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Automatic three-dimensional multimodality registration using radionuclide transmission CT attenuation maps: a phantom
1Department of Physics, University of Calgary, Canada.
Unlabelled:
Coregistration of images from a single subject, acquired by different modalities, is important in clinical diagnosis, surgery and therapy planning. The purpose of this study was to evaluate, using a physical torso phantom, a novel, fully automated method for three-dimensional image registration of CT and SPECT, using radionuclide transmission (RNT) attenuation maps.
Methods:
We obtained CT scans and SPECT scans paired with RNT maps of an anthropomorphic cardiac phantom. RNT attenuation maps were acquired using an uncollimated 99mTc-filled flood source. RNT and SPECT scans were acquired in the same spatial orientation (usual clinical practice in nonuniform attenuation correction). In addition, CT attenuation maps (CTMAPs) for 99mTc SPECT were generated from CT by linear energy scaling. RNT maps were registered to CT and CTMAPs by iterative simplex minimization of count difference and uniformity index (sum of RNT map intensity variances corresponding to each intensity level in the CT volume). In each iteration, three shifts and three angles were adjusted. To register SPECT to CT, we applied the RNT transformation parameters to SPECT.
Results:
RNT maps could be registered to CT and CTMAP images using both criteria. The average three-dimensional distance between landmark and automated registration was 2.5 +/- 1.2 mm for count difference and 3.3 +/- 1.3 mm for uniformity index. The three-dimensional reproducibility errors were 1.2 +/- 0.7 mm for count difference, 2.1 +/- 0.5 mm for uniformity index and 2.3 +/- 1.0 mm for manual marker registration. The minimization of uniformity index was robust when up to 50% CT or RNT slices were missing and was not affected significantly (<2 mm) by realistic variation in CT values (+/- 12 Hounsfield units).
Conclusion:
In addition to typical use in nonuniform attenuation correction, RNT maps can be used for fully automated three-dimensional registration of SPECT to CT. Such registration is not affected by features and quality of SPECT images and avoids difficulties associated with fiducial markers. Our method can be applied to SPECT-CT registration of various organs, such as brain, heart, lungs, breasts and abdomen, including oncological scans.
