A bootstrap method for identifying image regions affected by intra-scan body movement during a PET/CT scan

Intra-scan body movement (IBM) during a PET/CT study can degrade the image quality in subtle ways that are not easy for physicians to detect and can thus affect the diagnostic value of the images. In this study, we propose a method for identifying regions on a PET/CT image that are affected by IBM. The method is based on bootstrapping the sinogram data of short sub-frames of a scan to form multiple sets of sinograms of original scan length, from which multiple images are reconstructed. High voxel-wise percent standard variation among these images would indicate image regions that are compromised by IBM and should be interpreted with caution. Both computer simulation and real human PET/CT data were used in this study to demonstrate the validity of the proposed method for identifying IBM.