Monte Carlo-based Scatter Correction Research Articles

Development of a Monte Carlo-based scatter correction method for total-body PET using the uEXPLORER PET/CT scanner

Objective. This study presents and evaluates a robust Monte Carlo-based scatter correction (SC) method for long axial field of view (FOV) and total-body positron emission tomography (PET) using the uEXPLORER total-body PET/CT scanner. Approach. Our algorithm utilizes the Monte Carlo (MC) tool SimSET to compute SC factors in between individual image reconstruction iterations within our in-house list-mode and time-of-flight-based image reconstruction framework. We also introduced a unique scatter scaling technique at the detector block-level for optimal estimation of the scatter contribution in each line of response. First image evaluations were derived from phantom data spanning the entire axial FOV along with image data from a human subject with a large body mass index. Data was evaluated based on qualitative inspections, and contrast recovery, background variability, residual scatter removal from cold regions, biases and axial uniformity were quantified and compared to non-scatter-corrected images. Main results. All reconstructed images demonstrated qualitative and quantitative improvements compared to non-scatter-corrected images: contrast recovery coefficients improved by up to 17.2% and background variability was reduced by up to 34.3%, and the residual lung error was between 1.26% and 2.08%. Low biases throughout the axial FOV indicate high quantitative accuracy and axial uniformity of the corrections. Up to 99% of residual activity in cold areas in the human subject was removed, and the reliability of the method was demonstrated in challenging body regions like in the proximity of a highly attenuating knee prosthesis. Significance. The MC SC method employed was demonstrated to be accurate and robust in TB-PET. The results of this study can serve as a benchmark for optimizing the quantitative performance of future SC techniques.

Monte Carlo-based scatter correction for the SMARTZOOM collimator

BackgroundMyocardial perfusion imaging is a commonly performed SPECT protocol and hence it would be beneficial if its scan duration could be shortened. For traditional gamma cameras, two developments have separately shown to allow for a shortened scan duration: (i) reconstructing with Monte Carlo-based scatter correction instead of dual-energy window scatter correction and (ii) acquiring projections with the SMARTZOOM collimator instead of a parallel-hole collimator. This study investigates which reduction in scan duration can be achieved when both methods are combined in a single system.ResultsThe SMARTZOOM collimator was implemented in a Monte Carlo-based reconstruction package and the implementation was validated through image quality phantom experiments. The potential for scan duration reduction was evaluated with a phantom configuration that is realistic for myocardial perfusion imaging. The original reconstruction quality was achieved in 76 ± 8% of the original scan duration when switching from dual-energy window scatter correction to Monte Carlo-based scatter correction. The original reconstruction quality was achieved in 56 ± 13% of the original scan duration when switching from the parallel-hole to the SMARTZOOM collimator. After combining both methods in a single system, the original reconstruction quality was achieved in 34 ± 7% of the original scan duration.ConclusionsMonte Carlo-based scatter correction combined with the SMARTZOOM collimator can further decrease the scan duration in myocardial perfusion imaging.

Fast quantitative reconstruction with focusing collimators for liver SPECT

BackgroundGeneration of a SPECT scan during procedure may aid in the optimization of treatments as liver radioembolization by offering image-guided dosimetry. This, however, requires both shortened acquisition times and fast quantitative reconstruction. Focusing collimators increase sensitivity and thus may speed up imaging. Monte Carlo-based iterative reconstruction has shown to provide quantitative results for parallel hole collimators but may be slow. The purpose of this work is to develop fast Monte Carlo-based reconstruction for focusing collimators and to evaluate the impact of reconstruction and collimator choice on quantitative accuracy of liver dosimetry by means of simulations.ResultsThe developed fast Monte Carlo simulator was found to accurately generate projections compared to a full Monte Carlo simulation, providing projections in several seconds instead of several days. Monte Carlo-based scatter correction was superior to other scatter correction methods in describing recovered activity and reached similar noise levels as dual-energy window scatter correction. Although truncation artifacts were present in the cone beam collimator (50 cm), the region inside the field of view (FOV) could be reconstructed without loss of accuracy. Provided the object to image is inside the FOV, the focusing collimator with 50 cm focal distance could retrieve the same noise levels as a parallel hole collimator in 68% of the total scanning time, the multifocal collimator in 73% of the time, and the 100-cm focal distance collimator in 84% of the time.ConclusionFocusing collimators combined with Monte Carlo-based reconstruction have the ability to enable quantitative imaging of the FOV in a significantly shorter timeframe. The proposed approach to the forward projector will additionally make it possible to reconstruct within minutes. These are crucial steps in moving toward real-time dosimetry during interventions.

Implementation of GPU accelerated SPECT reconstruction with Monte Carlo-based scatter correction.

Statistical SPECT reconstruction can be very time-consuming especially when compensations for collimator and detector response, attenuation, and scatter are included in the reconstruction. This work proposes an accelerated SPECT reconstruction algorithm based on graphics processing unit (GPU) processing. Ordered subset expectation maximization (OSEM) algorithm with CT-based attenuation modelling, depth-dependent Gaussian convolution-based collimator-detector response modelling, and Monte Carlo-based scatter compensation was implemented using OpenCL. The OpenCL implementation was compared against the existing multi-threaded OSEM implementation running on a central processing unit (CPU) in terms of scatter-to-primary ratios, standardized uptake values (SUVs), and processing speed using mathematical phantoms and clinical multi-bed bone SPECT/CT studies. The difference in scatter-to-primary ratios, visual appearance, and SUVs between GPU and CPU implementations was minor. On the other hand, at its best, the GPU implementation was noticed to be 24 times faster than the multi-threaded CPU version on a normal 128 × 128 matrix size 3 bed bone SPECT/CT data set when compensations for collimator and detector response, attenuation, and scatter were included. GPU SPECT reconstructions show great promise as an every day clinical reconstruction tool.

Abstract ID: 195 A fast Cone-Beam CT scatter correction method with Monte Carlo simulation using GPUMCD

GPUMCD, a fast GPU-based Monte Carlo transport code, was initially developed and validated for photon and electron dose calculations in radiation oncology. In this work, the code was adapted to rapidly simulate realistic X-ray Cone-Beam Computed Tomography (CBCT) projections, and in particular to estimate the scatter component of the signal. This estimate is thereafter filtered and used for scatter correction, which is especially important in a CBCT geometry. The signal generated by scattered photons on a 1028 × 768 detector was estimated with GPUMCD. The simulation geometry was derived from actual CBCT reconstructions (pelvis, thorax), with density and materials assigned to each voxel with a HU-electronic density calibration curve. Simulations were conducted on a NVIDIA GTX970m GPU with either 10 7 or 10 9 photons per projection. Recursive Gaussian filtering in projections with 10 7 photons was performed to assess the potential of faster simulations conducted with fewer photons. A simple Gaussian filter was used for the projection of 10 9 photons. The primary signal was obtained with deterministic ray-tracing, and normalized by the primary signal computed derived from the Monte Carlo simulation. Simulated projections with 10 7 photons were obtained in 3.5 s while the primary signal estimation took 0.2s. Recursive Gaussian filtering of projections was shown to be an effective way to reduce the simulation time by a factor 100 and preserve more complex scatter patterns. The simulation times reported here let envision a Monte Carlo-based scatter correction strategies in CBCT reconstruction.

Monte Carlo-based scatter correction considering the tailing effect of a CdTe detector for dual-isotope brain SPECT imaging

A Monte Carlo (MC)-based scatter correction method considering the tailing effect of a CdTe detector was developed for dual-isotope brain single-photon emission computed tomography (SPECT) imaging using technetium-99m (99mTc) and iodine-123 (123I), and its accuracy was validated by measuring phantoms. The tailing effect was modeled by convolutions of energy spectra obtained by geometry and tracking (GEANT) simulation with energy smoothing kernels. In our experimental phantom studies, quantitative accuracy and image contrast in the reconstructed image of dual-isotope-filled phantoms with our MC-based scatter correction method (Dual_SC) were compared with those of single-isotope-filled phantoms (Single_SC). The quantitative accuracy was evaluated by the percent error between the estimated activity concentration and true activity concentration. In our six-compartment phantom study with six different activity concentrations, the mean absolute percent errors of 99mTc for Single_SC and Dual_SC were 1.7% and 2.8%, respectively, while those of 123I for Single_SC and Dual_SC were 4.8% and 5.6%, respectively. In our striatal phantom study, the percent errors in the background regions for Single_SC and Dual_SC were less than 2% for both 99mTc and 123I. The image contrast was evaluated by the percent contrast of a cold or hot spot region to a background region. In our cold rod phantom study, the mean percent contrasts in the cold rod regions of 99mTc for Single_SC and Dual_SC were 66.2% and 65.0%, respectively, while those of 123I for Single_SC and Dual_SC were 59.3% and 61.6%, respectively. In our striatal phantom study, the percent contrasts in the striatal regions of 99mTc for Single_SC and Dual_SC were 56.1% and 56.1%, respectively, while those of 123I for Single_SC and Dual_SC were 39.8% and 40.0%, respectively. In conclusion, dual-isotope imaging with the CdTe-based brain SPECT system and our MC-based scatter correction method can provide comparable quantitative accuracy and image contrast to those of single-isotope imaging.

Impact of reconstruction parameters on quantitative I-131 SPECT

Radioiodine therapy using I-131 is widely used for treatment of thyroid disease or neuroendocrine tumors. Monitoring treatment by accurate dosimetry requires quantitative imaging. The high energy photons however render quantitative SPECT reconstruction challenging, potentially requiring accurate correction for scatter and collimator effects. The goal of this work is to assess the effectiveness of various correction methods on these effects using phantom studies.A SPECT/CT acquisition of the NEMA IEC body phantom was performed. Images were reconstructed using the following parameters: (1) without scatter correction, (2) with triple energy window (TEW) scatter correction and (3) with Monte Carlo-based scatter correction. For modelling the collimator-detector response (CDR), both (a) geometric Gaussian CDRs as well as (b) Monte Carlo simulated CDRs were compared. Quantitative accuracy, contrast to noise ratios and recovery coefficients were calculated, as well as the background variability and the residual count error in the lung insert.The Monte Carlo scatter corrected reconstruction method was shown to be intrinsically quantitative, requiring no experimentally acquired calibration factor. It resulted in a more accurate quantification of the background compartment activity density compared with TEW or no scatter correction. The quantification error relative to a dose calibrator derived measurement was found to be <1%,−26% and 33%, respectively. The adverse effects of partial volume were significantly smaller with the Monte Carlo simulated CDR correction compared with geometric Gaussian or no CDR modelling. Scatter correction showed a small effect on quantification of small volumes. When using a weighting factor, TEW correction was comparable to Monte Carlo reconstruction in all measured parameters, although this approach is clinically impractical since this factor may be patient dependent.Monte Carlo based scatter correction including accurately simulated CDR modelling is the most robust and reliable method to reconstruct accurate quantitative iodine-131 SPECT images.

GPU-accelerated Monte Carlo based scatter correction in brain PET/MR.

To develop and evaluate a fast and accurate Monte Carlo simulation (MCS) based scatter correction for PET/MR imaging, based on Geant4 using graphical processing units (GPUs). The GPU implementation by Bert et al. [1] including the photon tracking within a voxelized volume was extended with the modeling of the detection process in the Siemens MR-BrainPET. Using NVIDIA’s CUDA photon pairs undergo several kernel functions in parallel, from their generation according to the activity distribution up to their detection in the scanner. Subsequently, coincidences are sorted and stored in list-mode. The new GPU implementation (GeForce GTX690) was validated by comparison with Gate v6.2 on a single CPU (Intel Core i7, 3.4GHz), showing a speedup factor of 135. The use of multiple GPUs can further increase this acceleration. For Compton scatter correction the reconstructed emission image, the patient MR-derived attenuation map and a CT-derived attenuation template of the MR coils are used as input for the simulation. The resulting simulated projection data are scaled to the normalized measured projection data. Thus, the often unstable fit to the distribution tails, necessary for single scatter simulation (SSS)[2], is circumvented. The scaled simulated scatter distribution is then incorporated in the reconstruction. The proposed scatter correction methodology was evaluated and compared to the SSS approach using sphere phantom measurements. Finally, the effect on patient data was investigated. Phantom results suggest an improved contrast with our new MC-based scatter correction, especially for measurements including the MR coils, where the contrast recovery was improved by 10-14%. First patient images also show improved grey/white matter contrast. Table 1 Comparison of recovery coefficients after scatter correction based on MCS and SSS. MC-based scatter correction shows improved recovery coefficients for the hot spheres. Figure 1 Assessment of image quality according to NEMA NU 2-2007. Images show the phantom with a hot spheres/background ratio of 8:1 measured with MR head coils inside the BrainPET scanner. Figure 2 Comparison of reconstructed FDG images using the scatter estimate provided by the vendor’s SSS (left) and our MCS method (right). Images were reconstructed using the vendor provided 3D OP-OSEM algorithm with 2 subsets and 32 iterations. The new GPU-accelerated MCS allows for fast and accurate estimation of scattered coincidences in PET studies using the Siemens MR-BrainPET with a major speed-up compared to standard MCS and superior image quality compared with the standard correction based on SSS.

Half-time myocardial perfusion SPECT imaging with attenuation and Monte Carlo-based scatter correction

To test the potential of a new reconstruction algorithm with Monte Carlo-based scatter correction in half-time myocardial perfusion single-photon emission computed tomography (SPECT). The mathematical four-dimensional NURBS-based Cardiac-Torso phantom and the SIMIND Monte Carlo simulation package were used to simulate full-time and half-time SPECT projection data. The data were reconstructed using the standard ordered subset expectation maximization-based algorithm and the new Monte Carlo-based algorithm. Defect contrast, myocardium versus ventricle contrast and resolution were calculated. In addition to the simulation studies, full-time and half-time SPECT projection data of 30 patients were reconstructed with the standard and the new method. The patient data were qualitatively evaluated by four nuclear medicine experts on a scale from 1 (poor quality) to 5 (high quality). The new reconstruction method with half-time data produced higher contrast and better resolution in the simulations and also achieved higher qualitative scores in the patient study than the standard reconstruction with full-time data. Half-time myocardial perfusion imaging using the new reconstruction algorithm with Monte Carlo-based scatter correction produced images with superior quality when compared with full-time imaging with standard reconstruction.

Impact of image reconstruction on phase analysis of ECG-gated myocardial perfusion SPECT studies

Phase analysis (SyncTool) has been developed to assess left-ventricular (LV) dyssynchrony from gated myocardial perfusion single-photon emission computed tomography (GSPECT) studies. Conventionally, GSPECT data are reconstructed using filtered backprojection (FBP). This study is intended to determine the impact of various iterative reconstruction methods on SyncTool. Thirty consecutive patients, acquired using a Philips CardioMD system, were enrolled in this study. The GSPECT data were reconstructed using FBP, maximum likelihood expectation maximization (MLEM), MLEM with three-dimensional resolution recovery (Astonish), MLEM with Vantage attenuation correction (AC), and MLEM with Vantage AC and three-dimensional Monte Carlo-based scatter correction (ACSC), respectively. The reconstructed data were then submitted to SyncTool to measure LV dyssynchrony (phase standard deviation and histogram bandwidth). The paired t-test was used to compare the LV dyssynchrony indices given by MLEM, Astonish, AC, and ACSC, respectively, with those given by the FBP. No statistical significance was observed for any comparison between iterative reconstruction methods and the FBP. Reconstruction methods have insignificant impact on the LV dyssynchrony indices, indicating that the standard FBP reconstruction is sufficient for accurate phase analysis, supporting the widespread clinical use of SyncTool in measuring LV dyssynchrony.

Evaluation of 3D Monte Carlo-Based Scatter Correction for 201Tl Cardiac Perfusion SPECT

(201)Tl-Chloride ((201)Tl) is a myocardial perfusion SPECT agent with excellent biochemical properties commonly used for assessing tissue viability. However, cardiac (201)Tl SPECT images are severely degraded by photons scattered in the thorax. Accurate correction for this scatter is complicated by the nonuniform density and varied sizes of thoraxes, by the additional attenuation and scatter caused by female patients' breasts, and by the energy spectrum of (201)Tl. Monte Carlo simulation is a general and accurate method well suited to modeling this scatter. Statistical reconstruction that includes Monte Carlo modeling of scatter was compared with statistical reconstruction algorithms not corrected for scatter. In the ADS method, corrections for attenuation, detector response, and scatter (Monte Carlo-based) were implemented simultaneously via the dual-matrix ordered-subset expectation maximization algorithm with a Monte Carlo simulator as part of the forward projector. The ADS method was compared with the A method (ordered-subset expectation maximization with attenuation correction) and with the AD method (a method like the A method but with detector response modeling added). A dual-head SPECT system equipped with two (153)Gd scanning line sources was used for simultaneously acquiring transmission and emission data. Four clinically realistic phantom configurations (a large thorax and a small thorax, each with and without breasts) with a cardiac insert containing 2 cold defects were used to evaluate the proposed reconstruction algorithms. We compared the performance of the different algorithms in terms of noise properties, contrast-to-noise ratios, the contrast separability of perfusion defects, uniformity, and robustness to anatomic variations. The ADS method provided images with clearly better visual defect contrast than did the other methods. The contrasts achieved with the ADS method were 10%-24% higher than those achieved with the AD method and 11%-37% higher than those achieved with the A method. For a typical contrast level, the ADS method exhibited noise levels around 27% lower than the AD method and 34% lower than the A method. Compared with the other 2 algorithms, the ADS reconstructions were less sensitive to anatomic variations and had better image uniformity in the homogeneously perfused myocardium. Finally, we found that the improvements that can be achieved with Monte Carlo-based scatter correction are stronger for (201)Tl than for (99m)Tc imaging. Our results indicate that Monte Carlo-based scatter correction is suitable for (201)Tl cardiac imaging and that such correction simultaneously improves several image-quality metrics.