Frederic Boisson

NEMA NU 4-2008 validation and applications of the PET-SORTEO Monte Carlo simulations platform for the geometry of the Inveon PET preclinical scanner

Monte Carlo-based simulation of positron emission tomography (PET) data plays a key role in the design and optimization of data correction and processing methods. Our first aim was to adapt and configure the PET-SORTEO Monte Carlo simulation program for the geometry of the widely distributed Inveon PET preclinical scanner manufactured by Siemens Preclinical Solutions. The validation was carried out against actual measurements performed on the Inveon PET scanner at the Australian Nuclear Science and Technology Organisation in Australia and at the Brain & Mind Research Institute and by strictly following the NEMA NU 4-2008 standard. The comparison of simulated and experimental performance measurements included spatial resolution, sensitivity, scatter fraction and count rates, image quality and Derenzo phantom studies. Results showed that PET-SORTEO reliably reproduces the performances of this Inveon preclinical system. In addition, imaging studies showed that the PET-SORTEO simulation program provides raw data for the Inveon scanner that can be fully corrected and reconstructed using the same programs as for the actual data. All correction techniques (attenuation, scatter, randoms, dead-time, and normalization) can be applied on the simulated data leading to fully quantitative reconstructed images. In the second part of the study, we demonstrated its ability to generate fast and realistic biological studies. PET-SORTEO is a workable and reliable tool that can be used, in a classical way, to validate and/or optimize a single PET data processing step such as a reconstruction method. However, we demonstrated that by combining a realistic simulated biological study ([(11)C]Raclopride here) involving different condition groups, simulation allows one also to assess and optimize the data correction, reconstruction and data processing line flow as a whole, specifically for each biological study, which is our ultimate intent.

4D PET iterative deconvolution with spatiotemporal regularization for quantitative dynamic PET imaging

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.

Simulation-based optimisation of the PET data processing for Partial Saturation Approach protocols

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 sampling, 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.

Carbidopa Effect on 18F-FDOPA Uptake in Insulinoma: from Cell Culture to microPET Imaging

Patient premedication with carbidopa seems to improve the accuracy of 6-18F-fluoro-3,4-dihydroxy-l-phenylalanine (18F-FDOPA) PET for insulinoma diagnosis. However, the risk of PET false-negative results in the presence of carbidopa is a concern. Consequently, we aimed to evaluate the effect of carbidopa on 18F-FDOPA uptake in insulinoma β-cells and an insulinoma xenograft model in mice. Methods: 18F-FDOPA in vitro accumulation was assessed in the murine β-cell line RIN-m5F. In vivo small-animal PET experiments were performed on tumor-bearing nude mice after subcutaneous injection of RIN-m5F cells. Experiments were conducted with and without carbidopa pretreatment. Results: Incubation of RIN-m5F cells with 80 μM carbidopa did not significantly affect the cellular accumulation of 18F-FDOPA. Tumor xenografts were clearly detectable by small-animal PET in all cases. Insulinoma xenografts in carbidopa-treated mice showed significantly higher 18F-FDOPA uptake than those in nontreated mice. Regardless of carbidopa premedication, the xenografts were characterized by an early increase in 18F-FDOPA uptake and then a progressive reduction over time. Conclusion: Carbidopa did not influence in vitro 18F-FDOPA accumulation in RIN-m5F cells but improved insulinoma imaging in vivo. Our findings increase current knowledge about the 18F-FDOPA uptake profile of RIN-m5F cells and a related xenograft model. To our knowledge, the present work represents the first preclinical research specifically focused on insulinomas, with potential translational implications.

Motion-corrected planar projection imaging for awake and freely moving small animals

Awake and/or freely moving small animal single photon emission imaging allows the pseudo-continuous study of 125I-labelled macromolecule kinetics, which could not otherwise be performed with systems involving restraint or anaesthesia. 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 projections rather than the 3D volume), where the angular sampling depends on the observed motion. In this study, we hypothesise that the motion corrected planar projections estimated by reconstructing the 3D volume using an iterative reconstruction algorithm and integrating it along the projection path, will closely match the true planar distribution, regardless of the observed motion. We tested this hypothesis using 3D simulations based on a dual opposed detector system, where motion was modelled with 6 degrees of freedom (i.e. rigid body). We also investigated the quantitative accuracy of regional activity extracted from the geometric mean of opposing motion corrected planar projections. Results showed that it is feasible to accurately estimate motion-corrected projections for a wide range of motions around all 3 axes. Errors were dependent on the observed motion, as well as the surrounding activity of overlapping organs, but geometric mean estimates of regional activity were within 10% of expected values. We conclude that quantitatively accurate motion-free projections of the tracer distribution in a freely moving animal can be estimated from dual opposed detectors using MLEM-based motion correction.

Rigid motion correction of dual opposed planar projections in single photon imaging

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 sampling 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.

Simultaneous scanning of two mice in a small-animal PET scanner: a simulation-based assessment of the signal degradation.

In PET imaging, research groups have recently proposed different experimental set ups allowing multiple animals to be simultaneously imaged in a scanner in order to reduce the costs and increase the throughput. In those studies, the technical feasibility was demonstrated and the signal degradation caused by additional mice in the FOV characterized, however, the impact of the signal degradation on the outcome of a PET study has not yet been studied. Here we thoroughly investigated, using Monte Carlo simulated [18F]FDG and [11C]Raclopride PET studies, different experimental designs for whole-body and brain acquisitions of two mice and assessed the actual impact on the detection of biological variations as compared to a single-mouse setting. First, we extended the validation of the PET-SORTEO Monte Carlo simulation platform for the simultaneous simulation of two animals. Then, we designed [18F]FDG and [11C]Raclopride input mouse models for the simulation of realistic whole-body and brain PET studies. Simulated studies allowed us to accurately estimate the differences in detection between single- and dual-mode acquisition settings that are purely the result of having two animals in the FOV. Validation results showed that PET-SORTEO accurately reproduced the spatial resolution and noise degradations that were observed with actual dual phantom experiments. The simulated [18F]FDG whole-body study showed that the resolution loss due to the off-center positioning of the mice was the biggest contributing factor in signal degradation at the pixel level and a minimal inter-animal distance as well as the use of reconstruction methods with resolution modeling should be preferred. Dual mode acquisition did not have a major impact on ROI-based analysis except in situations where uptake values in organs from the same subject were compared. The simulated [11C]Raclopride study however showed that dual-mice imaging strongly reduced the sensitivity to variations when mice were positioned side-by-side while no sensitivity reduction was observed when they were facing each other. This is the first study showing the impact of different experimental designs for whole-body and brain acquisitions of two mice on the quality of the results using Monte Carlo simulated [18F]FDG and [11C]Raclopride PET studies.