Optimised motion tracking for positron emission tomography studies of brain function in awake rats.

Positron emission tomography (PET) is a non-invasive molecular imaging technique using positron-emitting radioisotopes to study functional processes within the body. High resolution PET scanners designed for imaging rodents and non-human primates are now commonplace in preclinical research. Brain imaging in this context, with motion compensation, can potentially enhance the usefulness of PET by avoiding confounds due to anaesthetic drugs and enabling freely moving animals to be imaged during normal and evoked behaviours. Due to the frequent and rapid motion exhibited by alert, awake animals, optimal motion correction requires frequently sampled pose information and precise synchronisation of these data with events in the PET coincidence data stream. Motion measurements should also be as accurate as possible to avoid degrading the excellent spatial resolution provided by state-of-the-art scanners. Here we describe and validate methods for optimised motion tracking suited to the correction of motion in awake rats. A hardware based synchronisation approach is used to achieve temporal alignment of tracker and scanner data to within 10 ms. We explored the impact of motion tracker synchronisation error, pose sampling rate, rate of motion, and marker size on motion correction accuracy. With accurate synchronisation (<100 ms error), a sampling rate of >20 Hz, and a small head marker suitable for awake animal studies, excellent motion correction results were obtained in phantom studies with a variety of continuous motion patterns, including realistic rat motion (<5% bias in mean concentration). Feasibility of the approach was also demonstrated in an awake rat study. We conclude that motion tracking parameters needed for effective motion correction in preclinical brain imaging of awake rats are achievable in the laboratory setting. This could broaden the scope of animal experiments currently possible with PET.

Event-based motion correction for PET transmission measurements with a rotating point source.

Accurate attenuation correction is important for quantitative positron emission tomography (PET) studies. When performing transmission measurements using an external rotating radioactive source, object motion during the transmission scan can distort the attenuation correction factors computed as the ratio of the blank to transmission counts, and cause errors and artefacts in reconstructed PET images. In this paper we report a compensation method for rigid body motion during PET transmission measurements, in which list mode transmission data are motion corrected event-by-event, based on known motion, to ensure that all events which traverse the same path through the object are recorded on a common line of response (LOR). As a result, the motion-corrected transmission LOR may record a combination of events originally detected on different LORs. To ensure that the corresponding blank LOR records events from the same combination of contributing LORs, the list mode blank data are spatially transformed event-by-event based on the same motion information. The number of counts recorded on the resulting blank LOR is then equivalent to the number of counts that would have been recorded on the corresponding motion-corrected transmission LOR in the absence of any attenuating object. The proposed method has been verified in phantom studies with both stepwise movements and continuous motion. We found that attenuation maps derived from motion-corrected transmission and blank data agree well with those of the stationary phantom and are significantly better than uncorrected attenuation data.

An event-driven motion correction method for neurological PET studies of awake laboratory animals.

PURPOSE: The purpose of the study is to investigate the feasibility of an event driven motion correction method for neurological microPET imaging of small laboratory animals in the fully awake state. PROCEDURES: A motion tracking technique was developed using an optical motion tracking system and light (<1g) printed targets. This was interfaced to a microPET scanner. Recorded spatial transformations were applied in software to list mode events to create a motion-corrected sinogram. Motion correction was evaluated in microPET studies, in which a conscious animal was simulated by a phantom that was moved during data acquisition. RESULTS: The motion-affected scan was severely distorted compared with a reference scan of the stationary phantom. Motion correction yielded a nearly distortion-free reconstruction and a marked reduction in mean squared error. CONCLUSIONS: This work is an important step towards motion tracking and motion correction in neurological studies of awake animals in the small animal PET imaging environment.