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Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
Published on: February 21, 2025
Geometric feature-based multimodal image registration of contrast-enhanced cardiac CT with gated myocardial perfusion
Jonghye Woo1, Piotr J Slomka, Damini Dey
1Department of Imaging/AIM program, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA.
Insights
A new automated method accurately registers cardiac CT and myocardial perfusion SPECT scans for diagnosing coronary artery disease. This fusion of imaging data improves diagnostic accuracy for specific coronary vessels.
Area of Science:
- Medical Imaging
- Cardiovascular Disease Diagnosis
- Image Registration
Background:
- Cardiac computed tomography (CT) and single photon emission computed tomography (SPECT) offer complementary diagnostic information for coronary artery disease (CAD).
- Sequential acquisition of fused anatomical and physiological data on separate scanners necessitates accurate coregistration for precise CAD diagnosis in specific coronary vessels.
Purpose of the Study:
- To present a fully automated method for registering contrast cardiac CT with gated myocardial perfusion SPECT (MPS).
- To achieve accurate fusion of cardiac CT and MPS data for improved CAD diagnosis.
Main Methods:
- Utilized geometric features from segmented gated MPS volumes as an anatomical mask to mitigate intensity variations.
- Employed a multiresolution approach with a piecewise constant image model and gradient descent for alignment.
- Incorporated nonlinear registration using thin-plate-spline warping for automatic cardiac phase matching between CT and MPS.
Main Results:
- The automated method achieved registration accuracy comparable to manual alignment, with mean errors typically below 5 mm and 2 degrees.
- Demonstrated robustness across different sites and CT perfusion datasets, with errors generally less than 1 voxel.
- Validation confirmed that the automated phase matching aligned closely with expert visual assessment.
Conclusions:
- Developed a fast, fully automated registration method for cardiac CT and gated MPS, including nonlinear cardiac phase matching.
- The method demonstrates capability in registering these modalities with accuracy <10 mm in 87% of cases.
- This automated approach facilitates accurate CAD diagnosis through fused imaging data.
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 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.
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