Synthesis and Preclinical Evaluation of Fluorinated 5-Azaindoles as CB2 PET Radioligands.

Several classes of cannabinoid receptor type 2 radioligands have been evaluated for imaging of neuroinflammation, with successful clinical translation yet to take place. Here we describe the synthesis of fluorinated 5-azaindoles and pharmacological characterization and in vivo evaluation of 18F-radiolabeled analogues. [18F]2 (hCB2 Ki = 96.5 nM) and [18F]9 (hCB2 Ki = 7.7 nM) were prepared using Cu-mediated 18F-fluorination with non-decay-corrected radiochemical yields of 15 ± 6% and 18 ± 2% over 85 and 80 min, respectively, with high radiochemical purities (>97%) and molar activities (140-416 GBq/µmol). In PET imaging studies in rats, both [18F]2 and [18F]9 demonstrated specific binding in CB2-rich spleen after pretreatment with CB2-specific GW405833. Moreover, [18F]9 exhibited higher brain uptake at later time points in a murine model of neuroinflammation compared with a healthy control group. The results suggest further evaluation of azaindole based CB2 radioligands is warranted in other neuroinflammation models.

Reduction of scan duration and radiation dose in cerebral CT perfusion imaging of acute stroke using a recurrent neural network.

Objective. Cerebral CT perfusion (CTP) imaging is most commonly used to diagnose acute ischaemic stroke and support treatment decisions. Shortening CTP scan duration is desirable to reduce the accumulated radiation dose and the risk of patient head movement. In this study, we present a novel application of a stochastic adversarial video prediction approach to reduce CTP imaging acquisition time.Approach. A variational autoencoder and generative adversarial network (VAE-GAN) were implemented in a recurrent framework in three scenarios: to predict the last 8 (24 s), 13 (31.5 s) and 18 (39 s) image frames of the CTP acquisition from the first 25 (36 s), 20 (28.5 s) and 15 (21 s) acquired frames, respectively. The model was trained using 65 stroke cases and tested on 10 unseen cases. Predicted frames were assessed against ground-truth in terms of image quality and haemodynamic maps, bolus shape characteristics and volumetric analysis of lesions.Main results. In all three prediction scenarios, the mean percentage error between the area, full-width-at-half-maximum and maximum enhancement of the predicted and ground-truth bolus curve was less than 4 ± 4%. The best peak signal-to-noise ratio and structural similarity of predicted haemodynamic maps was obtained for cerebral blood volume followed (in order) by cerebral blood flow, mean transit time and time to peak. For the 3 prediction scenarios, average volumetric error of the lesion was overestimated by 7%-15%, 11%-28% and 7%-22% for the infarct, penumbra and hypo-perfused regions, respectively, and the corresponding spatial agreement for these regions was 67%-76%, 76%-86% and 83%-92%.Significance. This study suggests that a recurrent VAE-GAN could potentially be used to predict a portion of CTP frames from truncated acquisitions, preserving the majority of clinical content in the images, and potentially reducing the scan duration and radiation dose simultaneously by 65% and 54.5%, respectively.

Transition to Fast Whole-Body SPECT/CT Bone Imaging: An Assessment of Image Quality.

OBJECTIVE: To investigate the impact of reduced SPECT acquisition time on reconstructed image quality for diagnostic purposes. METHOD: Data from five patients referred for a routine bone SPECT/CT using the standard multi-bed SPECT/CT protocol were reviewed. The acquisition time was 900 s using gating technique; SPECT date was resampled into reduced data sets of 480 s, 450 s, 360 s and 180 s acquisition duration per bed position. Each acquisition time was reconstructed using a fixed number of subsets (8 subsets) and 4, 8, 12, and 16 iterations, followed by a post-reconstruction 3D Gaussian filter of 8 mm FWHM. Two Nuclear Medicine physicians analysed all images independently to score image quality, noise and diagnostic confidence based on a pre-defined 4-point scale. RESULTS: Our result showed that the most frequently selected categories for 480 s and 450 s images were good image quality, average noise and fair confidence, particularly at lower iteration numbers 4 and 8. For the shortened acquisition time of 360 s and 180 s, statistical significance was observed in most reconstructed images compared with 900 s. CONCLUSION: The SPECT/CT can significantly shorten the acquisition time with maintained image quality, noise and diagnostic confidence. Therefore, acquiring data over 480 s and 450 s is feasible for WB-SPECT/CT bone scans to provide an optimal balance between acquisition time and image quality.

Optimization of 99m Tc whole-body SPECT/CT image quality: A phantom study.

PURPOSE: Investigate the impact of acquisition time and reconstruction parameters on single-photon emission computed tomography/computed tomography (SPECT/CT) image quality with the ultimate aim of finding the shortest possible acquisition time for clinical whole-body SPECT/CT (WB-SPECT/CT) while maintaining image quality METHODS: The National Electrical Manufacturers Association (NEMA) image quality measurements were performed on a SPECT/CT imaging system using a NEMA International Electrotechnical Commission (IEC) phantom with spherical inserts of varying diameter (10-37 mm), filled with 99m Tc in activity sphere-to-background concentration ratio of 8.5:1. A gated acquisition was acquired and binned data were summed to simulate acquisitions of 15, 8, and 3 s per projection angle. Images were reconstructed on a Hermes (HERMES Medical Solutions AB, Stockholm, Sweden) workstation using eight subsets and between 4 and 24 iterations of the three-dimensional (3D) ordered subset expectation maximization (OSEM) algorithm. Reconstructed images were post-smoothed with 3D Gaussian filter ranging from 0 to 12 mm full-width at half maximum (FWHM). Contrast recovery, background variability, and contrast-to-noise ratio were evaluated RESULTS: As expected, the spheres were more clearly defined as acquisition time and count statistics improved. The optimal iteration number and Gaussian filter were determined from the contrast recovery convergence and level of noise. Convergence of contrast recovery was observed at eight iterations while 12 iterations yielded stabilized values at all acquisition times. In addition, it was observed that applying 3D Gaussian filter of 8-12 mm FWHM suppressed the noise and mitigated Gibbs artifacts. Background variability was larger for small spheres than larger spheres and the noise decreased when acquisition time became longer. A contrast-to-noise ratio >5 was reached for the two smallest spheres of 10 and 13 mm at acquisition times of 8 s CONCLUSION: Optimized reconstruction parameters preserved image quality with reduce acquisition time in present study. This study suggests an optimal protocol for clinical 99m Tc SPECT/CT can be reached at 8 s per projection angle, with data reconstructed using 12 iterations and eight subset of the 3D OSEM algorithm and 8 mm Gaussian post-filter.

Inferring CT perfusion parameters and uncertainties using a Bayesian approach.

BACKGROUND: Computed tomography perfusion imaging is commonly used for the rapid assessment of patients presenting with symptoms of acute stroke. Maps of perfusion parameters, such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) derived from the perfusion scan data, provide crucial information for stroke diagnosis and treatment decisions. Most CT scanners use singular value decomposition (SVD)-based methods to calculate these parameters. However, some known problems are associated with conventional methods. METHODS: In this work, we propose a Bayesian inference algorithm, which can derive both the perfusion parameters and their uncertainties. We apply the variational technique to the inference, which then becomes an expectation-maximization problem. The probability distribution (with Gaussian mean and variance) of each estimated parameter can be obtained, and the coefficient of variation is used to indicate the uncertainty. We perform evaluations using both simulations and patient studies. RESULTS: In a simulation, we show that the proposed method has much less bias than conventional methods. Then, in separate simulations, we apply the proposed method to evaluate the impacts of various scan conditions, i.e., with different frame intervals, truncated measurement, or motion, on the parameter estimate. In one patient study, the method produced CBF and MTT maps indicating an ischemic lesion consistent with the radiologist's report. In a second patient study affected by patient movement, we showed the feasibility of applying the proposed method to motion corrected data. CONCLUSIONS: The proposed method can be used to evaluate confidence in parameter estimation and the scan protocol design. More clinical evaluation is required to fully test the proposed method.

Head movement during cerebral CT perfusion imaging of acute ischaemic stroke: Characterisation and correlation with patient baseline features.

PURPOSE: To quantitatively characterise head motion prevalence and severity and to identify patient-based risk factors for motion during cerebral CT perfusion (CTP) imaging of acute ischaemic stroke. METHODS: The head motion of 80 stroke patients undergoing CTP imaging was classified retrospectively into four categories of severity. Each motion category was then characterised quantitatively based on the average head movement with respect to the first frame for all studies. Statistical testing and principal component analysis (PCA) were then used to identify and analyse the relationship between motion severity and patient baseline features. RESULTS: 46/80 (58%) of patients showed negligible motion, 19/80 (24%) mild-to-moderate motion, and 15/80 (19%) considerable-to-extreme motion sufficient to affect diagnostic/therapeutic accuracy even with correction. The most prevalent movement was "nodding" with maximal translation/rotation in the sagittal/axial planes. There was a tendency for motion to worsen as scan proceeded and for faster motion to occur in the first 15 s. Statistical analyses showed that greater stroke severity (National Institutes of Health Stroke Scale (NIHSS)), older patient age and shorter time from stroke onset were predictive of increased head movement (p < 0.05 Kruskal-Wallis). Using PCA, the combination of NIHSS and patient age was found to be highly predictive of head movement (p < 0.001). CONCLUSIONS: Quantitative methods were developed to characterise CTP studies impacted by motion and to anticipate patients at-risk of motion. NIHSS, age, and time from stroke onset function as good predictors of motion likelihood and could potentially be used pre-emptively in CTP scanning of acute stroke.

Motion estimation and correction in SPECT, PET and CT.

Patient motion impacts single photon emission computed tomography (SPECT), positron emission tomography (PET) and x-ray computed tomography (CT) by giving rise to projection data inconsistencies that can manifest as reconstruction artifacts, thereby degrading image quality and compromising accurate image interpretation and quantification. Methods to estimate and correct for patient motion in SPECT, PET and CT have attracted considerable research effort over several decades. The aims of this effort have been two-fold: to estimate relevant motion fields characterizing the various forms of voluntary and involuntary motion; and to apply these motion fields within a modified reconstruction framework to obtain motion-corrected images. The aims of this review are to outline the motion problem in medical imaging and to critically review published methods for estimating and correcting for the relevant motion fields in clinical and preclinical SPECT, PET and CT. Despite many similarities in how motion is handled between these modalities, utility and applications vary based on differences in temporal and spatial resolution. Technical feasibility has been demonstrated in each modality for both rigid and non-rigid motion but clinical feasibility remains an important target. There is considerable scope for further developments in motion estimation and correction, and particularly in data-driven methods that will aid clinical utility. State-of-the-art deep learning methods may have a unique role to play in this context.

A motion correction approach for oral and maxillofacial cone-beam CT imaging.

Patient movement affects image quality in oral and maxillofacial cone-beam computed tomography imaging. While many efforts are made to minimize the possibility of motion during a scan, relatively little attention has been given to motion correction after acquisition. We propose a novel method which can improve the image quality after an oral and maxillofacial scan. The proposed method is based on our previous work and is a retrospective motion estimation and motion compensation (ME/MC) approach that iteratively estimates and compensates for rigid pose change over time. During motion estimation, image update and motion update are performed alternately in a multi-resolution scheme to obtain the motion. We propose use of a feature-based motion update and patch-based image update in the iterative estimation process, to alleviate the effect of limited scan field of view on estimation. During motion compensation, a fine-resolution image reconstruction was performed with compensation for the estimated motion. The proposed ME/MC method was evaluated with simulations, phantom and patient studies. Two experts in dentomaxillofacial radiology assessed the diagnostic importance of the resulting motion artifact suppression. The quality of the reconstructed images was improved after motion compensation, and most of the image artifacts were eliminated. Quantitative analysis by comparison to a reference image and by calculation of a sharpness metric agreed with the qualitative observation. The results are promising, and further evaluation is required to assess the clinical value of the proposed method.

Efficient radiation dose reduction in whole-brain CT perfusion imaging using a 3D GAN: performance and clinical feasibility.

Dose reduction in cerebral CT perfusion (CTP) imaging is desirable but is accompanied by an increase in noise that can compromise the image quality and the accuracy of image-based haemodynamic modelling used for clinical decision support in acute ischaemic stroke. The few reported methods aimed at denoising low-dose CTP images lack practicality by considering only small sections of the brain or being computationally expensive. Moreover, the prediction of infarct and penumbra size and location-the chief means of decision support for treatment options-from denoised data has not been explored using these approaches. In this work, we present the first application of a 3D generative adversarial network (3D GAN) for predicting normal-dose CTP data from low-dose CTP data. Feasibility of the approach was tested using real data from 30 acute ischaemic stroke patients in conjunction with low dose simulation. The 3D GAN model was applied to 643voxel patches extracted from two different configurations of the CTP data-frame-based and stacked. The method led to whole-brain denoised data being generated for haemodynamic modelling within 90 s. Accuracy of the method was evaluated using standard image quality metrics and the extent to which the clinical content and lesion characteristics of the denoised CTP data were preserved. Results showed an average improvement of 5.15-5.32 dB PSNR and 0.025-0.033 structural similarity index (SSIM) for CTP images and 2.66-3.95 dB PSNR and 0.036-0.067 SSIM for functional maps at 50% and 25% of normal dose using GAN model in conjunction with a stacked data regime for image synthesis. Consequently, the average lesion volumetric error reduced significantly (p-value <0.05) by 18%-29% and dice coefficient improved significantly by 15%-22%. We conclude that GAN-based denoising is a promising practical approach for reducing radiation dose in CTP studies and improving lesion characterisation.

Quantitative PET in the 2020s: a roadmap.

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

Anaesthetic-dependent changes in gene expression following acute and chronic exposure in the rodent brain.

Anaesthesia has been predicted to affect gene expression of the memory-related regions of the brain including the primary visual cortex. It is also believed that anaesthesia causes inflammation of neural tissues, increasing elderly patients' chances of developing precursor lesions that lead to Alzheimer's disease and other neurodegeneration related diseases. We have analyzed the expression of over 22,000 genes and 129,800 transcripts using oligonucleotide microarrays to examine the brain expression profiles in Sprague Dawley rats following exposure to acute or chronic doses of the anaesthetics isoflurane, ketamine and propofol. Here we report for the first time molecular and genomic data on the effect on the rodent brain of chronic and acute exposure to isoflurane, ketamine and propofol. Our screen identified multiple genes that responded to all three anaesthetics. Although some of the genes were previously known to be anaesthesia responsive, we have for the most part identified novel genes involved in the acute and chronic rodent brain response to different anaesthesia treatments. The latter may be useful candidate genes in the search to elucidate the molecular pathways mediating anaesthetic effects in the brain and may allow us to identify mechanisms by which anaesthetics could impact on neurodegeneration.

Synthesis and in vitro evaluation of fluorine-18 benzimidazole sulfones as CB2 PET-radioligands.

Cannabinoid type 2 receptor (CB2) is up-regulated on activated microglial cells and can potentially be used as a biomarker for PET-imaging of neuroinflammation. In this study the synthesis and pharmacological evaluation of novel fluorinated pyridyl and ethyl sulfone analogues of 2-(tert-butyl)-5-((2-fluoropyridin-4-yl)sulfonyl)-1-(2-methylpentyl)-1H-benzo[d]imidazole (rac-1a) are described. In general, the ligands showed low nanomolar potency (CB2 EC50 < 10 nM) and excellent selectivity over the CB1 subtype (>10 000×). Selected ligands 1d, 1e, 1g and 3l showing high CB2 binding affinity (Ki < 10 nM) were radiolabelled with fluorine-18 from chloropyridyl and alkyl tosylate precursors with good to high isolated radioactive yields (25-44%, non-decay corrected, at the end of synthesis). CB2-specific binding of the radioligand candidates [18F]-1d and [18F]-3l was assessed on rat spleen cryosections using in vitro autoradiography. The results warrant further in vivo evaluation of the tracer candidates as prospective CB2 PET-imaging agents.

Dosimetric impact of breast density in breast tomosynthesis: A comparative study.

A radiation dose survey has been undertaken involving 256 patients to investigate the dosimetric impact of breast tomosynthesis screening by employing different breast densities estimated by the Dance model, 50-50 breast model, and patient-specific density software: Volpara. Mean glandular dose (MGD) based on the Dance model provided the most realistic dose estimate with an average difference of -3.3 ± 4.8% from the patient-specific estimation. Average differences of -8.2 ± 6.5% and -7.3 ± 4.7% were observed for the 50-50 breast model and console MGD, respectively. We conclude that the Dance model should be used for dose calculations in radiation dose surveys and establishing diagnostic reference levels (DRL).

Direct Estimation of Voxel-Wise Neurotransmitter Response Maps From Dynamic PET Data.

Computational methods, such as the linear parametric neurotransmitter PET (lp-ntPET) method, have been developed to characterize the transient changes in radiotracer kinetics in the target tissue during endogenous neurotransmitter release. In this paper, we describe and evaluate a parametric reconstruction algorithm that uses an expectation maximization framework, along with the lp-ntPET model, to estimate the endogenous neurotransmitter response to stimuli directly from the measured PET data. Computer simulations showed that the proposed direct reconstruction method offers improved accuracy and precision for the estimated timing parameters of the neurotransmitter response at the voxel level ( td=1±2 min, for activation onset bias and standard deviation) compared with conventional post reconstruction modeling ( td=4±7 min). In addition, we applied the proposed direct parameter estimation methodology to a [11C]raclopride displacement study of an awake rat and generated parametric maps illustrating the magnitude of ligand displacement from striatum. Although the estimated parametric maps of activation magnitude obtained from both direct and post reconstruction methodologies suffered from false positive activations, the proposed direct reconstruction framework offered more reliable parametric maps when the activation onset parameter was constrained.

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.

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.

Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data.

Respiratory motion degrades the detection and quantification capabilities of PET/CT imaging. Moreover, mismatch between a fast helical CT image and a time-averaged PET image due to respiratory motion results in additional attenuation correction artifacts and inaccurate localization. Current motion compensation approaches typically have 3 limitations: the mismatch among respiration-gated PET images and the CT attenuation correction (CTAC) map can introduce artifacts in the gated PET reconstructions that can subsequently affect the accuracy of the motion estimation; sinogram-based correction approaches do not correct for intragate motion due to intracycle and intercycle breathing variations; and the mismatch between the PET motion compensation reference gate and the CT image can cause an additional CT-mismatch artifact. In this study, we established a motion correction framework to address these limitations. Methods: In the proposed framework, the combined emission-transmission reconstruction algorithm was used for phase-matched gated PET reconstructions to facilitate the motion model building. An event-by-event nonrigid respiratory motion compensation method with correlations between internal organ motion and external respiratory signals was used to correct both intracycle and intercycle breathing variations. The PET reference gate was automatically determined by a newly proposed CT-matching algorithm. We applied the new framework to 13 human datasets with 3 different radiotracers and 323 lesions and compared its performance with CTAC and non-attenuation correction (NAC) approaches. Validation using 4-dimensional CT was performed for one lung cancer dataset. Results: For the 10 18F-FDG studies, the proposed method outperformed (P < 0.006) both the CTAC and the NAC methods in terms of region-of-interest-based SUVmean, SUVmax, and SUV ratio improvements over no motion correction (SUVmean: 19.9% vs. 14.0% vs. 13.2%; SUVmax: 15.5% vs. 10.8% vs. 10.6%; SUV ratio: 24.1% vs. 17.6% vs. 16.2%, for the proposed, CTAC, and NAC methods, respectively). The proposed method increased SUV ratios over no motion correction for 94.4% of lesions, compared with 84.8% and 86.4% using the CTAC and NAC methods, respectively. For the 2 18F-fluoropropyl-(+)-dihydrotetrabenazine studies, the proposed method reduced the CT-mismatch artifacts in the lower lung where the CTAC approach failed and maintained the quantification accuracy of bone marrow where the NAC approach failed. For the 18F-FMISO study, the proposed method outperformed both the CTAC and the NAC methods in terms of motion estimation accuracy at 2 lung lesion locations. Conclusion: The proposed PET/CT respiratory event-by-event motion-correction framework with motion information derived from matched attenuation-corrected PET data provides image quality superior to that of the CTAC and NAC methods for multiple tracers.

The effect of isoflurane on 18F-FDG uptake in the rat brain: a fully conscious dynamic PET study using motion compensation.

BACKGROUND: In preclinical positron emission tomography (PET) studies an anaesthetic is used to ensure that the animal does not move during the scan. However, anaesthesia may have confounding effects on the drug or tracer kinetics under study, and the nature of these effects is usually not known. METHOD: We have implemented a protocol for tracking the rigid motion of the head of a fully conscious rat during a PET scan and performing a motion compensated list-mode reconstruction of the data. Using this technique we have conducted eight rat studies to investigate the effect of isoflurane on the uptake of 18F-FDG in the brain, by comparing conscious and unconscious scans. RESULTS: Our results indicate that isoflurane significantly decreases the whole brain uptake, as well as decreasing the relative regional FDG uptake in the cortex, diencephalon, and inferior colliculi, while increasing it in the vestibular nuclei. No statistically significant changes in FDG uptake were observed in the cerebellum and striata. CONCLUSION: The applied event-based motion compensation technique allowed for the investigation of the effect of isoflurane on FDG uptake in the rat brain using fully awake and unrestrained rats, scanned dynamically from the moment of injection. A significant effect of the anaesthesia was observed in various regions of the brain.

An iterative projection-based motion estimation and compensation scheme for head x-ray CT.

PURPOSE: Although current computed tomography (CT) systems can scan the head in a very short time, patient motion sometimes still induces artifacts. If motion occurs, one has to repeat the scan; to avoid motion, sedation or anesthesia is sometimes applied. METHODS: The authors propose a method to iteratively estimate and compensate this motion during the reconstruction. In every iteration, the rigid motion was estimated view-by-view and then used to update the system matrix. A multiresolution scheme was used to speed up the convergence of this joint estimation of the image and the motion of the subject. A final iterative reconstruction was performed with the last motion estimate. RESULTS: The method was evaluated on simulations, patient scans, and a phantom study. The quality of the reconstructed images was improved substantially after the compensation. In simulation and phantom studies, root-mean-square error was reduced and mean structural similarity was increased. In the patient studies, most of the motion blurring in the reconstructed images disappeared after the compensation. CONCLUSIONS: The proposed method effectively eliminated motion-induced artifacts in head CT scans. Since only measured raw data are needed for the motion estimation and compensation, the proposed method can be applied retrospectively to clinical helical CT scans affected by motion.

Optimising rigid motion compensation for small animal brain PET imaging.

Motion compensation (MC) in PET brain imaging of awake small animals is attracting increased attention in preclinical studies since it avoids the confounding effects of anaesthesia and enables behavioural tests during the scan. A popular MC technique is to use multiple external cameras to track the motion of the animal's head, which is assumed to be represented by the motion of a marker attached to its forehead. In this study we have explored several methods to improve the experimental setup and the reconstruction procedures of this method: optimising the camera-marker separation; improving the temporal synchronisation between the motion tracker measurements and the list-mode stream; post-acquisition smoothing and interpolation of the motion data; and list-mode reconstruction with appropriately selected subsets. These techniques have been tested and verified on measurements of a moving resolution phantom and brain scans of an awake rat. The proposed techniques improved the reconstructed spatial resolution of the phantom by 27% and of the rat brain by 14%. We suggest a set of optimal parameter values to use for awake animal PET studies and discuss the relative significance of each parameter choice.