title: Fusion of dynamic contrast-enhanced magnetic resonance mammography at 3.0T with X-ray mammograms: pilot study evaluation using dedicated semi-automatic registration software.
abstract: OBJECTIVE
  To evaluate the semi-automatic image registration accuracy of X-ray-mammography (XR-M) with high-resolution high-field (3.0T) MR-mammography (MR-M) in an initial pilot study.
  
  
  METHODS
  MR-M was acquired on a high-field clinical scanner at 3.0T (T1-weighted 3D VIBE ± Gd). XR-M was obtained with state-of-the-art full-field digital systems. Seven patients with clearly delineable mass lesions >10mm both in XR-M and MR-M were enrolled (exclusion criteria: previous breast surgery; surgical intervention between XR-M and MR-M). XR-M and MR-M were matched using a dedicated image-registration algorithm allowing semi-automatic non-linear deformation of MR-M based on finite-element modeling. To identify registration errors (RE) a virtual craniocaudal 2D mammogram was calculated by the software from MR-M (with and w/o Gadodiamide/Gd) and matched with corresponding XR-M. To quantify REs the geometric center of the lesions in the virtual vs. conventional mammogram were subtracted. The robustness of registration was quantified by registration of X-MRs to both MR-Ms with and w/o Gadodiamide.
  
  
  RESULTS
  Image registration was performed successfully for all patients. Overall RE was 8.2mm (1 min after Gd; confidence interval/CI: 2.0-14.4mm, standard deviation/SD: 6.7 mm) vs. 8.9 mm (no Gd; CI: 4.0-13.9 mm, SD: 5.4mm). The mean difference between pre- vs. post-contrast was 0.7 mm (SD: 1.9 mm).
  
  
  CONCLUSIONS
  Image registration of high-field 3.0T MR-mammography with X-ray-mammography is feasible. For this study applying a high-resolution protocol at 3.0T, the registration was robust and the overall registration error was sufficient for clinical application.
authors.affiliation: Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena, Erlanger Allee 101, D-07740 Jena, Germany. dietzelmatthias2@hotmail.com
authors.forename: Matthias
authors.initials: M
authors.lastname: Dietzel
authors.forename: Torsten
authors.initials: T
authors.lastname: Hopp
authors.forename: Nicole
authors.initials: N
authors.lastname: Ruiter
authors.forename: Ramy
authors.initials: R
authors.lastname: Zoubi
authors.forename: Ingo B
authors.initials: IB
authors.lastname: Runnebaum
authors.forename: Werner A
authors.initials: WA
authors.lastname: Kaiser
authors.forename: Pascal A T
authors.initials: PA
authors.lastname: Baltzer
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D003287:Contrast Media; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008327:Mammography; D008875:Middle Aged; D010865:Pilot Projects; D012984:Software
chemical_list: D003287:Contrast Media; C064925:gadodiamide; D019786:Gadolinium DTPA