<title>Factor analysis for spillover correction or movement detection in dynamic PET studies</title>

Abstract

In this study, we applied factor analysis of dynamic structures (FADS) techniques in dynamic PET images to (1) extract the arterial time activity curve (TAC) from human adult or small monkey dynamic FDG PET; and (2) investigate the use of FADS generated factor images and factor curves to detect large subject movements during dynamic GA-68 EDTA scans of brain tumor patients. The results showed that a blood sample constraint improved the accuracy of FADS technique in extracting the `pure' blood pool TAC from dynamic PET studies that have large spillover problems. The studies of GA-68 EDTA brain PET studies showed that three major factors were extracted from images using FADS. For studies with little patient movement, a standard pattern of three factor curves and three factor images were obtained. However, large patient movement changed the outcomes of FADS results. We conclude that (1) FADS technique with a blood sample allows the extraction of the `pure' blood pool TAC directly from quantitative PET images without requiring multiple blood samples, region-of- interest drawing or spillover correction; and (2) FADS technique provides a sensitive way to detect large patient movements in dynamic PET studies.