title: Geometric feature-based multimodal image registration of contrast-enhanced cardiac CT with gated myocardial perfusion SPECT.
abstract: OBJECTIVE
  Cardiac computed tomography (CT) and single photon emission computed tomography (SPECT) provide clinically complementary information in the diagnosis of coronary artery disease (CAD). Fused anatomical and physiological data acquired sequentially on separate scanners can be coregistered to accurately diagnose CAD in specific coronary vessels.
  
  
  METHODS
  A fully automated registration method is presented utilizing geometric features from a reliable segmentation of gated myocardial perfusion SPECT (MPS) volumes, where regions of myocardium and blood pools are extracted and used as an anatomical mask to de-emphasize the inhomogeneities of intensity distribution caused by perfusion defects and physiological variations. A multiresolution approach is employed to represent coarse-to-fine details of both volumes. The extracted voxels from each level are aligned using a similarity measure with a piecewise constant image model and minimized using a gradient descent method. The authors then perform limited nonlinear registration of gated MPS to adjust for phase differences by automatic cardiac phase matching between CT and MPS. For phase matching, they incorporate nonlinear registration using thin-plate-spline-based warping. Rigid registration has been compared with manual alignment (n=45) on 20 stress/rest MPS and coronary CTA data sets acquired from two different sites and five stress CT perfusion data sets. Phase matching was also compared to expert visual assessment.
  
  
  RESULTS
  As compared with manual alignment obtained from two expert observers, the mean and standard deviation of absolute registration errors of the proposed method for MPS were 4.3 +/- 3.5, 3.6 +/- 2.6, and 3.6 +/- 2.1 mm for translation and 2.1 +/- 3.2 degrees, 0.3 +/- 0.8 degree, and 0.7 +/- 1.2 degrees for rotation at site A and 3.8 +/- 2.7, 4.0 +/- 2.9, and 2.2 +/- 1.8mm for translation and 1.1 +/- 2.0 degrees, 1.6 +/- 3.1 degrees, and 1.9 +/- 3.8 degrees for rotation at site B. The results for CT perfusion were 3.0 +/- 2.9, 3.5 +/- 2.4, and 2.8 +/- 1.0 mm for translation and 3.0 +/- 2.4 degrees, 0.6 +/- 0.9 degree, and 1.2 +/- 1.3 degrees for rotation. The registration error shows that the proposed method achieves registration accuracy of less than 1 voxel (6.4 x 6.4 x 6.4 mm) misalignment. The proposed method was robust for different initializations in the range from -80 to 70, -80 to 70, and -50 to 50 mm in the x-, y-, and z-axes, respectively. Validation results of finding best matching phase showed that best matching phases were not different by more than two phases, as visually determined.
  
  
  CONCLUSIONS
  The authors have developed a fast and fully automated method for registration of contrast cardiac CT with gated MPS which includes nonlinear cardiac phase matching and is capable of registering these modalities with accuracy <10 mm in 87% of the cases.
authors.affiliation: Department of Imaging/AIM program, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA.
authors.forename: Jonghye
authors.initials: J
authors.lastname: Woo
authors.forename: Piotr J
authors.initials: PJ
authors.lastname: Slomka
authors.forename: Damini
authors.initials: D
authors.lastname: Dey
authors.forename: Victor Y
authors.initials: VY
authors.lastname: Cheng
authors.forename: Byung-Woo
authors.initials: BW
authors.lastname: Hong
authors.forename: Amit
authors.initials: A
authors.lastname: Ramesh
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Berman
authors.forename: Ronald P
authors.initials: RP
authors.lastname: Karlsberg
authors.forename: C-C Jay
authors.initials: CC
authors.lastname: Kuo
authors.forename: Guido
authors.initials: G
authors.lastname: Germano
mesh_terms: D000368:Aged; D055426:Cardiac-Gated Single-Photon Emission Computer-Assisted Tomography / Q000379:methods*; D003287:Contrast Media; D005260:Female; D006321:Heart / Q000000981:diagnostic imaging; D006801:Humans; D008297:Male; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D015588:Observer Variation; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013997:Time Factors; D014057:Tomography, X-Ray Computed
chemical_list: D003287:Contrast Media