Markerless rat head motion tracking using structured light for brain PET imaging of unrestrained awake small animals

Markerless head motion tracking and event-by-event correction in brain PET

Objective.Head motion correction (MC) is an essential process in brain positron emission tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based motion tracking (HMT) device, for PET head MC. However, this requires attachment of a marker to the subject's head. Markerless HMT (MLMT) methods are more convenient for clinical translation than HMT with external markers. In this study, we validated the United Imaging Healthcare motion tracking (UMT) MLMT system using phantom and human point source studies, and tested its effectiveness on eight18F-FPEB and four11C-LSN3172176 human studies, with frame-based region of interest (ROI) analysis. We also proposed an evaluation metric, registration quality (RQ), and compared it to a data-driven evaluation method, motion-corrected centroid-of-distribution (MCCOD).Approach.UMT utilized a stereovision camera with infrared structured light to capture the subject's real-time 3D facial surface. Each point cloud, acquired at up to 30 Hz, was registered to the reference cloud using a rigid-body iterative closest point registration algorithm.Main results.In the phantom point source study, UMT exhibited superior reconstruction results than the Vicra with higher spatial resolution (0.35 ± 0.27 mm) and smaller residual displacements (0.12 ± 0.10 mm). In the human point source study, UMT achieved comparable performance as Vicra on spatial resolution with lower noise. Moreover, UMT achieved comparable ROI values as Vicra for all the human studies, with negligible mean standard uptake value differences, while no MC results showed significant negative bias. TheRQevaluation metric demonstrated the effectiveness of UMT and yielded comparable results to MCCOD.Significance.We performed an initial validation of a commercial MLMT system against the Vicra. Generally, UMT achieved comparable motion-tracking results in all studies and the effectiveness of UMT-based MC was demonstrated.

Translation of Preclinical PET Imaging Findings: Challenges and Motion Correction to Overcome the Confounding Effect of Anesthetics

Preclinical brain positron emission tomography (PET) in animals is performed using anesthesia to avoid movement during the PET scan. In contrast, brain PET scans in humans are typically performed in the awake subject. Anesthesia is therefore one of the principal limitations in the translation of preclinical brain PET to the clinic. This review summarizes the available literature supporting the confounding effect of anesthesia on several PET tracers for neuroscience in preclinical small animal scans. In a second part, we present the state-of-the-art methodologies to circumvent this limitation to increase the translational significance of preclinical research, with an emphasis on motion correction methods. Several motion tracking systems compatible with preclinical scanners have been developed, each one with its advantages and limitations. These systems and the novel experimental setups they can bring to preclinical brain PET research are reviewed here. While technical advances have been made in this field, and practical implementations have been demonstrated, the technique should become more readily available to research centers to allow for a wider adoption of the motion correction technique for brain research.

Seated versus supine: consideration of the optimum measurement posture for brain-dedicated PET

Some recently developed brain-dedicated positron emission tomography (PET) scanners measure subjects in a sitting position. Sitting enables PET scanning under more natural conditions for the subjects and also helps with making the scanners smaller. It is unclear, however, how much the degree of head motion when sitting differs from the supine posture commonly employed in clinical PET. In this report, we describe development of a markerless and contactless head motion tracking system and a study of healthy volunteers in several different postures to determine the optimum posture for brain PET. We used Kinect^® (Microsoft) and developed software that can measure head motion with about 1 mm (translation) and less than 1° (rotation) accuracy. In the volunteer study, we measured the amount of head motion, with and without head fixation, in supine, normal sitting, and reclining postures. The results indicated that the normal sitting posture without head fixation had the largest head movement, and that the reclining and supine postures were similarly effective for minimizing head movement (average head movement of about 0.5 mm during 1 min). We also visualized the influence that head motion had on images for each pose by simulating the actual motions obtained from the volunteer study using a digital Hoffman phantom. Comparisons with the original image showed that the extent to which motion was reduced in the reclining and supine postures were quantitatively equivalent. The head motions of the volunteer studies were also reproduced using a mannequin head on a motorized stage to assess how well the proposed motion measurement system worked when used for motion correction. The results indicated that even though the system improved image quality for all postures, the reclining and supine postures could provide better image quality than the normal sitting posture.

Markerless motion tracking and correction for PET, MRI, and simultaneous PET/MRI

OBJECTIVE

We demonstrate and evaluate the first markerless motion tracker compatible with PET, MRI, and simultaneous PET/MRI systems for motion correction (MC) of brain imaging.

METHODS

PET and MRI compatibility is achieved by careful positioning of in-bore vision extenders and by placing all electronic components out-of-bore. The motion tracker is demonstrated in a clinical setup during a pediatric PET/MRI study including 94 pediatric patient scans. PET MC is presented for two of these scans using a customized version of the Multiple Acquisition Frame method. Prospective MC of MRI acquisition of two healthy subjects is demonstrated using a motion-aware MRI sequence. Real-time motion estimates are accompanied with a tracking validity parameter to improve tracking reliability.

RESULTS

For both modalities, MC shows that motion induced artifacts are noticeably reduced and that motion estimates are sufficiently accurate to capture motion ranging from small respiratory motion to large intentional motion. In the PET/MRI study, a time-activity curve analysis shows image improvements for a patient performing head movements corresponding to a tumor motion of ±5-10 mm with a 19% maximal difference in standardized uptake value before and after MC.

CONCLUSION

The first markerless motion tracker is successfully demonstrated for prospective MC in MRI and MC in PET with good tracking validity.

SIGNIFICANCE

As simultaneous PET/MRI systems have become available for clinical use, an increasing demand for accurate motion tracking and MC in PET/MRI scans has emerged. The presented markerless motion tracker facilitate this demand.

Acute Ketamine Infusion in Rat Does Not Affect In Vivo [11C]ABP688 Binding to Metabotropic Glutamate Receptor Subtype 5

Detecting changes in metabotropic glutamate receptor 5 (mGluR5) availability through molecular imaging with the positron emission tomography (PET) tracer [¹¹C]ABP688 is valuable for studying dysfunctional glutamate transmission associated with neuropsychiatric disorders. Using an infusion protocol in rats, we visualized the acute effect of subanesthetic doses of ketamine on mGluR5 in rat brain. Ketamine is an N-methyl-D-aspartate (NMDA) receptor antagonist known to increase glutamate release. Imaging was performed with a high-affinity PET ligand [¹¹C]ABP688, a negative allosteric modulator of mGluR5. Binding did not change significantly from baseline to ketamine in any region, thereby confirming previous literature with other NMDA receptor antagonists in rodents. Hence, in rats, we could not reproduce the findings in a human setup showing significant decreases in the [¹¹C]ABP688 binding after a ketamine bolus followed by ketamine infusion. Species differences may have contributed to the different findings in the present study of rats. In conclusion, we could not confirm in rats that endogenous glutamate increases by ketamine infusion are reflected in [¹¹C]ABP688 binding decreases as was previously shown for humans.

Open-field PET: Simultaneous brain functional imaging and behavioural response measurements in freely moving small animals

A comprehensive understanding of how the brain responds to a changing environment requires techniques capable of recording functional outputs at the whole-brain level in response to external stimuli. Positron emission tomography (PET) is an exquisitely sensitive technique for imaging brain function but the need for anaesthesia to avoid motion artefacts precludes concurrent behavioural response studies. Here, we report a technique that combines motion-compensated PET with a robotically-controlled animal enclosure to enable simultaneous brain imaging and behavioural recordings in unrestrained small animals. The technique was used to measure in vivo displacement of [¹¹C]raclopride from dopamine D2 receptors (D2R) concurrently with changes in the behaviour of awake, freely moving rats following administration of unlabelled raclopride or amphetamine. The timing and magnitude of [¹¹C]raclopride displacement from D2R were reliably estimated and, in the case of amphetamine, these changes coincided with a marked increase in stereotyped behaviours and hyper-locomotion. The technique, therefore, allows simultaneous measurement of changes in brain function and behavioural responses to external stimuli in conscious unrestrained animals, giving rise to important applications in behavioural neuroscience.

Estimation of and correction for finite motion sampling errors in small animal PET rigid motion correction

Motion tracking with finite time sampling causing an associated unknown residual motion between two motion measurements is one of the factors contributing to resolution loss in small animal PET motion correction. The aim of this work is (i) to provide a means to estimate the effect of the finite motion sampling on the spatial resolution of the motion correction reconstructions and (ii) to correct for this residual motion thereby minimizing resolution loss. We calculate a tailored spatially variant deconvolution kernel from the measured motion data which is then used to deconvolve the motion corrected image using a 3D Richardson-Lucy algorithm. A simulation experiment of numerical phantoms as well as a microDerenzo phantom experiment wherein the phantom was manually moved at different speeds was performed to assess the performance of our proposed method. In the motion corrected images of the microDerenzo phantom there was an average rod FWHM differences between the slow and fast motion cases of 9.7%. This difference was reduced to 5.8% after applying the residual motion deconvolution. In awake animal experiments, the proposed method can serve to mitigate the finite sampling factor degrading the spatial resolution as well as the resolution differences between fast-moving and slow-moving animals.

Graphical abstract

Markerless motion estimation for motion-compensated clinical brain imaging

Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon emission computed tomography (SPECT) and computed tomography (CT). However, motion-compensated imaging protocols are not in widespread clinical use for these modalities. A key reason for this seems to be the lack of a practical motion tracking technology that allows for smooth and reliable integration of motion-compensated imaging protocols in the clinical setting. We seek to address this problem by investigating the feasibility of a highly versatile optical motion tracking method for PET, SPECT and CT geometries. The method requires no attached markers, relying exclusively on the detection and matching of distinctive facial features. We studied the accuracy of this method in 16 volunteers in a mock imaging scenario by comparing the estimated motion with an accurate marker-based method used in applications such as image guided surgery. A range of techniques to optimize performance of the method were also studied. Our results show that the markerless motion tracking method is highly accurate (<2 mm discrepancy against a benchmarking system) on an ethnically diverse range of subjects and, moreover, exhibits lower jitter and estimation of motion over a greater range than some marker-based methods. Our optimization tests indicate that the basic pose estimation algorithm is very robust but generally benefits from rudimentary background masking. Further marginal gains in accuracy can be achieved by accounting for non-rigid motion of features. Efficiency gains can be achieved by capping the number of features used for pose estimation provided that these features adequately sample the range of head motion encountered in the study. These proof-of-principle data suggest that markerless motion tracking is amenable to motion-compensated brain imaging and holds good promise for a practical implementation in clinical PET, SPECT and CT systems.