Comparison of different methods for data-driven respiratory gating of PET data

Respiratory movement degrades image quality in PET/CT. The first step in correcting for movement is to gate the data into different motion states. In current practice, the gating is based on information from external devices that measure physical parameters such as the chest position. Various groups have proposed methods to extract a gating signal out of the PET data. Here we compare methods using PCA, Laplacian Eigenmaps, Spectral Analysis and sensitivity. We test the methods on clinical PET list mode data for different tracers. We evaluate correlation with the chest position as measured by the Varian RPM system, and stability under increased noise in the PET data, both by reducing counts and reducing total duration. We also compare SUVmax and lesion displacement when gating the PET data based on the signals extracted by the different methods.