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The aim of this paper is to investigate the feasibility and limitations of activity-concentration estimation for 223 Ra using SPECT. Phantom measurements are performed using spheres (volumes 5.5 mL to 26.4 mL, concentrations 1.6 kBq mL -1 to 4.5 kBq mL -1 ). Furthermore, SPECT projections are simulated using the SIMIND Monte Carlo program for two geometries, one similar to the physical phantom and the other being an anthropomorphic phantom with added lesions (volumes 34 mL to 100 mL, concentrations 0.5 kBq mL -1 to 4 kBq mL -1 ). Medium-energy and high-energy collimators, 60 projections with 55 s per projection and a 20% energy window at 82 keV are employed. For the Monte Carlo simulated images, Poisson-distributed noise is added in ten noise realizations. Reconstruction is performed (OS-EM, 40 iterations, 6 subsets) employing compensation for attenuation, scatter, and collimator-detector response. The estimated concentrations in the anthropomorphic phantom are also corrected using recovery coefficients. Errors for the largest sphere in the physical phantom range from -25% to -34% for the medium-energy collimator and larger deviations for smaller spheres. Corresponding results for the high-energy collimator are -15% to -31%. The corresponding Monte Carlo simulations show standard deviations of a few percentage points. For the anthropomorphic phantom, before application of recovery coefficients the bias ranges from -16% to -46% (medium-energy collimator) and -10% to -28% (high-energy collimator), with standard deviations of 2% to 14% and 1% to 16%. After the application of recovery coefficients, the biases range from -3% to -35% (medium energy collimator) and from 0% to -18%. The errors decrease with increasing concentrations. Activity-concentration estimation of 223 Ra with SPECT is feasible, but problems with repeatability need to be further studied.

This paper presents the development and validation of a Monte Carlo-based singe photon emission computed tomography reconstruction program for parallel-hole collimation contained within the SIMIND Monte Carlo framework. The Monte Carlo code is used as an accurate forward-projector and is combined with a simplified back-projector to perform iterative tomographic reconstruction using the Maximum Likelihood Expectation Maximization and Ordered Subsets Expectation Maximization algorithms, together forming a program called SIMREC. The Monte Carlo simulation transforms the estimated source distribution directly from activity to counts in its projections. Hence, the reconstructed image is expressed in activity without reference to an external calibration. The program is tested using phantom measurements of spheres filled with 99m Tc, 177 Lu and 131 I placed in air and centrally and peripherally in a water-filled elliptical phantom. The feasibility of applying the reconstruction to patients is also demonstrated for a range of radiopharmaceuticals. The deviation in total activity in the spheres ranged between  -4.1% and 6.2% compared with the activity determined when preparing the phantom. The SIMREC program was found to be accurate with respect to activity estimation and to reconstruct visually acceptable images within a few hours when applied to patient examples.

Background: The aim was to investigate the noise and bias properties of quantitative 177Lu-SPECT with respect to the number of projection angles, and the number of subsets and iterations in the OS-EM reconstruction, for different total acquisition times. Methods: Experimental SPECT acquisition of six spheres in a NEMA body phantom filled with 177Lu was performed, using medium-energy collimators and 120 projections with 180 s per projection. Bootstrapping was applied to generate data sets representing acquisitions with 20 to 120 projections for 10 min, 20 min, and 40 min, with 32 noise realizations per setting. Monte Carlo simulations were performed of 177Lu-DOTA-TATE in an anthropomorphic computer phantom with three tumours (2.8 mL to 40.0 mL). Projections representing 24 h and 168 h post administration were simulated, each with 32 noise realizations. Images were reconstructed using OS-EM with compensation for attenuation, scatter, and distance-dependent resolution. The number of subsets and iterations were varied within a constrained range of the product number of iterations × number of projections ≤ 2400 . Volumes-of-interest were defined following the physical size of the spheres and tumours, the mean activity-concentrations estimated, and the absolute mean relative error and coefficient of variation (CV) over noise realizations calculated. Pareto fronts were established by analysis of CV versus mean relative error. Results: Points at the Pareto fronts with low CV and high mean error resulted from using a low number of subsets, whilst points at the Pareto fronts associated with high CV but low mean error resulted from reconstructions with a high number of subsets. The number of projection angles had limited impact. Conclusions: For accurate estimation of the 177Lu activity-concentration from SPECT images, the number of projection angles has limited importance, whilst the total acquisition time and the number of subsets and iterations are parameters of importance. [ABSTRACT FROM AUTHOR]

Background: Although the importance of quantitative SPECT has increased tremendously due to newly developed therapeutic radiopharmaceuticals, there are still no accreditation programs to harmonize SPECT imaging. Work is currently underway to develop an accreditation for quantitative 177Lu SPECT/CT. The aim of this study is to verify whether the positioning of the spheres within the phantom has an influence on the recovery and thus needs to be considered in SPECT harmonization. In addition, the effects of these recovery coefficients on a potential partial volume correction as well as absorbed-dose estimates are investigated. Methods: Using a low-dose CT of a SPECT/CT acquisition, a computerized version of the NEMA body phantom was created using a semi-automatic threshold-based method. Based on the mass-density map, the detector orbit, and the sphere centers, realistic SPECT acquisitions of all possible 720 sphere configurations of both the PET and the SPECT versions of the NEMA Body Phantom were generated using Monte Carlo simulations. SPECT reconstructions with different numbers of updates were performed without (CASToR) and with resolution modeling (STIR). Recovery coefficients were calculated for all permutations, reconstruction methods, and phantoms, and their dependence on the sphere positioning was investigated. Finally, the simulation-based findings were validated using SPECT/CT acquisitions of six different sphere configurations. Results: Our analysis shows that sphere positioning has a significant impact on the recovery for both of the reconstruction methods and the phantom type. Although resolution modeling resulted in significantly higher recovery, the relative variation in recovery within the 720 permutations was even larger. When examining the extreme values of the recovery, reconstructions without resolution modeling were influenced primarily by the sphere position, while with resolution modeling the volume of the two adjacent spheres had a larger influence. The SPECT measurements confirmed these observations, and the recovery curves showed good overall agreement with the simulated data. Conclusion: Our study shows that sphere positioning has a significant impact on the recovery obtained in NEMA sphere phantom measurements and should therefore be considered in a future SPECT accreditation. Furthermore, the single-measurement method normally performed for PVC should be reconsidered to account for the position dependency. [ABSTRACT FROM AUTHOR]

Background: A 3D printing grid-based method was developed to construct anthropomorphic phantoms with non-uniform activity distributions, to be used for evaluation of quantitative SPECT images. The aims were to characterize the grid-based method and to evaluate its capability to provide realistically shaped phantoms with non-uniform activity distributions. Methods: Characterization of the grid structures was performed by printing grid-filled spheres. Evaluation was performed by micro-CT imaging to investigate the printing accuracy and by studying the modulation contrast ( C M ) in SPECT images for 177Lu and 99mTc as a function of the grid fillable-volume fraction (FVF) determined from weighing. The grid-based technique was applied for the construction of two kidney phantoms and two thyroid phantoms, designed using templates from the XCAT digital phantoms. The kidneys were constructed with a hollow outer container shaped as cortex, an inner grid-based structure representing medulla and a solid section representing pelvis. The thyroids consisted of two lobes printed as grid-based structures, with void hot spots within the lobes. The phantoms were filled with solutions of 177Lu (kidneys) or 99mTc (thyroids) and imaged with SPECT. For verification, Monte Carlo simulations of SPECT imaging were performed for activity distributions corresponding to those of the printed phantoms. Measured and simulated SPECT images were compared qualitatively and quantitatively. Results: Micro-CT images showed that printing inaccuracies were mainly uniform across the grid. The relationships between the FVF from weighing and C M were found to be linear (r = 0.9995 and r = 0.9993 for 177Lu and 99mTc, respectively). The FVF-deviations from the design were up to 15% for thyroids and 4% for kidneys, mainly related to possibilities of cleaning after printing. Measured and simulated SPECT images of kidneys and thyroids exhibited similar activity distributions and quantitative comparisons agreed well, thus verifying the grid-based method. Conclusions: We find the grid-based technique useful for the provision of 3D printed, realistically shaped, phantoms with non-uniform activity distributions, which can be used for evaluation of different quantitative methods in SPECT imaging. [ABSTRACT FROM AUTHOR]

Purpose: A hybrid planar‐SPECT/CT method for tumor dosimetry in 177Lu‐DOTATATE therapy, applicable to datasets consisting of multiple conjugate‐view images and one SPECT/CT, is developed and evaluated. Methods: The imaging protocol includes conjugate‐view imaging at 1, 24, 96, and 168 h post infusion (p.i.) and a SPECT/CT acquisition 24 h p.i. The dosimetry method uses the planar images to estimate the shape of the time–activity concentration curve, which is then rescaled to absolute units using the SPECT‐derived activity concentration. The resulting time‐integrated activity concentration coefficient (TIACC) is used to calculate the tumor‐absorbed dose. Semiautomatic segmentation techniques are applied for tumor delineation in both planar and SPECT images, where the planar image segmentation is accomplished using an active‐rays‐based technique. The selection of tumors is done by visual inspection of planar and SPECT images and applying a set of criteria concerning the tumor visibility and possible interference from superimposed activity uptakes in the planar images. Five different strategies for determining values from planar regions of interest (ROIs), based on entire or partial ROIs, and with and without background correction, are evaluated. Evaluation is performed against a SPECT/CT‐based method on data from six patients where sequential conjugate‐view and SPECT/CT imaging have been performed in parallel and against ground truths in Monte Carlo simulated images. The patient data are also used to evaluate the interoperator variability and to assess the validity of the developed criteria for tumor selection. Results: For patient images, the hybrid method produces TIACCs that are on average 6% below those of the SPECT/CT only method, with standard deviations for the relative TIACC differences of 8%–11%. Simulations show that the hybrid and SPECT‐based methods estimate the TIACCs to within approximately 10% for tumors larger than around 10 ml, while for smaller tumors, all methods underestimate the TIACCs due to underestimations of the activity concentrations in the SPECT images. The planar image segmentation has a low operator dependence, with a median Dice similarity coefficient of 0.97 between operators. The adopted criteria for tumor selection manage to discriminate the tumors for which the absorbed‐dose deviations between the hybrid and SPECT methods are the highest. Conclusions: The hybrid method is found suitable for studies of tumor‐absorbed doses in radionuclide therapy, provided that selection criteria regarding the visibility and overlapping activities in the planar images are applied. [ABSTRACT FROM AUTHOR]

Background: Monte Carlo simulations provide accurate models of nuclear medicine imaging systems as they can properly account for the full physics of photon transport. The accuracy of the model included in the maximum-likelihood-expectation-maximization (ML-EM) reconstruction limits the overall accuracy of the reconstruction results. In this paper, we present a Monte Carlo-based ML-EM reconstruction method for pinhole single-photon emission computed tomography (SPECT) that has been incorporated into the SIMIND Monte Carlo program. The Monte Carlo-based model, which accounts for all of the physical and geometrical characteristics of the camera system, is used in the forward-projection step of the reconstruction, while a simpler model based on ray-tracing is used for back-projection. The aim of this work was to investigate the quantitative accuracy of this combination of forward- and back-projectors in the clinical pinhole camera GE Discovery NM 530c. Results: The total activity was estimated in Tc-filled spheres with volumes between 0.5 and 16 mL. The total sphere activity was generally overestimated but remained within 10% of the reference activity defined by the phantom preparation. The recovered activity converged towards the reference activity as the number of iterations increased. Furthermore, the recovery of the activity concentrations within the physical boundaries of the spheres increased with increasing sphere volume. Additionally, the Monte Carlo-based reconstruction enabled recovery of the true activity concentration in the myocardium of a cardiac phantom mounted in a torso phantom regardless of whether the torso was empty or water-filled. A qualitative comparison to data reconstructed using the clinical reconstruction algorithm showed that the two methods performed similarly, although the images reconstructed using the clinical software were more uniform due to the incorporation of noise regularization and post-filtration in that reconstruction technique. Conclusions: We developed a Monte Carlo-based reconstruction method for pinhole SPECT and evaluated it using phantom measurements. The combination of a Monte Carlo-based forward-projector and a simplified analytical ray-tracing back-projector produced quantitative images of acceptable image quality. No explicit calibration is necessary in this method since the forward-projector model maintains a relationship between the number of counts and activity. [ABSTRACT FROM AUTHOR]