4D affine registration models for respiratory-gated PET

The heart position shifts considerably due to motion associated with the respiratory cycle, and this motion can degrade the image quality of cardiac-gated PET studies. One method to combat this motion-induced blur is a respiratory-gated acquisition followed by recombination of registered image volumes using a rigid-body motion assumption; however, deformation of the heart from respiratory motion may reduce the effectiveness of this procedure. We have investigated a 12-parameter global affine motion model for registration of different respiratory gates in an end-diastolic cardiac PET sequence. To obtain robust estimates of motion, a 4D registration model was devised that encouraged smoothly varying motion between adjacent respiratory time frames. Registration parameters were iteratively calculated using a cost function that combined a least squares voxel difference measure with a penalty obtained from a prediction prior. The prior was calculated from adjacent time frames assuming constant velocity and an affine model. After registration, the principal extension ratios were calculated to measure the degree of non-rigid motion. In data from 10 subjects, extension ratios of over 5% were common, indicating that an affine model may provide better registrations and in turn, better motion-corrected composite volumes than could a technique restricted to the 6-parameter rigid body assumption