Development and validation of a Monte Carlo simulation tool for multi-pinhole SPECT

NEMA NU 1-2018 performance characterization and Monte Carlo model validation of the Cubresa Spark SiPM-based preclinical SPECT scanner

BACKGROUND

The Cubresa Spark is a novel benchtop silicon-photomultiplier (SiPM)-based preclinical SPECT system. SiPMs in SPECT significantly improve resolution and reduce detector size compared to preclinical cameras with photomultiplier tubes requiring highly magnifying collimators. The NEMA NU 1 Standard for Performance Measurements of Gamma Cameras provides methods that can be readily applied or extended to characterize preclinical cameras with minor modifications. The primary objective of this study is to characterize the Spark according to the NEMA NU 1-2018 standard to gain insight into its nuclear medicine imaging capabilities. The secondary objective is to validate a GATE Monte Carlo simulation model of the Spark for use in preclinical SPECT studies.

METHODS

NEMA NU 1-2018 guidelines were applied to characterize the Spark's intrinsic, system, and tomographic performance with single- and multi-pinhole collimators. Phantoms were fabricated according to NEMA specifications with deviations involving high-resolution modifications. GATE was utilized to model the detector head with the single-pinhole collimator, and NEMA measurements were employed to tune and validate the model. Single-pinhole and multi-pinhole SPECT data were reconstructed with the Software for Tomographic Image Reconstruction and HiSPECT, respectively.

RESULTS

The limiting intrinsic resolution was measured as 0.85 mm owing to a high-resolution SiPM array combined with a 3 mm-thick scintillation crystal. The average limiting tomographic resolution was 1.37 mm and 1.19 mm for the single- and multi-pinhole collimators, respectively, which have magnification factors near unity at the center of rotation. The maximum observed count rate was 15,400 cps, and planar sensitivities of 34 cps/MBq and 150 cps/MBq were measured at the center of rotation for the single- and multi-pinhole collimators, respectively. All simulated tests agreed well with measurement, where the most considerable deviations were below 7%.

CONCLUSIONS

NEMA NU 1-2018 standards determined that a SiPM detector mitigates the need for highly magnifying pinhole collimators while preserving detailed information in projection images. Measured and simulated NEMA results were highly comparable with differences on the order of a few percent, confirming simulation accuracy and validating the GATE model. Of the collimators initially provided with the Spark, the multi-pinhole collimator offers high resolution and sensitivity for organ-specific imaging of small animals, and the single-pinhole collimator enables high-resolution whole-body imaging of small animals.

The effects of mismatch between SPECT and CT images on quantitative activity estimation - A simulation study

BACKGROUND

Quantitative activity estimation is essential in nuclear medicine imaging. Mismatch between SPECT and CT images at the same imaging time point due to patient movement degrades accuracy in both diagnostic studies and target radionuclide therapy dosimetry. This work aims to study the mismatch effects between CT and SPECT data on attenuation correction (AC), volume-of-interest (VOI) delineation, and registration for activity estimation.

METHODS

Nine 4D XCAT phantoms were generated at 1, 24, and 144 h post In-111 Zevalin injection, varying in activity distributions, body sizes, and organ sizes. Realistic noisy SPECT projections were generated by an analytical projector and reconstructed with a quantitative OS-EM method. CT images were shifted, corresponding to SPECT images at each imaging time point, from -5 to 5 voxels and also according to a clinical reference. The effect of mismatched AC maps was evaluated using mismatched CT images for AC in SPECT reconstruction while VOIs were mapped out from matched CTs. The effect of mismatched VOI drawings was evaluated using mismatched CTs to map out target organs while using matched CTs for AC. The effect of mismatched CT images for registration was evaluated by registering sequential mismatched CTs to align corresponding SPECT images, with no AC and VOI mismatch. Bi-exponential curve fitting was performed to obtain time-integrated activity (TIA). Organ activity errors (%OAE) and TIA errors (%TIAE) were calculated.

RESULTS

According to the clinical reference, %OAE was larger for organs near ribs for AC effect. For VOI effect, %OAE was larger for small and low uptake organs. For registration effect, %TIAE were larger when mismatch existed in more numbers of SPECT/CT images, while no substantial difference was observed when using mismatched CT at different imaging time points as registration reference. %TIAE was highest for VOI, followed by registration and AC, e.g., 20.62%±8.61%, 9.33%±4.66% and 1.13%±0.90% respectively for kidneys.

CONCLUSIONS

The mismatch between CT and SPECT images poses a significant impact on the accuracy of quantitative activity estimation, attributed particularly from VOI delineation errors. It is recommended to perform registration between emission and transmission images at the same time point to ensure diagnostic and dosimetric accuracy.

Accurate Monte Carlo Modeling of Small-Animal Multi-Pinhole SPECT for Non-Standard Multi-Isotope Applications

Recent advances in preclinical SPECT instrumentation enable non-standard multi-isotope acquisitions at the edge of physical feasibility to improve efficiency of pharmaceutical research. Due to the variety of applications, optimization of imaging hardware, acquisition protocols and reconstruction algorithms is a central and recurring task. For this purpose, we developed a Monte Carlo simulation model of a preclinical state-of-the-art multi-pinhole SPECT system, the NanoSPECT/CT^PLUS, with emphasis on high accuracy for multi-isotope experiments operating near the system range limits. The GATE/ GEANT4 model included an accurate description of multi-pinhole collimators and all substructures of the detector back compartment. The readout electronics was modeled with a variety of signal processors partially extended to incorporate non-simplified measured response functions. The final model was able to predict energy spectra, planar images and tomographic reconstructions with high accuracy for both standard and non-standard multi-isotope experiments. Complex activity distributions could be reproduced for a wide range of noise levels and different modes of angular undersampling. Using the example of a dual-isotope triple-tracer experiment, the model has proven to be a powerful tool for protocol optimization and quantitative image correction at the performance range limits of multi-isotope multi-pinhole SPECT.

Advanced Monte Carlo simulations of emission tomography imaging systems with GATE

Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.

DeepAMO: a multi-slice, multi-view anthropomorphic model observer for visual detection tasks performed on volume images

Purpose: We propose a deep learning-based anthropomorphic model observer (DeepAMO) for image quality evaluation of multi-orientation, multi-slice image sets with respect to a clinically realistic 3D defect detection task. Approach: The DeepAMO is developed based on a hypothetical model of the decision process of a human reader performing a detection task using a 3D volume. The DeepAMO is comprised of three sequential stages: defect segmentation, defect confirmation (DC), and rating value inference. The input to the DeepAMO is a composite image, typical of that used to view 3D volumes in clinical practice. The output is a rating value designed to reproduce a human observer's defect detection performance. In stages 2 and 3, we propose: (1) a projection-based DC block that confirms defect presence in two 2D orthogonal orientations and (2) a calibration method that "learns" the mapping from the features of stage 2 to the distribution of observer ratings from the human observer rating data (thus modeling inter- or intraobserver variability) using a mixture density network. We implemented and evaluated the DeepAMO in the context of   Tc 99 m -DMSA SPECT imaging. A human observer study was conducted, with two medical imaging physics graduate students serving as observers. A 5 × 2 -fold cross-validation experiment was conducted to test the statistical equivalence in defect detection performance between the DeepAMO and the human observer. We also compared the performance of the DeepAMO to an unoptimized implementation of a scanning linear discriminant observer (SLDO). Results: The results show that the DeepAMO's and human observer's performances on unseen images were statistically equivalent with a margin of difference ( Δ AUC ) of 0.0426 at p < 0.05 , using 288 training images. A limited implementation of an SLDO had a substantially higher AUC (0.99) compared to the DeepAMO and human observer. Conclusion: The results show that the DeepAMO has the potential to reproduce the absolute performance, and not just the relative ranking of human observers on a clinically realistic defect detection task, and that building conceptual components of the human reading process into deep learning-based models can allow training of these models in settings where limited training images are available.

Current pediatric administered activity guidelines for 99m Tc-DMSA SPECT based on patient weight do not provide the same task-based image quality

PURPOSE

In the current clinical practice, administered activity (AA) for pediatric molecular imaging is often based on the North American expert consensus guidelines or the European Association of Nuclear Medicine dosage card, both of which were developed based on the best clinical practice. These guidelines were not formulated using a rigorous evaluation of diagnostic image quality (IQ) relative to AA. In the guidelines, AA is determined by a weight-based scaling of the adult AA, along with minimum and maximum AA constraints. In this study, we use task-based IQ assessment methods to rigorously evaluate the efficacy of weight-based scaling in equalizing IQ using a population of pediatric patients of different ages and body weights.

METHODS

A previously developed projection image database was used. We measured task-based IQ, with respect to the detection of a renal functional defect at six different AA levels (AA relative to the AA obtained from the guidelines). IQ was assessed using an anthropomorphic model observer. Receiver-operating characteristics (ROC) analysis was applied; the area under the ROC curve (AUC) served as a figure-of-merit for task performance. In addition, we investigated patient girth (circumference) as a potential improved predictor of the IQ.

RESULTS

The data demonstrate a monotonic and modestly saturating increase in AUC with increasing AA, indicating that defect detectability was limited by quantum noise and the effects of object variability were modest over the range of AA levels studied. The AA for a given value of the AUC increased with increasing age. The AUC vs AA plots for all the patient ages indicate that, for the current guidelines, the newborn and 10- and 15-yr phantoms had similar IQ for the same AA suggested by the North American expert consensus guidelines, but the 5- and 1-yr phantoms had lower IQ. The results also showed that girth has a stronger correlation with the needed AA to provide a constant AUC for ^99m Tc-DMSA renal SPECT.

CONCLUSIONS

The results suggest that (a) weight-based scaling is not sufficient to equalize task-based IQ for patients of different weights in pediatric ^99m Tc-DMSA renal SPECT; and (b) patient girth should be considered instead of weight in developing new administration guidelines for pediatric patients.

Development of computational small animal models and their applications in preclinical imaging and therapy research

The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

GATE based Monte Carlo simulation of planar scintigraphy to estimate the nodular dose in radioiodine therapy for autonomous thyroid adenoma

The recommended target dose in radioiodine therapy of solitary hyperfunctioning thyroid nodules is 300-400Gy and therefore higher than in other radiotherapies. This is due to the fact that an unknown, yet significant portion of the activity is stored in extranodular areas but is neglected in the calculatory dosimetry. We investigate the feasibility of determining the ratio of nodular and extranodular activity concentrations (uptakes) from post-therapeutically acquired planar scintigrams with Monte Carlo simulations in GATE. The geometry of a gamma camera with a high energy collimator was emulated in GATE (Version 5). A geometrical thyroid-neck phantom (GP) and the ICRP reference voxel phantoms "Adult Female" (AF, 16ml thyroid) and "Adult Male" (AM, 19ml thyroid) were used as source regions. Nodules of 1ml and 3ml volume were placed in the phantoms. For each phantom and each nodule 200 scintigraphic acquisitions were simulated. Uptake ratios of nodule and rest of thyroid ranging from 1 to 20 could be created by summation. Quantitative image analysis was performed by investigating the number of simulated counts in regions of interest (ROIs). ROIs were created by perpendicular projection of the phantom onto the camera plane to avoid a user dependant bias. The ratio of count densities in ROIs over the nodule and over the contralateral lobe, which should be least affected by nodular activity, was taken to be the best available measure for the uptake ratios. However, the predefined uptake ratios are underestimated by these count density ratios: For an uptake ratio of 20 the count ratios range from 4.5 (AF, 1ml nodule) to 15.3 (AM, 3ml nodule). Furthermore, the contralateral ROI is more strongly affected by nodular activity than expected: For an uptake ratio of 20 between nodule and rest of thyroid up to 29% of total counts in the ROI over the contralateral lobe are caused by decays in the nodule (AF 3 ml). In the case of the 1ml nodules this effect is smaller: 9-11% (AF) respectively 7-8% (AM). For each phantom, the dependency of count density ratios upon uptake ratios can be modeled well by both linear and quadratic regression (quadratic: r(2)>0.99), yielding sets of parameters which in reverse allow the computation of uptake ratios (and thus dose) from count density ratios. A single regression model obtained by fitting the data of all simulations simultaneously did not provide satisfactory results except for GP, while underestimating the true uptake ratios in AF and overestimating them in AM. The scintigraphic count density ratios depend upon the uptake ratios between nodule and rest of thyroid, upon their volumes, and their respective position in a non-trivial way. Further investigations are required to derive a comprehensive rule to calculate the uptake or dose ratios based on post-therapeutic scintigraphy.