Motion Compensation in Positron Emission Tomography: Performance of a Clinical Integration at the PET centre Dresden-Rossendorf

Positron emission tomography (PET) is a well-established functional imaging method used in nuclear medicine. It allows for retrieving information about biochemical and physiological processes in vivo. The currently achievable spatial resolution of PET is about 5mm for brain acquisitions and about 8mm for whole-body acquisitions. However, recent improvements in image reconstruction methods point to a resolution of 2mm in the near future. Typical acquisition times range from minutes to hours due to the low signal-to-noise ratio of the measuring principle of PET, as well as due to the monitoring of the metabolism of the patient over a certain time. Therefore, patient motion increasingly limits the possible spatial resolution of PET. In addition, patient immobilizations are only of limited benefit in this context. Thus, if kept uncorrected, patient motion leads to a relevant resolution degradation and incorrect quantification of metabolic parameters.
In this talk, the results of a novel motion compensation method for clinical brain PET acquisitions developed at the research centre Dresden-Rossendorf (Forschungszentrum Dresden-Rossendorf ) in cooperation with the nuclear medicine department of the university hospital of the Technical University Dresden are presented. By using an external motion tracking system, information about the head motion of a patient is continuously acquired during routine PET acquisitions. Based on the motion information, an event-based motion compensation algorithm performs spatial transformations of all registered coincidence events, thus utilizing the raw data of a PET system - the so-called list-mode data. For routine acquisition of this raw data, methods have been developed which allow for the first time to acquire list-mode data from an ECAT Exact HR⁺ PET scanner within an acceptable time frame. Furthermore, methods for acquiring the patient motion in clinical routine and methods for an automatic analysis of the registered motion have been developed. For the clinical integration of the aforementioned motion compensation approach, the development of additional methods (e.g. graphical user interfaces) was also part of this work.
After development, optimisation and integration of the event-based motion compensation in clinical use, analysis with example data sets have been performed. Noticeable changes could be demonstrated by analysis of the qualitative and quantitative effects after the motion compensation. From a qualitative point of view, image artefacts have been eliminated, while quantitatively, the results of a tracer kinetics analysis of a FDOPA acquisition showed relevant changes in the R0k3 rates of an irreversible reference tissue two-compartment model. Thus, it could be shown that an integration of an event-based motion compensation method which is based on the utilization of the raw data of a PET scanner, as well as the use of an external motion tracking system, is not only reasonable and possible for clinical use, but also shows relevant qualitative and quantitative improvements for PET imaging.