GATE: a simulation toolkit for PET and SPECT

Partial volume effect estimation and correction in the aortic vascular wall in PET imaging

We evaluated the impact of partial volume effect (PVE) in the assessment of arterial diseases with (18)FDG PET. An anthropomorphic digital phantom enabling the modeling of aorta related diseases like atherosclerosis and arteritis was used. Based on this phantom, we performed GATE Monte Carlo simulations to produce realistic PET images with a known organ segmentation and ground truth activity values. Images corresponding to 15 different activity-concentration ratios between the aortic wall and the blood and to 7 different wall thicknesses were generated. Using the PET images, we compared the theoretical wall-to-blood activity-concentration ratios (WBRs) with the measured WBRs obtained with five measurement methods: (1) measurement made by a physician (Expert), (2) automated measurement supposed to mimic the physician measurements (Max), (3) simple correction based on a recovery coefficient (Max-RC), (4) measurement based on an ideal VOI segmentation (Mean-VOI) and (5) measurement corrected for PVE using an ideal geometric transfer matrix (GTM) method. We found that Mean-VOI WBRs values were strongly affected by PVE. WBRs obtained by the physician measurement, by the Max method and by the Max-RC method were more accurate than WBRs obtained with the Mean-VOI approach. However Expert, Max and Max-RC WBRs strongly depended on the wall thickness. Only the GTM corrected WBRs did not depend on the wall thickness. Using the GTM method, we obtained more reproducible ratio values that could be compared across wall thickness. Yet, the feasibility of the implementation of a GTM-like method on real data remains to be studied.

Influence of detector pixel size, TOF resolution and DOI on image quality in MR-compatible whole-body PET

The optimization of a whole-body PET system remains a challenging task, as the imaging performance is influenced by a complex interaction of different design parameters. However, it is not always clear which parameters have the largest impact on image quality and are most eligible for optimization. To determine this, we need to be able to assess their influence on image quality. We performed Monte-Carlo simulations of a whole-body PET scanner to predict the influence on image quality of three detector parameters: the TOF resolution, the transverse pixel size and depth-of-interaction (DOI)-correction. The inner diameter of the PET scanner was 65 cm, small enough to allow physical integration into a simultaneous PET-MR system. Point sources were used to evaluate the influence of transverse pixel size and DOI-correction on spatial resolution as function of radial distance. To evaluate the influence on contrast recovery and pixel noise a cylindrical phantom of 35 cm diameter was used, representing a large patient. The phantom contained multiple hot lesions with 5 mm diameter. These lesions were placed at radial distances of 50, 100 and 150 mm from the center of the field-of-view, to be able to study the effects at different radial positions. The non-prewhitening (NPW) observer was used for objective analysis of the detectability of the hot lesions in the cylindrical phantom. Based on this analysis the NPW-SNR was used to quantify the relative improvements in image quality due to changes of the variable detector parameters. The image quality of a whole-body PET scanner can be improved significantly by reducing the transverse pixel size from 4 to 2.6 mm and improving the TOF resolution from 600 to 400 ps and further from 400 to 200 ps. Compared to pixel size, the TOF resolution has the larger potential to increase image quality for the simulated phantom. The introduction of two layer DOI-correction only leads to a modest improvement for the spheres at radial distance of 150 mm from the center of the transaxial FOV.

An efficient numerical tool for dose deposition prediction applied to synchrotron medical imaging and radiation therapy

Medical imaging and radiation therapy are widely used synchrotron-based techniques which have one thing in common: a significant dose delivery to typically biological samples. Among the ways to provide the experimenters with image guidance techniques indicating optimization strategies, Monte Carlo simulation has become the gold standard for accurately predicting radiation dose levels under specific irradiation conditions. A highly important hampering factor of this method is, however, its slow statistical convergence. A track length estimator (TLE) module has been coded and implemented for the first time in the open-source Monte Carlo code GATE/Geant4. Results obtained with the module and the procedures used to validate them are presented. A database of energy-absorption coefficients was also generated, which is used by the TLE calculations and is now also included in GATE/Geant4. The validation was carried out by comparing the TLE-simulated doses with experimental data in a synchrotron radiation computed tomography experiment. The TLE technique shows good agreement versus both experimental measurements and the results of a classical Monte Carlo simulation. Compared with the latter, it is possible to reach a pre-defined statistical uncertainty in about two to three orders of magnitude less time for complex geometries without loss of accuracy.

Monte Carlo simulation of PET images for injection dose optimization

When a patient is examined by positron emission tomography (PET), radiotracer dose amount (activity) has to be determined. However, the rules for activity correction according to patients' weight used nowadays do not correspond with practical experience. Very high image quality is achieved for slim patients, whereas noisy images are produced for obese patients. There is opportunity to modify the correction rule with the aim to equalize image quality within the broad spectrum of patients and to diminish radiation risk to slim patients, with special importance for children. We have built a model of a particular PET scanner and approximated human trunk, which is our region of interest, by a cylindrical model with segments of liver, outer adipose tissue, and the rest. We have performed Monte Carlo simulations of PET imaging using the GATE simulation package. Under reasonably simplifying assumptions and for special parameters, we have developed curves that recommend amount of injected activity based on body parameters to give PET images of constant quality, the quality being expressed in terms of noise equivalent counts. The dependence qualitatively differs from the rules used in clinical practice nowadays, and the results indicate potential for improvement.

Conceptual design and simulation study of an ROI-focused panel-PET scanner

Positron emission tomography (PET) is an important imaging modality for clincial use. Conventionally, the PET scanner is generally built to provide a roomy enough transverse field-of-view (FOV) for imaging most adults’ torsos. However, in many cases, the region-of-interest (ROI) for imaging is usually a small area inside the human body. Therefore, to fulfill a PET system which provides an FOV comparable in size to the target ROI seems appealing and more cost effective. Meanwhile, such a PET system has the potential for portable or bedside application with the reduced system size. In this work, we have investigated the feasibility of using dual-headed panel-detectors to build an ROI-focused PET scanner. A novel windowed list-mode ordered subset expectation maximization method was developed to perform the ROI image reconstruction. With this method, the ROI of the object can be reconstructed from the coincidences whose position determined by time-of-flight (TOF) measurements was inside the ROI. Monte Carlo simulation demonstrates the feasibility of detecting lesions not less than 1 cm in diameter, with a 300 ps full width at half maximum timing resolution. As a critical system performance, the impact of TOF information on image quality has been studied and the required TOF capability was assessed. With enhanced timing resolution, the distortions and artifacts were reduced effectively. The further improved TOF capability also shows a noticeable improvement of detection performance for low uptake lesions, as well as the recovery speed of lesion contrast, which is of practical significance in the lesion detection task.

Few-view single photon emission computed tomography (SPECT) reconstruction based on a blurred piecewise constant object model

A sparsity-exploiting algorithm intended for few-view single photon emission computed tomography (SPECT) reconstruction is proposed and characterized. The algorithm models the object as piecewise constant subject to a blurring operation. To validate that the algorithm closely approximates the true object in the noiseless case, projection data were generated from an object assuming this model and using the system matrix. Monte Carlo simulations were performed to provide more realistic data of a phantom with varying smoothness across the field of view and a cardiac phantom. Reconstructions were performed across a sweep of two primary design parameters. The results demonstrate that the algorithm recovers the object in a noiseless simulation case. While the algorithm assumes a specific blurring model, the results suggest that the algorithm may provide high reconstruction accuracy even when the object does not match the assumed blurring model. Generally, increased values of the blurring parameter and total variation weighting parameters reduced streaking artifacts, while decreasing spatial resolution. The proposed algorithm demonstrated higher correlation with respect to the true phantom compared to maximum-likelihood expectation maximization (MLEM) reconstructions. Images reconstructed with the proposed algorithm demonstrated reduced streaking artifacts when reconstructing from few views compared to MLEM. The proposed algorithm introduced patchy artifacts in some reconstructed images, depending on the noise level and the selected algorithm parameters. Overall, the results demonstrate preliminary feasibility of a sparsity-exploiting reconstruction algorithm which may be beneficial for few-view SPECT.

Least-squares dual characterization for ROI assessment in emission tomography

Our aim is to describe an original method for estimating the statistical properties of regions of interest (ROIs) in emission tomography. Drawn upon the works of Louis on the approximate inverse, we propose a dual formulation of the ROI estimation problem to derive the ROI activity and variance directly from the measured data without any image reconstruction. The method requires the definition of an ROI characteristic function that can be extracted from a co-registered morphological image. This characteristic function can be smoothed to optimize the resolution-variance tradeoff. An iterative procedure is detailed for the solution of the dual problem in the least-squares sense (least-squares dual (LSD) characterization), and a linear extrapolation scheme is described to compensate for sampling partial volume effect and reduce the estimation bias (LSD-ex). LSD and LSD-ex are compared with classical ROI estimation using pixel summation after image reconstruction and with Huesman's method. For this comparison, we used Monte Carlo simulations (GATE simulation tool) of 2D PET data of a Hoffman brain phantom containing three small uniform high-contrast ROIs and a large non-uniform low-contrast ROI. Our results show that the performances of LSD characterization are at least as good as those of the classical methods in terms of root mean square (RMS) error. For the three small tumor regions, LSD-ex allows a reduction in the estimation bias by up to 14%, resulting in a reduction in the RMS error of up to 8.5%, compared with the optimal classical estimation. For the large non-specific region, LSD using appropriate smoothing could intuitively and efficiently handle the resolution-variance tradeoff.

A wireless beta-microprobe based on pixelated silicon for in vivo brain studies in freely moving rats

The investigation of neurophysiological mechanisms underlying the functional specificity of brain regions requires the development of technologies that are well adjusted to in vivo studies in small animals. An exciting challenge remains the combination of brain imaging and behavioural studies, which associates molecular processes of neuronal communications to their related actions. A pixelated intracerebral probe (PIXSIC) presents a novel strategy using a submillimetric probe for beta(+) radiotracer detection based on a pixelated silicon diode that can be stereotaxically implanted in the brain region of interest. This fully autonomous detection system permits time-resolved high sensitivity measurements of radiotracers with additional imaging features in freely moving rats. An application-specific integrated circuit (ASIC) allows for parallel signal processing of each pixel and enables the wireless operation. All components of the detector were tested and characterized. The beta(+) sensitivity of the system was determined with the probe dipped into radiotracer solutions. Monte Carlo simulations served to validate the experimental values and assess the contribution of gamma noise. Preliminary implantation tests on anaesthetized rats proved PIXSIC's functionality in brain tissue. High spatial resolution allows for the visualization of radiotracer concentration in different brain regions with high temporal resolution.

Monte Carlo simulation of the basic features of the GE Millennium MG single photon emission computed tomography gamma camera

OBJECTIVE

To describe and validate the simulation of the basic features of GE Millennium MG gamma camera using the GATE Monte Carlo platform.

MATERIAL AND METHODS

Crystal size and thickness, parallel-hole collimation and a realistic energy acquisition window were simulated in the GATE platform. GATE results were compared to experimental data in the following imaging conditions: a point source of (99m)Tc at different positions during static imaging and tomographic acquisitions using two different energy windows. The accuracy between the events expected and detected by simulation was obtained with the Mann-Whitney-Wilcoxon test. Comparisons were made regarding the measurement of sensitivity and spatial resolution, static and tomographic. Simulated and experimental spatial resolutions for tomographic data were compared with the Kruskal-Wallis test to assess simulation accuracy for this parameter.

RESULTS

There was good agreement between simulated and experimental data. The number of decays expected when compared with the number of decays registered, showed small deviation (≤ 0.007%). The sensitivity comparisons between static acquisitions for different distances from source to collimator (1, 5, 10, 20, 30 cm) with energy windows of 126-154 keV and 130-158 keV showed differences of 4.4%, 5.5%, 4.2%, 5.5%, 4.5% and 5.4%, 6.3%, 6.3%, 5.8%, 5.3%, respectively. For the tomographic acquisitions, the mean differences were 7.5% and 9.8% for the energy window 126-154 keV and 130-158 keV. Comparison of simulated and experimental spatial resolutions for tomographic data showed no statistically significant differences with 95% confidence interval.

CONCLUSIONS

Adequate simulation of the system basic features using GATE Monte Carlo simulation platform was achieved and validated.

Design Optimization of a TOF, Breast PET Scanner

A dedicated breast positron emission tomography (PET) scanner with limited angle geometry can provide flexibility in detector placement around the patient as well as the ability to combine it with other imaging modalities. A primary challenge of a stationary limited angle scanner is the reduced image quality due to artifacts present in the reconstructed image leading to a loss in quantitative information. Previously it has been shown that using time-of-flight (TOF) information in image reconstruction can help reduce these image artifacts arising due to missing angular projections. Our goal in this work is to optimize the TOF, breast scanner design by performing studies for estimating image uniformity and lesion activity uptake as a function of system timing resolution, scanner angular coverage and shape. Our results show that (i) 1.5 × 1.5 × 15 mm³ lutetium oxy-orthosilicate (LSO) crystals provide a high spatial resolution and system sensitivity relative to clinical scanners, (ii) 2/3 angular coverage scanner design with TOF timing resolution less than 600 ps is appropriate for providing a tomographic image with fewer artifacts and good lesion uptake estimation relative to other partial ring designs studied in this work, (iii) a flat scanner design with 2/3 angular coverage is affected more by larger parallax error than a curved scanner geometry with the same angular coverage, but provides more uniform lesion contrast estimate over the imaging field-of-view (FOV), (iv) 2/3 angular coverage, flat, 300 ps TOF scanner design (for short, practical scan times of ≤ 5 mins per breast) provides similar precision of contrast recovery coefficient (CRC) values to a full curved, non-TOF scanner, and (v) employing depth-of-interaction (DOI) measuring detector and/or implementing resolution modeling (RM) in image reconstruction lead to improved and more uniform spatial resolution and lesion contrast over the whole FOV.

A tailored ML-EM algorithm for reconstruction of truncated projection data using few view angles

Dedicated cardiac single photon emission computed tomography (SPECT) systems have the advantage of high speed and sensitivity at no loss, or even a gain, in resolution. The potential drawbacks of these dedicated systems are data truncation by the small field of view (FOV) and the lack of view angles. Serious artifacts, including streaks outside the FOV and distortion in the FOV, are introduced to the reconstruction when using the traditional emission data maximum-likelihood expectation-maximization (ML-EM) algorithm to reconstruct images from the truncated data with a small number of views. In this note, we propose a tailored ML-EM algorithm to suppress the artifacts caused by data truncation and insufficient angular sampling by reducing the image updating step sizes for the pixels outside the FOV. As a consequence, the convergence speed for the pixels outside the FOV is decelerated. We applied the proposed algorithm to truncated analytical data, Monte Carlo simulation data and real emission data with different numbers of views. The computer simulation results show that the tailored ML-EM algorithm outperforms the conventional ML-EM algorithm in terms of streak artifacts and distortion suppression for reconstruction from truncated projection data with a small number of views.

Study of PET scanner designs using clinical metrics to optimize the scanner axial FOV and crystal thickness

The aim of this study is to understand the trade-off between crystal thickness and scanner axial field-of-view FOV (AFOV) for clinical PET imaging. Clinical scanner design has evolved towards 20-25 mm thick crystals and 16-22 cm long scanner AFOV, as well as time-of-flight (TOF) imaging. While Monte Carlo studies demonstrate that longer AFOV and thicker crystals will lead to higher scanner sensitivity, cost has prohibited the building of commercial scanners with >22 cm AFOV. In this study, we performed a series of system simulations to optimize the use of a given amount of crystal material by evaluating the impact on system sensitivity and noise equivalent counts (NEC), as well as image quality in terms of lesion detectability. We evaluated two crystal types (LSO and LaBr3) and fixed the total crystal volume used for each type (8.2 L of LSO and 17.1 L of LaBr3) while varying the crystal thickness and scanner AFOV. In addition, all imaging times were normalized so that the total scan time needed to scan a 100 cm long object with multiple bed positions was kept constant. Our results show that the highest NEC cm(-1) in a 35 cm diameter ×70 cm long line source cylinder is achieved for an LSO scanner with 10 mm long crystals and AFOV of 36 cm, while for LaBr3 scanners, the highest NEC cm(-1) is obtained with 20 mm long crystals and an AFOV of 38 cm. Lesion phantom simulations show that the best lesion detection performance is achieved in scanners with long AFOV (≥36 cm) and using thin crystals (≤10 mm of LSO and ≤20 mm of LaBr3). This is due to a combination of improved NEC, as well as improved lesion contrast estimation due to better spatial resolution in thinner crystals. Alternatively, for lesion detection performance similar to that achieved in standard clinical scanner designs, the long AFOV scanners can be used to reduce the total scan time without increasing the amount of crystal used in the scanner. In addition, for LaBr3 based scanners, the reduced lesion contrast relative to LSO based scanners requires improved timing resolution and longer scan times in order to achieve lesion detectability similar to that achieved in an LSO scanner with similar NEC cm(-1).

NEMA NU-4 performance evaluation of PETbox4, a high sensitivity dedicated PET preclinical tomograph

PETbox4 is a new, fully tomographic bench top PET scanner dedicated to high sensitivity and high resolution imaging of mice. This manuscript characterizes the performance of the prototype system using the National Electrical Manufacturers Association NU 4-2008 standards, including studies of sensitivity, spatial resolution, energy resolution, scatter fraction, count-rate performance and image quality. The PETbox4 performance is also compared with the performance of PETbox, a previous generation limited angle tomography system. PETbox4 consists of four opposing flat-panel type detectors arranged in a box-like geometry. Each panel is made by a 24 × 50 pixelated array of 1.82 × 1.82 × 7 mm bismuth germanate scintillation crystals with a crystal pitch of 1.90 mm. Each of these scintillation arrays is coupled to two Hamamatsu H8500 photomultiplier tubes via a glass light guide. Volumetric images for a 45 × 45 × 95 mm field of view (FOV) are reconstructed with a maximum likelihood expectation maximization algorithm incorporating a system model based on a parameterized detector response. With an energy window of 150-650 keV, the peak absolute sensitivity is approximately 18% at the center of FOV. The measured crystal energy resolution ranges from 13.5% to 48.3% full width at half maximum (FWHM), with a mean of 18.0%. The intrinsic detector spatial resolution is 1.5 mm FWHM in both transverse and axial directions. The reconstructed image spatial resolution for different locations in the FOV ranges from 1.32 to 1.93 mm, with an average of 1.46 mm. The peak noise equivalent count rate for the mouse-sized phantom is 35 kcps for a total activity of 1.5 MBq (40 µCi) and the scatter fraction is 28%. The standard deviation in the uniform region of the image quality phantom is 5.7%. The recovery coefficients range from 0.10 to 0.93. In comparison to the first generation two panel PETbox system, PETbox4 achieves substantial improvements on sensitivity and spatial resolution. The overall performance demonstrates that the PETbox4 scanner is suitable for producing high quality images for molecular imaging based biomedical research.

Sparse signal recovery methods for multiplexing PET detector readout

Nuclear medicine imaging detectors are commonly multiplexed to reduce the number of readout channels. Because the underlying detector signals have a sparse representation, sparse recovery methods such as compressed sensing may be used to develop new multiplexing schemes. Random methods may be used to create sensing matrices that satisfy the restricted isometry property. However, the restricted isometry property provides little guidance for developing multiplexing networks with good signal-to-noise recovery capability. In this work, we describe compressed sensing using a maximum likelihood framework and develop a new method for constructing multiplexing (sensing) matrices that can recover signals more accurately in a mean square error sense compared to sensing matrices constructed by random construction methods. Signals can then be recovered by maximum likelihood estimation constrained to the support recovered by either greedy l₀ iterative algorithms or l₁-norm minimization techniques. We show that this new method for constructing and decoding sensing matrices recovers signals with 4%-110% higher SNR than random Gaussian sensing matrices, up to 100% higher SNR than partial DCT sensing matrices 50%-2400% higher SNR than cross-strip multiplexing, and 22%-210% higher SNR than Anger multiplexing for photoelectric events.

A detector response function design in pinhole SPECT including geometrical calibration

Clinical single photon emission computed tomography (SPECT) equipped with pinhole collimators have a magnification factor that results in high spatial resolution images for small animal imaging. Using Monte Carlo simulations to model the acquisition process and the propagation of the photons from their point of emission to their detection point then integrating the model into an iterative reconstruction algorithm improves the signal-to-noise ratio, the contrast and the spatial resolution in the reconstructed images. However, pinhole SPECT systems are known to be very sensitive to geometrical misalignments. Geometrical misalignments are defined as the radial or axial shift of the collimator pinhole and/or twist and tilt of the detector heads and are introduced in the system each time the collimation device is changed (pinhole to parallel holes or vice versa). In this work, we present a flexible detector response function table (DRFT) design that takes into account the geometrical misalignments and avoids performing new Monte Carlo simulations for each exam in order to calculate a geometrical study-dependent system matrix. The utilization of the DRFT for the calculation of the system matrix speeds up its computation time by two orders of magnitude making it acceptable for preclinical and clinical applications.

A Monte Carlo investigation of the spatial resolution performance of a small-animal PET scanner designed for mouse brain imaging studies

Our laboratory has developed PET detectors with depth-encoding accuracy of ∼2 mm based on finely pixelated crystals with a tapered geometry, readout at both ends with position-sensitive avalanche photodiodes (PSAPDs). These detectors are currently being used in our laboratory to build a one-ring high resolution PET scanner for mouse brain imaging studies. Due to the inactive areas around the PSAPDs, large gaps exist between the detector modules which can degrade the image spatial resolution obtained using analytical reconstruction with filtered backprojection (FBP). In this work, the Geant4-based GATE Monte Carlo package was used to assist in determining whether gantry rotation was necessary and to assess the expected spatial resolution of the system. The following factors were investigated: rotating vs. static gantry modes with and without compensation of missing data using the discrete cosine transform (DCT) method, two levels of depth-encoding, and positron annihilation effects for (18)F. Our results indicate that while the static scanner produces poor quality FBP images with streak and ring artifacts, the image quality was greatly improved after compensation of missing data. The simulation indicates that the expected FWHM system spatial resolution is 0.70 ± 0.05 mm, which approaches the predicted limit of 0.5 mm FWHM due to positron range, photon non-colinearity and physical detector element size effects. We conclude that excellent reconstructed resolution without gantry rotation is possible even using FBP if the gaps are appropriately handled and that this design can approach the resolution limits set by positron annihilation physics.

Development and validation of RAYDOSE: a Geant4-based application for molecular radiotherapy

We developed and validated a Monte-Carlo-based application (RAYDOSE) to generate patient-specific 3D dose maps on the basis of pre-treatment imaging studies. A CT DICOM image is used to model patient geometry, while repeated PET scans are employed to assess radionuclide kinetics and distribution at the voxel level. In this work, we describe the structure of this application and present the tests performed to validate it against reference data and experiments. We used the spheres of a NEMA phantom to calculate S values and total doses. The comparison with reference data from OLINDA/EXM showed an agreement within 2% for a sphere size above 2.8 cm diameter. A custom heterogeneous phantom composed of several layers of Perspex and lung equivalent material was used to compare TLD measurements of gamma radiation from (131)I to Monte Carlo simulations. An agreement within 5% was found. RAYDOSE has been validated against reference data and experimental measurements and can be a useful multi-modality platform for treatment planning and research in MRT.

Normalized mean glandular dose computation from mammography using GATE: a validation study

Mean glandular dose (MGD) is the figure of merit to assess breast dose after a mammographic acquisition. The use of normalized MGD obtained from Monte Carlo computations with measured incident air kerma determines the MGD delivered to patients. The Geant4 Application for Tomographic Emission (GATE) toolkit is a modern Monte Carlo application specifically designed for medical imaging systems modelling. Although there is an increasing number of publications using GATE worldwide for a wide range of medical imaging and therapeutic applications, there is currently no means to obtain normalized MGD. In this work, the GATE toolkit is extended, through the development of two new modules, to provide normalized MGD information for compressed breast phantoms based on simple geometries. The normalized MGD values were validated against published work and provided results at half value layers lower than 0.3 and greater than 0.6 mmAl. In addition, the skin thickness and composition were considered. Normalized MGD was computed after substitution of the adipose layer surrounding the standard breast phantom with skin tissue and the relative difference is reported. Spectrum generation was facilitated by further development of previously published work by other authors. Validation of the new GATE extension showed good agreement with published data and can be used to assess breast dose from mammographic as well as more complex x-ray imaging techniques. Changing skin thickness and composition revealed substantial changes in normalized MGD specifically for compressed breast thickness different than 5 cm and a possible revision of the structure of the standard breast model may be necessary.

Simulation of light transport in scintillators based on 3D characterization of crystal surfaces

In the development of positron emission tomography (PET) detectors, understanding and optimizing scintillator light collection is critical for achieving high performance, particularly when the design incorporates depth-of-interaction (DOI) encoding or time-of-flight information. Monte-Carlo simulations play an important role in guiding research in detector designs and popular software such as GATE now include models of light transport in scintillators. Although current simulation toolkits are able to provide accurate models of perfectly polished surfaces, they do not successfully predict light output for other surface finishes, for example those often used in DOI-encoding detectors. The lack of accuracy of those models mainly originates from a simplified description of rough surfaces as an ensemble of micro-facets determined by the distribution of their normal, typically a gaussian distribution. The user can specify the standard deviation of this distribution, but this parameter does not provide a full description of the surface reflectance properties. We propose a different approach based on 3D measurements of the surface using atomic force microscopy. Polished and rough (unpolished) crystals were scanned to compute the surface reflectance properties. The angular distributions of reflectance and reflected rays were computed and stored in look-up tables (LUTs). The LUTs account for the effect of incidence angle and were integrated in a light transport model. Crystals of different sizes were simulated with and without reflector. The simulated maximum light output and the light output as a function of DOI showed very good agreement with experimental characterization of the crystals, indicating that our approach provides an accurate model of polished and rough surfaces and could be used to predict light collection in scintillators. This model is based on a true 3D representation of the surface, makes no assumption about the surface and provides insight on the optical behaviour of rough crystals that can play a critical role in optimizing the design of PET detectors. This approach is also compatible with existing simulation toolkits and next steps include the implementation in GATE.

Averaging and Metropolis iterations for positron emission tomography

Iterative positron emission tomography (PET) reconstruction computes projections between the voxel space and the lines of response (LOR) space, which are mathematically equivalent to the evaluation of multi-dimensional integrals. The dimension of the integration domain can be very high if scattering needs to be compensated. Monte Carlo (MC) quadrature is a straightforward method to approximate high-dimensional integrals. As the numbers of voxels and LORs can be in the order of hundred millions and the projection also depends on the measured object, the quadratures cannot be precomputed, but Monte Carlo simulation should take place on-the-fly during the iterative reconstruction process. This paper presents modifications of the maximum likelihood, expectation maximization (ML-EM) iteration scheme to reduce the reconstruction error due to the on-the-fly MC approximations of forward and back projections. If the MC sample locations are the same in every iteration step of the ML-EM scheme, then the approximation error will lead to a modified reconstruction result. However, when random estimates are statistically independent in different iteration steps, then the iteration may either diverge or fluctuate around the solution. Our goal is to increase the accuracy and the stability of the iterative solution while keeping the number of random samples and therefore the reconstruction time low. We first analyze the error behavior of ML-EM iteration with on-the-fly MC projections, then propose two solutions: averaging iteration and Metropolis iteration. Averaging iteration averages forward projection estimates during the iteration sequence. Metropolis iteration rejects those forward projection estimates that would compromise the reconstruction and also guarantees the unbiasedness of the tracer density estimate. We demonstrate that these techniques allow a significant reduction of the required number of samples and thus the reconstruction time. The proposed methods are built into the Teratomo system.

The performance of MLEM for dynamic imaging from simulated few-view, multi-pinhole SPECT

Stationary small-animal SPECT systems are being developed for rapid dynamic imaging from limited angular views. This paper quantified, through simulations, the performance of Maximum Likelihood Expectation Maximization (MLEM) for reconstructing a time-activity curve (TAC) with uptake duration of a few seconds from a stationary, three-camera multi-pinhole SPECT system. The study also quantified the benefits of a heuristic method of initializing the reconstruction with a prior image reconstructed from a conventional number of views, for example from data acquired during the late-study portion of the dynamic TAC. We refer to MLEM reconstruction initialized by a prior-image initial guess (IG) as MLEM ig . The effect of the prior-image initial guess on the depiction of contrast between two regions of a static phantom was quantified over a range of angular sampling schemes. A TAC was modeled from the experimentally measured uptake of 99m Tc-hexamethylpropyleneamine oxime (HMPAO) in the rat lung. The resulting time series of simulated images was quantitatively analyzed with respect to the accuracy of the estimated exponential washin and washout parameters. In both static and dynamic phantom studies, the prior-image initial guess improved the spatial depiction of the phantom, for example improved definition of the cylinder boundaries and more accurate quantification of relative contrast between cylinders. For example in the dynamic study, there was ~50% error in relative contrast for MLEM reconstructions compared to ~25-30% error for MLEM ig . In the static phantom study, the benefits of the initial guess decreased as the number of views increased. The prior-image initial guess introduced an additive offset in the reconstructed dynamic images, likely due to biases introduced by the prior image. MLEM initialized with a uniform initial guess yielded images that faithfully reproduced the time dependence of the simulated TAC; there were no statistically significant differences in the mean exponential washin/washout parameters estimated from MLEM reconstructions compared to the true values. Washout parameters estimated from MLEM ig reconstructions did not differ significantly from the true values, however the estimated washin parameter differed significantly from the true value in some cases. Overall, MLEM reconstruction from few views and a uniform initial guess accurately quantified the time dependance of the TAC while introducing errors in the spatial depiction of the object. Initializing the reconstruction with a late-study initial guess improved spatial accuracy while decreasing temporal accuracy in some cases.

Accelerating image reconstruction in dual-head PET system by GPU and symmetry properties

Positron emission tomography (PET) is an important imaging modality in both clinical usage and research studies. We have developed a compact high-sensitivity PET system that consisted of two large-area panel PET detector heads, which produce more than 224 million lines of response and thus request dramatic computational demands. In this work, we employed a state-of-the-art graphics processing unit (GPU), NVIDIA Tesla C2070, to yield an efficient reconstruction process. Our approaches ingeniously integrate the distinguished features of the symmetry properties of the imaging system and GPU architectures, including block/warp/thread assignments and effective memory usage, to accelerate the computations for ordered subset expectation maximization (OSEM) image reconstruction. The OSEM reconstruction algorithms were implemented employing both CPU-based and GPU-based codes, and their computational performance was quantitatively analyzed and compared. The results showed that the GPU-accelerated scheme can drastically reduce the reconstruction time and thus can largely expand the applicability of the dual-head PET system.

A self-normalization reconstruction technique for PET scans using the positron emission data

Positron emission tomography (PET) image quality in both clinical and preclinical environments highly depends on an accurate knowledge of the detector hardware to correct for image quality degrading effects like gain, temperature, and photon detection efficiency variations of the individual crystals. In conventional PET systems some of these variations are typically corrected using a dedicated calibration scan in which the scanner performance for a well-known activity source is measured. We propose an alternative method for estimating the relative sensitivity of each detector pixel using the coincidences as well as the singles emission data of each PET scan. The overall idea is to compare the total sum of all measured single photons before coincidence processing in each crystal with a steadily low-frequent distribution that can normally be expected. Both the estimated activity and the estimated detector sensitivity are simultaneously improved by using an extended iterative reconstruction scheme. This way we ensure the use of an optimal calibration correction (with the exception of a global factor) for each data set, even if the scanner performance has changed between two scans. Data measured with a preclinical PET scanner (HYPERIon-I) which uses analog silicon photomultipliers in combination with a custom-made ASIC shows a significant increase of image quality and homogeneity using the proposed method.

Modeling and Simulation of 4D PET-CT and PET-MR Images

The driving force in the research and development of new hybrid PET-CT/MR imaging scanners is the production of images with optimum quality, accuracy, and resolution. However, the acquisition process is limited by several factors. Key issues are the respiratory and cardiac motion artifacts that occur during an imaging session. In this article the necessary tools for modeling and simulation of realistic high-resolution four-dimensional PET-CT and PET-MR imaging data are described. Beyond the need for four-dimensional simulations, accurate modeling of the acquisition process can be included within the reconstruction algorithms assisting in the improvement of image quality and accuracy of estimation of physiologic parameters from four-dimensional hybrid PET imaging.

Emission guided radiation therapy for lung and prostate cancers: a feasibility study on a digital patient

PURPOSE

Accurate tumor tracking remains a challenge in current radiation therapy. Many strategies including image guided radiation therapy alleviate the problem to certain extents. The authors propose a new modality called emission guided radiation therapy (EGRT) to accurately and directly track the tumor based on its biological signature. This work is to demonstrate the feasibility of EGRT under two clinical scenarios using a 4D digital patient model.

METHODS

EGRT uses lines of response (LOR's) from positron emission events to direct beamlets of therapeutic radiation through the emission sites inside a tumor. This is accomplished by a radiation delivery system consisting of a Linac and positron emission tomography (PET) detectors on a fast rotating closed-ring gantry. During the treatment of radiotracer-administrated cancer patients, PET detectors collect LOR's from tumor uptake sites and the Linac responds in nearly real-time with beamlets of radiation along the same LOR paths. Moving tumors are therefore treated with a high targeting accuracy. Based on the EGRT concept, the authors design a treatment method with additional modulation algorithms including attenuation correction and an integrated boost scheme. Performance is evaluated using simulations of a lung tumor case with 3D motion and a prostate tumor case with setup errors. The emission process is simulated by Geant4 Application for Tomographic Emission package (GATE) and Linac dose delivery is simulated using a voxel-based Monte Carlo algorithm (VMC++).

RESULTS

In the lung case with attenuation correction, compared to a conventional helical treatment, EGRT achieves a 41% relative increase in dose to 95% of the gross tumor volume (GTV) and a 55% increase to 50% of the GTV. All dose distributions are normalized for the same dose to the lung. In the prostate case with the integrated boost and no setup error, EGRT yields a 19% and 55% relative dose increase to 95% and 50% of the GTV, respectively, when all methods are normalized for the same dose to the rectum. In the prostate case with integrated boost where setup error is present, EGRT contributes a 21% and 52% relative dose increase to 95% and 50% of the GTV, respectively.

CONCLUSIONS

As a new radiation therapy modality with inherent tumor tracking, EGRT has the potential to substantially improve targeting in radiation therapy in the presence of intrafractional and interfractional motion.

Dose point kernel simulation for monoenergetic electrons and radionuclides using Monte Carlo techniques

Monte Carlo (MC) simulation has been commonly used in the dose evaluation of radiation accidents and for medical purposes. The accuracy of simulated results is affected by the particle-tracking algorithm, cross-sectional database, random number generator and statistical error. The differences among MC simulation software packages must be validated. This study simulated the dose point kernel (DPK) and the cellular S-values of monoenergetic electrons ranging from 0.01 to 2 MeV and the radionuclides of (90)Y, (177)Lu and (103 m)Rh, using Fluktuierende Kaskade (FLUKA) and MC N-Particle Transport Code Version 5 (MCNP5). A 6-μm-radius cell model consisting of the cell surface, cytoplasm and cell nucleus was constructed for cellular S-value calculation. The mean absolute percentage errors (MAPEs) of the scaled DPKs, simulated using FLUKA and MCNP5, were 7.92, 9.64, 4.62, 3.71 and 3.84 % for 0.01, 0.1, 0.5, 1 and 2 MeV, respectively. For the three radionuclides, the MAPEs of the scaled DPKs were within 5 %. The maximum deviations of S(N←N), S(N←Cy) and S(N←CS) for the electron energy larger than 10 keV were 6.63, 6.77 and 5.24 %, respectively. The deviations for the self-absorbed S-values and cross-dose S-values of the three radionuclides were within 4 %. On the basis of the results of this study, it was concluded that the simulation results are consistent between FLUKA and MCNP5. However, there is a minor inconsistency for low energy range. The DPK and the cellular S-value should be used as the quality assurance tools before the MC simulation results are adopted as the gold standard.

Simulation studies on depth of interaction effect correction using a Monte Carlo computed system matrix for brain positron emission tomography

The parallax errors caused by a lack of depth-of-interaction (DOI) information often degrade reconstruction quality in positron emission tomography (PET). To reduce parallax errors, some PET systems employ multi-layered detectors to provide detailed DOI information, but this approach requires more complicated detector configurations and signal processing schemes. In this paper, we conduct simulation studies on an inherited DOI effect correction of a brain PET with a single-layered detector. For this purpose, we compare the maximum likelihood expectation maximization (MLEM) iterations using the Monte Carlo computed system matrix of the single-layered detector with filtered backprojection (FBP) reconstructions from projection data obtained from multi-layered detectors. We also investigate the benefits of multi-layered detectors in MLEM iterations using simulated data. The quantitative comparison in this paper shows that an inherited DOI effect correction of a Monte Carlo computed system matrix for a single-layered detector results in the associated MLEM iterations outperforming FBP reconstructions even for the case in which the projection data for FBPs are obtained from an octuple-layered detector. It also shows that use of multi-layered detectors provides better results overall in MLEM reconstruction, but the improvement seems not to be substantial enough to ignore the complexity and costs required for multi-layered detectors. Based on these results, we conclude that detailed DOI information from multi-layered detectors is favorable, but unnecessary in brain PET imaging, because the inherited DOI effect correction via a Monte Carlo computed system matrix for a single-layered detector is sufficient.

Comparison of different methods of incorporating respiratory motion for lung cancer tumor volume delineation on PET images: a simulation study

The interest of PET complementary information for the delineation of the target volume in radiotherapy of lung cancer is increasing. However, respiratory motion requires the determination of a functional internal target volume (ITV) on PET images for which several strategies have been proposed. The purpose of this study was the comparison of these strategies for taking into account respiratory motion and deriving the ITV: (1) adding fixed margins to the volume defined on a single binned image, (2) segmenting a motion averaged image and (3) considering the union of volumes delineated on binned frames. For this third strategy, binned frames were either non-corrected for motion, or corrected using two different methods: elastic registration or super resolution. The strategies' performances were assessed on realistic simulated datasets combining the NCAT phantom with a PET Philips GEMINI scanner model in GATE, and containing various configurations of tumor to background contrast, with both regular and irregular respiratory motion (with a range of motion amplitudes). The obtained ITVs' sensitivity (SE) and positive predictive value (PVE) with respect to the known true ITV were significantly higher (from 0.8 to 0.95) than all other techniques when using binned frames corrected for motion, independently of motion regularity, amplitude, or tumor to background contrast. Although the absolute difference was small and not always significant, images corrected using super resolution led to systematically better results than using elastic registration. The worst results were obtained when using the motion averaged image for SE (around 0.5-0.6) and using the margins added to a single frame for PPV (0.6-0.7), respectively. The best strategy to account for breathing motion for tumor ITV delineation in radiotherapy planning is to rely on the use of the union of volumes delineated on super resolution-corrected binned images.

Assessment of a three-dimensional line-of-response probability density function system matrix for PET

To achieve optimal PET image reconstruction through better system modeling, we developed a system matrix that is based on the probability density function for each line of response (LOR-PDF). The LOR-PDFs are grouped by LOR-to-detector incident angles to form a highly compact system matrix. The system matrix was implemented in the MOLAR list mode reconstruction algorithm for a small animal PET scanner. The impact of LOR-PDF on reconstructed image quality was assessed qualitatively as well as quantitatively in terms of contrast recovery coefficient (CRC) and coefficient of variance (COV), and its performance was compared with a fixed Gaussian (iso-Gaussian) line spread function. The LOR-PDFs of three coincidence signal emitting sources, (1) ideal positron emitter that emits perfect back-to-back γ rays (γγ) in air; (2) fluorine-18 (¹⁸F) nuclide in water; and (3) oxygen-15 (¹⁵O) nuclide in water, were derived, and assessed with simulated and experimental phantom data. The derived LOR-PDFs showed anisotropic and asymmetric characteristics dependent on LOR-detector angle, coincidence emitting source, and the medium, consistent with common PET physical principles. The comparison of the iso-Gaussian function and LOR-PDF showed that: (1) without positron range and acollinearity effects, the LOR-PDF achieved better or similar trade-offs of contrast recovery and noise for objects of 4 mm radius or larger, and this advantage extended to smaller objects (e.g. 2 mm radius sphere, 0.6 mm radius hot-rods) at higher iteration numbers; and (2) with positron range and acollinearity effects, the iso-Gaussian achieved similar or better resolution recovery depending on the significance of positron range effect. We conclude that the 3D LOR-PDF approach is an effective method to generate an accurate and compact system matrix. However, when used directly in expectation-maximization based list-mode iterative reconstruction algorithms such as MOLAR, its superiority is not clear. For this application, using an iso-Gaussian function in MOLAR is a simple but effective technique for PET reconstruction.

A dose point kernel database using GATE Monte Carlo simulation toolkit for nuclear medicine applications: comparison with other Monte Carlo codes

PURPOSE

GATE is a Monte Carlo simulation toolkit based on the Geant4 package, widely used for many medical physics applications, including SPECT and PET image simulation and more recently CT image simulation and patient dosimetry. The purpose of the current study was to calculate dose point kernels (DPKs) using GATE, compare them against reference data, and finally produce a complete dataset of the total DPKs for the most commonly used radionuclides in nuclear medicine.

METHODS

Patient-specific absorbed dose calculations can be carried out using Monte Carlo simulations. The latest version of GATE extends its applications to Radiotherapy and Dosimetry. Comparison of the proposed method for the generation of DPKs was performed for (a) monoenergetic electron sources, with energies ranging from 10 keV to 10 MeV, (b) beta emitting isotopes, e.g., (177)Lu, (90)Y, and (32)P, and (c) gamma emitting isotopes, e.g., (111)In, (131)I, (125)I, and (99m)Tc. Point isotropic sources were simulated at the center of a sphere phantom, and the absorbed dose was stored in concentric spherical shells around the source. Evaluation was performed with already published studies for different Monte Carlo codes namely MCNP, EGS, FLUKA, ETRAN, GEPTS, and PENELOPE. A complete dataset of total DPKs was generated for water (equivalent to soft tissue), bone, and lung. This dataset takes into account all the major components of radiation interactions for the selected isotopes, including the absorbed dose from emitted electrons, photons, and all secondary particles generated from the electromagnetic interactions.

RESULTS

GATE comparison provided reliable results in all cases (monoenergetic electrons, beta emitting isotopes, and photon emitting isotopes). The observed differences between GATE and other codes are less than 10% and comparable to the discrepancies observed among other packages. The produced DPKs are in very good agreement with the already published data, which allowed us to produce a unique DPKs dataset using GATE. The dataset contains the total DPKs for (67)Ga, (68)Ga, (90)Y, (99m)Tc, (111)In, (123)I, (124)I, (125)I, (131)I, (153)Sm, (177)Lu (186)Re, and (188)Re generated in water, bone, and lung.

CONCLUSIONS

In this study, the authors have checked GATE's reliability for absorbed dose calculation when transporting different kind of particles, which indicates its robustness for dosimetry applications. A novel dataset of DPKs is provided, which can be applied in patient-specific dosimetry using analytical point kernel convolution algorithms.

Adaptation and applications of a realistic digital phantom based on patient lung tumor trajectories

Digital phantoms continue to play a significant role in modeling and characterizing medical imaging. The currently available XCAT phantom incorporates both the flexibility of mathematical phantoms and the realistic nature of voxelized phantoms. This phantom generates images based on a regular breathing pattern and can include arbitrary lung tumor trajectories. In this work, we present an algorithm that modifies the current XCAT phantom to generate 4D imaging data based on irregular breathing. First, a parameter is added to the existing XCAT phantom to include any arbitrary tumor motion. This modification introduces the desired tumor motion but, comes at the cost of decoupled diaphragm, chest wall and lung motion. To remedy this problem diaphragm and chest wall motion is first modified based on initial tumor location and then input to the XCAT phantom. This generates a phantom with synchronized respiratory motion. Mapping of tumor motion trajectories to diaphragm and chest wall motion is done by adaptively calculating a scale factor based on tumor to lung contour distance. The distance is calculated by projecting the initial tumor location to lung edge contours characterized by quadratic polynomials. Data from ten patients were used to evaluate the accuracy between actual independent tumor location and the location obtained from the modified XCAT phantom. The RMSE and standard deviations for ten patients in x, y, and z directions are: (0.29 ± 0.04, 0.54 ± 0.17, and0.39 ± 0.06) mm. To demonstrate the utility of the phantom, we use the new phantom to simulate a 4DCT acquisition as well as a recently published method for phase sorting. The modified XCAT phantom can be used to generate more realistic imaging data for enhanced testing of algorithms for CT reconstruction, tumor tracking, and dose reconstruction.

Toward truly combined PET/CT imaging using PET detectors and photon counting CT with iterative reconstruction implementing physical detector response

PURPOSE

This paper intends to demonstrate the feasibility of truly combined PET/CT imaging and addresses some of the major challenges raised by this dual modality approach. A method is proposed to retrieve maximum accuracy out of limited resolution computed tomography (CT) scans acquired with positron emission tomography (PET) detectors.

METHODS

A PET/CT simulator was built using the LabPET™ detectors and front-end electronics. Acquisitions of energy-binned data sets were made using this low spatial resolution CT system in photon counting mode. To overcome the limitations of the filtered back-projection technique, an iterative reconstruction library was developed and tested for the counting mode CT. Construction of the system matrix is based on a preregistered raster scan from which the experimental detector response is obtained. PET data were obtained sequentially with CT in a conventional manner.

RESULTS

A meticulous description of the system geometry and misalignment corrections is imperative and was incorporated into the matrix definition to achieve good image quality. Using this method, no sinogram precorrection or interpolation is necessary and measured projections can be used as raw input data for the iterative reconstruction algorithm. Genuine dual modality PET/CT images of phantoms and animals were obtained for the first time using the same detection platform.

CONCLUSIONS

CT and fused PET/CT images show that LabPET™ detectors can be successfully used as individual X-ray photon counting devices for low-dose CT imaging of the anatomy in a molecular PET imaging context.

Simultaneous MR-compatible emission and transmission imaging for PET using time-of-flight information

Quantitative positron emission tomography (PET) imaging relies on accurate attenuation correction. Predicting attenuation values from magnetic resonance (MR) images is difficult because MR signals are related to proton density and relaxation properties of tissues. Here, we propose a method to derive the attenuation map from a transmission scan. An annulus transmission source is positioned inside the field-of-view of the PET scanner. First a blank scan is acquired. The patient is injected with FDG and placed inside the scanner. 511-keV photons coming from the patient and the transmission source are acquired simultaneously. Time-of-flight information is used to extract the coincident photons originating from the annulus. The blank and transmission data are compared in an iterative reconstruction method to derive the attenuation map. Simulations with a digital phantom were performed to validate the method. The reconstructed attenuation coefficients differ less than 5% in volumes of interest inside the lungs, bone, and soft tissue. When applying attenuation correction in the reconstruction of the emission data a standardized uptake value error smaller than 9% was obtained for all tissues. In conclusion, our method can reconstruct the attenuation map and the emission data from a simultaneous scan without prior knowledge about the anatomy or the attenuation coefficients of the tissues.

EduGATE - basic examples for educative purpose using the GATE simulation platform

EduGATE is a collection of basic examples to introduce students to the fundamental physical aspects of medical imaging devices. It is based on the GATE platform, which has received a wide acceptance in the field of simulating medical imaging devices including SPECT, PET, CT and also applications in radiation therapy. GATE can be configured by commands, which are, for the sake of simplicity, listed in a collection of one or more macro files to set up phantoms, multiple types of sources, detection device, and acquisition parameters. The aim of the EduGATE is to use all these helpful features of GATE to provide insights into the physics of medical imaging by means of a collection of very basic and simple GATE macros in connection with analysis programs based on ROOT, a framework for data processing. A graphical user interface to define a configuration is also included.

Development and evaluation of an improved quantitative (90)Y bremsstrahlung SPECT method

PURPOSE

Yttrium-90 ((90)Y) is one of the most commonly used radionuclides in targeted radionuclide therapy (TRT). Since it decays with essentially no gamma photon emissions, surrogate radionuclides (e.g., (111)In) or imaging agents (e.g., (99m)Tc MAA) are typically used for treatment planning. It would, however, be useful to image (90)Y directly in order to confirm that the distributions measured with these other radionuclides or agents are the same as for the (90)Y labeled agents. As a result, there has been a great deal of interest in quantitative imaging of (90)Y bremsstrahlung photons using single photon emission computed tomography (SPECT) imaging. The continuous and broad energy distribution of bremsstrahlung photons, however, imposes substantial challenges on accurate quantification of the activity distribution. The aim of this work was to develop and evaluate an improved quantitative (90)Y bremsstrahlung SPECT reconstruction method appropriate for these imaging applications.

METHODS

Accurate modeling of image degrading factors such as object attenuation and scatter and the collimator-detector response is essential to obtain quantitatively accurate images. All of the image degrading factors are energy dependent. Thus, the authors separated the modeling of the bremsstrahlung photons into multiple categories and energy ranges. To improve the accuracy, the authors used a bremsstrahlung energy spectrum previously estimated from experimental measurements and incorporated a model of the distance between (90)Y decay location and bremsstrahlung emission location into the SIMIND code used to generate the response functions and kernels used in the model. This improved Monte Carlo bremsstrahlung simulation was validated by comparison to experimentally measured projection data of a (90)Y line source. The authors validated the accuracy of the forward projection model for photons in the various categories and energy ranges using the validated Monte Carlo (MC) simulation method. The forward projection model was incorporated into an iterative ordered subsets-expectation maximization (OS-EM) reconstruction code to allow for quantitative SPECT reconstruction. The resulting code was validated using both a physical phantom experiment with spherical objects in a warm background and a realistic anatomical phantom simulation. In the physical phantom study, the authors evaluated the method in terms of quantitative accuracy of activity estimates in the spheres; in the simulation study, the authors evaluated the accuracy and precision of activity estimates from various organs and compared them to results from a previously proposed method.

RESULTS

The authors demonstrated excellent agreement between the experimental measurement and Monte Carlo simulation. In the XCAT phantom simulation, the proposed method achieved much better accuracy in the modeling (error in photon counts was -1.1 %) compared to a previously proposed method (errors were more than 20  %); the quantitative accuracy of activity estimates was excellent for all organs (errors were from -1.6 % to 11.9 %) and comparable to previously published results for (131)I using the same collimator.

CONCLUSIONS

The proposed (90)Y bremsstrahlung SPECT reconstruction method provided very accurate estimates of organ activities, with accuracies approaching those previously observed for (131)I. The method may be useful in verifying organ doses for targeted radionuclide therapy using (90)Y.

3D calculation of absorbed dose for 131I-targeted radiotherapy: a Monte Carlo study

Various methods, such as those developed by the Medical Internal Radiation Dosimetry (MIRD) Committee of the Society of Nuclear Medicine or employing dose point kernels, have been applied to the radiation dosimetry of (131)I radionuclide therapy. However, studies have not shown a strong relationship between tumour absorbed dose and its overall therapeutic response, probably due in part to inaccuracies in activity and dose estimation. In the current study, the GATE Monte Carlo computer code was used to facilitate voxel-level radiation dosimetry for organ activities measured in an (131)I-treated thyroid cancer patient. This approach allows incorporation of the size, shape and composition of organs (in the current study, in the Zubal anthropomorphic phantom) and intra-organ and intra-tumour inhomogeneities in the activity distributions. The total activities of the tumours and their heterogeneous distributions were measured from the SPECT images to calculate the dose maps. For investigating the effect of activity distribution on dose distribution, a hypothetical homogeneous distribution of the same total activity was considered in the tumours. It was observed that the tumour mean absorbed dose rates per unit cumulated activity were 0.65E-5 and 0.61E-5 mGY MBq(-1) s(-1) for the uniform and non-uniform distributions in the tumour, respectively, which do not differ considerably. However, the dose-volume histograms (DVH) show that the tumour non-uniform activity distribution decreases the absorbed dose to portions of the tumour volume. In such a case, it can be misleading to quote the mean or maximum absorbed dose, because overall response is likely limited by the tumour volume that receives low (i.e. non-cytocidal) doses. Three-dimensional radiation dosimetry, and calculation of tumour DVHs, may lead to the derivation of clinically reliable dose-response relationships and therefore may ultimately improve treatment planning as well as response assessment for radionuclide therapy.