Influence of the SPECT calibration source position on the absorbed dose calculation for <sup>131</sup>I-NaI therapy using GATE simulations

Carvalho, S.M.; Costa, Alysson M.; Ramos, Celso Darío; Castelo, J.; Brunetto, S. Q.; Bonifacio, Daniel Alexandre Baptista

doi:10.1088/1361-6498/aad42a

Cited by 2 publications

(3 citation statements)

References 23 publications

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“…GATE/Geant4 tracks charged particles to the end of their range (Agostinelli et al 2003) unless a particle production threshold is properly set to avoid unnecessary computation time while maintaining the accuracy of the results (Costa et al 2017, Carvalho et al 2018. This threshold is defined as a range and is internally converted to an energy value according to the material and the particle.…”

Section: Simulations With the Gate Toolmentioning

confidence: 99%

“…The GATE DoseActor tool was used to calculate the number of interactions, the energy and the absorbed dose in each voxel of the micro-CT image of the bone sample. The DoseActor stores the required information in a 3D image (or matrix) with the same voxel size as the bone image (Carvalho et al 2018), enabling fast visualization of the dose distribution.…”

Section: Simulations With the Gate Toolmentioning

confidence: 99%

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A cell-based dosimetry model for radium-223 dichloride therapy using bone micro-CT images and GATE simulations

et al. 2020

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Dosimetry at the cellular level has outperformed macrodosimetry in terms of agreement with toxicity effects in clinical studies. This fact has encouraged dosimetry studies aiming to quantify the absorbed doses needed to reach radiotoxicity at the cellular level and to inform recommendations on the administration of radium-223. The aim of this work is to qualitatively and quantitatively evaluate the absorbed doses of radium-223 and the interactions of the doses at the cellular level. The analysis was performed by Monte Carlo simulations in GATE using micro-CT image of a mouse. Two physics lists available in the GATE code were tested. The influence of single and multiple scattering models on the absorbed dose distribution and number of particle hits was also studied. In addition, the fuzzy c-means clustering method was used for data segmentation. The segmentation method was suitable for these analyses, particularly given that it was unsupervised. There was no significant difference in the estimated absorbed dose between the two proposed physics lists. The absorbed dose values were not significantly influenced by scattering, although single scattering resulted in twice as many interactions as multiple scattering. The absorbed dose histogram at the voxel level shows heterogeneous absorbed dose values within each shell, but the observations from the graph of the medians were comparable to those in the literature. The interaction histogram indicates 104 events, although some voxels had no interactions with alpha particles. However, the voxels did not show absorbed doses capable of deterministic effects in the deepest part of the bone marrow. The absorbed dose distribution in images of mouse trabecular bone was compatible with simple geometric models, with absorbed doses capable of deterministic effects near the bone surface. The interaction distributions need to be correlated with in vivo studies for better interpretation.

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Section: Simulations With the Gate Toolmentioning

confidence: 99%

Section: Simulations With the Gate Toolmentioning

confidence: 99%

A cell-based dosimetry model for radium-223 dichloride therapy using bone micro-CT images and GATE simulations

et al. 2020

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“…The calibration factor is required to convert the measured count rates into absolute activity, or activity concentration per region [11]. System calibration is thus the foundation of image quantification, and several studies have aimed to improve calibration accuracy [4,7,12]- [14]. The guideline for quantitative 131 I SPECT, published by the committee on Medical Internal Radiation Dose (MIRD) [10], suggests performing calibration with a phantom that approximates the scatter and attenuation conditions in patient imaging, such as a water-filled tank [10].…”

Section: Jinst 14 P12010mentioning

confidence: 99%

Improved system calibration for ¹³¹I SPECT image quantification

et al. 2019

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A: Objective. SPECT system calibration plays an essential role in the accuracy of image quantification. In this work, an improved SPECT calibration method is proposed, considering the partial-volume effect (PVE) and the source calibration position. Methods. In the method presented, the calibration factor (S 0 ) is determined by an exponential fit of the calibration curve, which uses different threshold levels for determination of Volume of Interest. The calibration factor was calculated for images with High Count Density (HCD) and Low Count Density (LCD), and varying the source position within the phantom. To validate the calibration method, the calibration factors were used for absolute quantification of the total reference activities. Results. As expected, the sensitivity increases exponentially with volume, reaching a saturation level for volumes larger than the spatial resolution of the system, at which point the PVE becomes negligible. We obtained 13% accuracy in the image quantification using a centralized calibration source, which concurs with previous work. However, the calibration factors obtained with HCD images present the highest relative deviation (−18%) between the central and the most peripheral position, whereas for LCD images the deviation was only 3.7% for the same positions. Overall, deviations were below 9% for the calculated activities for each source position and using the calibration factor for the corresponding position. Conclusions. The proposed method has proven to be easier and faster to implement than other suggested procedures. SPECT quantification can be improved if the target position is considered in the calibration system procedure. K: Gamma camera, SPECT, PET PET/CT, coronary CT angiography (CTA); Medicalimage reconstruction methods and algorithms, computer-aided diagnosis 1Corresponding author.

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Influence of the SPECT calibration source position on the absorbed dose calculation for ¹³¹I-NaI therapy using GATE simulations

Cited by 2 publications

References 23 publications

A cell-based dosimetry model for radium-223 dichloride therapy using bone micro-CT images and GATE simulations

A cell-based dosimetry model for radium-223 dichloride therapy using bone micro-CT images and GATE simulations

Improved system calibration for ¹³¹I SPECT image quantification

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Influence of the SPECT calibration source position on the absorbed dose calculation for 131I-NaI therapy using GATE simulations

Cited by 2 publications

References 23 publications

A cell-based dosimetry model for radium-223 dichloride therapy using bone micro-CT images and GATE simulations

A cell-based dosimetry model for radium-223 dichloride therapy using bone micro-CT images and GATE simulations

Improved system calibration for 131I SPECT image quantification

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Influence of the SPECT calibration source position on the absorbed dose calculation for ¹³¹I-NaI therapy using GATE simulations

Improved system calibration for ¹³¹I SPECT image quantification