Geometric feature-based multimodal image registration of contrast-enhanced cardiac CT with gated myocardial perfusion SPECT.

PURPOSE 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 were4.3±3.5, 3.6±2.6, and 3.6±2.1mm for translation and 2.1±3.2°, 0.3±0.8°, and 0.7±1.2° 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°, 1.6±3.1°, and 1.9±3.8° for rotation at site B. The results for CT perfusion were 3.0±2.9, 3.5±2.4, and 2.8±1.0mm for translation and 3.0±2.4°, 0.6±0.9°, and 1.2±1.3° for rotation. The registration error shows that the proposed method achieves registration accuracy of less than 1 voxel (6.4×6.4×6.4mm) misalignment. The proposed method was robust for different initializations in the range from -80 to 70, -80 to 70, and -50to50mm 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<10mm in 87% of the cases.