ORCID Profile
0000-0002-0348-4878
Current Organisation
Centre National de la Recherche Scientifique
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Publisher: IOP Publishing
Date: 13-04-2017
Abstract: Awake and/or freely moving small animal single photon emission imaging allows the continuous study of molecules exhibiting slow kinetics without the need to restrain or anaesthetise the animals. Estimating motion free projections in freely moving small animal planar imaging can be considered as a limited angle tomography problem, except that we wish to estimate the 2D planar projections rather than the 3D volume, where the angular s ling in all three axes depends on the rotational motion of the animal. In this study, we hypothesise that the motion corrected planar projections estimated by reconstructing an estimate of the 3D volume using an iterative motion compensating reconstruction algorithm and integrating it along the projection path, will closely match the true, motion-less, planar distribution regardless of the object motion. We tested this hypothesis for the case of rigid motion using Monte-Carlo simulations and experimental phantom data based on a dual opposed detector system, where object motion was modelled with 6 degrees of freedom. In addition, we investigated the quantitative accuracy of the regional activity extracted from the geometric mean of opposing motion corrected planar projections. Results showed that it is feasible to estimate qualitatively accurate motion-corrected projections for a wide range of motions around all 3 axes. Errors in the geometric mean estimates of regional activity were relatively small and within 10% of expected true values. In addition, quantitative regional errors were dependent on the observed motion, as well as on the surrounding activity of overlapping organs. We conclude that both qualitatively and quantitatively accurate motion-free projections of the tracer distribution in a rigidly moving object can be estimated from dual opposed detectors using a correction approach within an iterative reconstruction framework and we expect this approach can be extended to the case of non-rigid motion.
Publisher: Society of Nuclear Medicine
Date: 05-09-2013
DOI: 10.2967/JNUMED.112.117572
Abstract: The Inveon small-animal SPECT system comes with several types of multipinhole collimator plates. We evaluate here the performance measurements of the Inveon SPECT system using 6 different collimators: 3 dedicated for mouse imaging and 3 for rat imaging. The measured performance parameters include the sensitivity, the spatial resolution using line sources, the ultra-micro Derenzo phantom, the recovery coefficient and the noise measurements using the National Electrical Manufacturers Association NU-4 image quality phantom, obtained with the 2 reconstruction algorithms available with the Inveon Acquisition Workplace, version 1.5-the 3-dimensional ordered-subset expectation maximization (3DOSEM) and the 3-dimensional maximum a posteriori (3DMAP). Further, the overall performance of the system is illustrated by an animal experiment. The results show that the Inveon SPECT scanner offers a spatial resolution, measured at the center of the field of view, ranging from 0.6 to 1 mm with the collimator plates dedicated to mouse imaging and from 1.2 to less than 2 mm with rat collimator plates. The system sensitivity varies from 29 to 404 cps/MBq for mouse collimators and from 53 to 175 cps/MBq for rat collimators. The image quality study showed that 3DMAP allows better noise reduction while preserving the recovery coefficient, compared with other regularization strategies such as the premature termination of the 3DOSEM reconstruction or 3DOSEM followed by gaussian filtering. The acquisition parameters, such as the collimator set and the radius of rotation, offer a wide range of possibilities to apply to a large number of biologic studies. However, special care must be taken because this increase in sensitivity can be offset by image degradation, such as image artifacts caused by projection overlap and statistical noise due to a higher number of iterations required for convergence. 3DMAP allowed better noise reduction while maintaining relatively constant recovery coefficients, as compared with other reconstruction strategies.
Publisher: Elsevier BV
Date: 09-2015
DOI: 10.1016/J.NEUROIMAGE.2015.06.029
Abstract: Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity.
Publisher: Elsevier BV
Date: 08-2014
DOI: 10.1016/J.NEUROIMAGE.2014.04.010
Abstract: Positron emission tomography (PET) with [(11)C]Raclopride is an important tool for studying dopamine D2 receptor expression in vivo. [(11)C]Raclopride PET binding experiments conducted using the Partial Saturation Approach (PSA) allow the estimation of receptor density (B(avail)) and the in vivo affinity appK(D). The PSA is a simple, single injection, single scan experimental protocol that does not require blood s ling, making it ideal for use in longitudinal studies. In this work, we generated a complete Monte Carlo simulated PET study involving two groups of scans, in between which a biological phenomenon was inferred (a 30% decrease of B(avail)), and used it in order to design an optimal data processing chain for the parameter estimation from PSA data. The impact of spatial smoothing, noise removal and image resolution recovery technique on the statistical detection was investigated in depth. We found that image resolution recovery using iterative deconvolution of the image with the system point spread function associated with temporal data denoising greatly improves the accuracy and the statistical reliability of detecting the imposed phenomenon. Before optimisation, the inferred B(avail) variation between the two groups was underestimated by 42% and detected in 66% of cases, while a false decrease of appK(D) by 13% was detected in more than 11% of cases. After optimisation, the calculated B(avail) variation was underestimated by only 3.7% and detected in 89% of cases, while a false slight increase of appK(D) by 3.7% was detected in only 2% of cases. We found during this investigation that it was essential to adjust a factor that accounts for difference in magnitude between the non-displaceable ligand concentrations measured in the target and in the reference regions, for different data processing pathways as this ratio was affected by different image resolutions.
Location: No location found
No related grants have been discovered for Frederic Boisson.