Validation of a SIMIND Monte Carlo modelled gamma camera for Iodine-123 and Iodine-131 imaging

Morphis, Michaella; Staden, Johan A. van; Raan, Hanlie du; Ljungberg, Michael

doi:10.1016/j.heliyon.2021.e07196

Cited by 13 publications

(13 citation statements)

References 30 publications

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“…1) Validating the SPECT Simulation: We conducted our simulations with SIMIND. While SIMIND has been validated for multiple SPECT studies [33], [42], we further validated the accuracy of our simulation approach in the context of α-RPT SPECT. For this purpose, we compared the projection data obtained with our simulation approach to that obtained on an actual scanner.…”

Section: Evaluation Using Realistic Simulation Studiesmentioning

confidence: 88%

A Projection-Domain Low-Count Quantitative SPECT Method for ɑ-Particle-Emitting Radiopharmaceutical Therapy

Benabdallah

Abou

et al. 2023

IEEE Trans. Radiat. Plasma Med. Sci.

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Single-photon emission-computed tomography (SPECT) provides a mechanism to estimate regional isotope uptake in lesions and at-risk organs after administration of α-particle-emitting radiopharmaceutical therapies (α-RPTs). However, this estimation task is challenging due to the complex emission spectra, the very low number of detected counts (∼20 times lower than in conventional SPECT), the impact of stray-radiation-related noise at these low counts, and the multiple image-degrading processes in SPECT. The conventional reconstruction-based quantification methods are observed to be erroneous for α-RPT SPECT. To address these challenges, we developed a low-count quantitative SPECT (LC-QSPECT) method that directly estimates the regional activity uptake from the projection data (obviating the reconstruction step), compensates for stray-radiation-related noise, and accounts for the radioisotope and SPECT physics, including the isotope spectra, scatter, attenuation, and collimator-detector response, using a Monte Carlo-based approach. The method was validated in the context of 3-D SPECT with 223 Ra, a commonly used radionuclide for α-RPT. Validation was performed using both realistic simulation studies, including a virtual clinical trial, and synthetic and 3-D-printed anthropomorphic physical-phantom studies. Across all studies, the LC-QSPECT method yielded reliable regional-uptake estimates and outperformed the conventional ordered subset expectation-maximization (OSEM)-based

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Section: Evaluation Using Realistic Simulation Studiesmentioning

confidence: 88%

A Projection-Domain Low-Count Quantitative SPECT Method for ɑ-Particle-Emitting Radiopharmaceutical Therapy

Benabdallah

Abou

et al. 2023

IEEE Trans. Radiat. Plasma Med. Sci.

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“…The ground‐truth tracer distributions were used to generate realistic DaT‐SPECT projection data. A GE Discovery 670 scanner (GE Healthcare, Haifa, Israel) with a low‐energy high‐resolution collimator was simulated using SIMIND, a well‐validated Monte‐Carlo‐based simulation software 55,56 . The simulation modeled all relevant image‐degrading processes in SPECT, including photon attenuation and scatter, the finite extent of the collimator with a thickness of

3.5\nobreakspace \mathrm{cm}

, the finite energy resolution of 9.8% at 159 keV, and the intrinsic spatial resolution of

0.39\nobreakspace \mathrm{cm}

for the detector.…”

Section: Discussionmentioning

confidence: 99%

A tissue‐fraction estimation‐based segmentation method for quantitative dopamine transporter SPECT

Liu

Moon

et al. 2022

Medical Physics

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Background: Quantitative measures of dopamine transporter (DaT) uptake in caudate, putamen, and globus pallidus (GP) derived from dopamine transporter-single-photon emission computed tomography (DaT-SPECT) images have potential as biomarkers for measuring the severity of Parkinson's disease. Reliable quantification of this uptake requires accurate segmentation of the considered regions. However, segmentation of these regions from DaT-SPECT images is challenging, a major reason being partial-volume effects (PVEs) in SPECT. The PVEs arise from two sources, namely the limited system resolution and reconstruction of images over finite-sized voxel grids. The limited system resolution results in blurred boundaries of the different regions. The finite voxel size leads to TFEs, that is, voxels contain a mixture of regions. Thus, there is an important need for methods that can account for the PVEs, including the TFEs, and accurately segment the caudate, putamen, and GP, from DaT-SPECT images. Purpose: Design and objectively evaluate a fully automated tissue-fraction estimation-based segmentation method that segments the caudate, putamen, and GP from DaT-SPECT images. Methods: The proposed method estimates the posterior mean of the fractional volumes occupied by the caudate, putamen, and GP within each voxel of a three-dimensional DaT-SPECT image. The estimate is obtained by minimizing a cost function based on the binary cross-entropy loss between the true and estimated fractional volumes over a population of SPECT images, where the distribution of true fractional volumes is obtained from existing populations of clinical magnetic resonance images. The method is implemented using a supervised deep-learning-based approach. Results: Evaluations using clinically guided highly realistic simulation studies show that the proposed method accurately segmented the caudate, putamen, and GP with high mean Dice similarity coefficients of ∼ 0.80 and significantly outperformed (p < 0.01) all other considered segmentation methods. Further, an objective evaluation of the proposed method on the task of quantifying regional uptake shows that the method yielded reliable quantification with low ensemble normalized root mean square error (NRMSE) < 20% for all the considered regions. In particular, the method yielded an even lower ensemble NRMSE of ∼ 10% for the caudate and putamen. Conclusions: The proposed tissue-fraction estimation-based segmentation method for DaT-SPECT images demonstrated the ability to accurately segment the caudate, putamen, and GP, and reliably quantify the uptake within these regions. The results motivate further evaluation of the method with physical-phantom and patient studies.

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“…Projection data corresponding to each phantom realization was obtained using a SIMIND-simulated dual-head GE Discovery 670 SPECT system equipped with a high energy general purpose (HEGP) collimator. 28,29 Projections were acquired at 60 angular positions spanning 360 degrees. The imaging duration for each phantom was set to 30 minutes.…”

Section: Modeling the Spect Systemmentioning

confidence: 99%

WIN-PDQ: a Wiener-estimator-based projection-domain quantitative SPECT method that accounts for intra-regional uptake heterogeneity

Li,

Benabdallah,

Thorek

et al. 2024

Medical Imaging 2024: Physics of Medical Imaging

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Single photon emission computed tomography (SPECT) can enable the quantification of activity uptake in lesions and at-risk organs in α-particle-emitting radiopharmaceutical therapies (α-RPTs). However, this quantification is challenged by the extremely low detected photon counts, complicated isotope physics, and the image-degrading effects in α-RPT SPECT. Thus, strategies to optimize the SPECT system and protocol designs for the task of regional uptake quantification are much needed. Objectively performing this task-based optimization requires a reliable (accurate and precise) regional uptake quantification method. Conventional reconstruction-based quantification (RBQ) methods have been observed to be erroneous for α-RPT SPECT. Projection-domain quantification methods, which estimate regional uptake directly from SPECT projections, have demonstrated potential in providing reliable regional uptake estimates, but these methods assume constant uptake within the regions, an assumption that may not hold. To address these challenges, we propose Wiener INtegration Projection-Domain Quantification (WIN-PDQ), a Wiener-estimator-based projection-domain quantitative SPECT method. The method accounts for the heterogeneity within the regions of interest while estimating mean uptake. An earlystage evaluation of the method was conducted using 3D Monte Carlo-simulated SPECT of anthropomorphic phantoms with 223 Ra uptake and lumpy-model-based intra-regional uptake heterogeneity. In this evaluation with phantoms of varying mean regional uptake and intra-regional uptake heterogeneity, the WIN-PDQ method yielded ensemble unbiased estimates and significantly outperformed both reconstruction-based and previously proposed projection-domain quantification methods in terms of normalized root ensemble mean squared error. In conclusion, based on these preliminary findings, the proposed WIN-PDQ method is showing potential for estimating mean regional uptake in α-RPTs and towards enabling the objective task-based optimization of SPECT system and protocol designs.

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Validation of a SIMIND Monte Carlo modelled gamma camera for Iodine-123 and Iodine-131 imaging

Cited by 13 publications

References 30 publications

A Projection-Domain Low-Count Quantitative SPECT Method for ɑ-Particle-Emitting Radiopharmaceutical Therapy

A Projection-Domain Low-Count Quantitative SPECT Method for ɑ-Particle-Emitting Radiopharmaceutical Therapy

A tissue‐fraction estimation‐based segmentation method for quantitative dopamine transporter SPECT

WIN-PDQ: a Wiener-estimator-based projection-domain quantitative SPECT method that accounts for intra-regional uptake heterogeneity

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