Effect of respiratory motion on plaque imaging in the mouse using Tc-99m labeled Annexin-V
W. Paul Segars1, B.M.W. Tsui1, A.J. DaSilva2, and L. Shao2
The purpose of this study is to improve CT-based attenuation correction of 3D PET data using an attenuation map derived from non-rigidly transformed 3D CT data.
METHODS AND MATERIALS:
Fig. 1. Registration results obtained for one patient. CT (gray level) is shown fused with the PET transmission data (orange). The non-rigid method better compensates for the respiratory differences (diaphragm position, size of lungs).
Utilizing the 4D NURBS-based cardiac-torso (NCAT) phantom with a realistic respiratory model based on high-resolution respiratory-gated CT data, we develop a method to non-rigidly transform 3D CT data obtained during a single breath hold to match that of 3D PET emission data of the same patient obtained over a longer acquisition time and many respiratory cycles. For patients who underwent 3D CT and PET (transmission and emission) studies, the anatomy of the 4D NCAT phantom was first fit to that revealed through automatic segmentation of the 3D CT data. From the 3D PET emission data, a second body outline was segmented, and the height of the diaphragm was estimated using the segmented CT structures as a guide. The difference in the CT and PET body outlines and the change in the height of the diaphragm were used in combination with the 4D NCAT respiratory model to determine the non-rigid CT-PET volumetric transformations for the different organs. The transformations were then applied to the 3D CT image data to form the attenuation map to be used for attenuation correction.
For eight preliminary sets of patient data, the NCAT respiratory model allowed excellent registration of the 3D CT and PET transmission data as assessed visually. An example is shown in Figure 1. Minor registration errors occurred near the diaphragm and lung walls.
The 4D NCAT phantom with a realistic model of the respiratory motion was found to be a valuable tool in a non-rigid warping method to improve CT-PET image fusion. The improved registration provides for a more accurate CT-based attenuation correction of 3D PET image data.
Research contract with Philips Nuclear Medicine-ADAC