01).
  
  
  CONCLUSIONS
  PV compared with TE provides marked better diagnostic information in FFDM, particularly for patients with malignancy in dense breast.
authors.affiliation: Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China. chenby128@yahoo.com
authors.forename: Baoying
authors.initials: B
authors.lastname: Chen
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Jin
authors.initials: J
authors.lastname: Huang
authors.forename: Ming
authors.initials: M
authors.lastname: Zhao
authors.forename: Guangbin
authors.initials: G
authors.lastname: Cui
authors.forename: Jing
authors.initials: J
authors.lastname: Xu
authors.forename: Wei
authors.initials: W
authors.lastname: Guo
authors.forename: Pang
authors.initials: P
authors.lastname: Du
authors.forename: Pei
authors.initials: P
authors.lastname: Li
authors.forename: Jun
authors.initials: J
authors.lastname: Yu
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies; D018709:Statistics, Nonparametric