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用于蒙特卡罗模拟伽马相机的锝和镥定量参数的验证

Validation of Tc and Lu quantification parameters for a Monte Carlo modelled gamma camera.

作者信息

Di Domenico Giovanni, Di Biaso Simona, Longo Lorenzo, Turra Alessandro, Tonini Eugenia, Longo MariaConcetta, Uccelli Licia, Bartolomei Mirco

机构信息

Department of Physics and Earth Science, University of Ferrara, via Saragat 1, 44122 Ferrara, IT Italy.

Medical Physics Unit, University Hospital, 44124 Ferrara, IT Italy.

出版信息

EJNMMI Phys. 2023 Apr 8;10(1):27. doi: 10.1186/s40658-023-00547-6.

DOI:10.1186/s40658-023-00547-6
PMID:37029829
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10082889/
Abstract

PURPOSE

Monte Carlo (MC) simulation in Nuclear Medicine is a powerful tool for modeling many physical phenomena which are difficult to track or measure directly. MC simulation in SPECT/CT imaging is particularly suitable for optimizing the quantification of activity in a patient, and, consequently, the absorbed dose to each organ. To do so, validating MC results with real data acquired with gamma camera is mandatory. The aim of this study was the validation of the calibration factor (CF) and the recovery coefficient (RC) obtained with SIMIND Monte Carlo code for modeling a Siemens Symbia Intevo Excel SPECT-CT gamma camera to ensure optimal Tc and Lu SPECT quantification.

METHODS

Phantom experiments using Tc and Lu have been performed to measure spatial resolution and sensitivity, as well as to evaluate the CF and RC from acquired data. The geometries used for 2D planar imaging were (1) Petri dish and (2) capillary source while for 3D volumetric imaging were (3) a uniform filled cylinder phantom and (4) a Jaszczack phantom with spheres of different volumes. The experimental results have been compared with the results obtained from Monte Carlo simulations performed in the same geometries.

RESULTS

Comparison shows good accordance between simulated and experimental data. The measured planar spatial resolution was 8.3 mm for Tc and 11.8±0.6 mm for Lu. The corresponding data obtained by SIMIND for Tc was 7.8±0.1 mm, while for Lu was 12.4±0.4 mm. The CF was 110.1±5.5 cps/MBq for Technetium and 18.3±1.0 cps/MBq for Lutetium. The corresponding CF obtained by SIMIND for Tc was 107.3±0.3 cps/MBq, while for Lu 20.4±0.7 cps/MBq. Moreover, a complete curve RCs vs Volume (ml) both for Technetium and Lutetium was determined to correct the PVE for all volumes of clinical interest. In none of the cases, a RC coefficient equal to 100 was found.

CONCLUSIONS

The validation of quantification parameters shows that SIMIND can be used for simulating both gamma camera planar and SPECT images of Siemens Symbia Intevo using Tc and Lu radionuclides for different medical purposes and treatments.

摘要

目的

核医学中的蒙特卡罗(MC)模拟是一种强大的工具,可用于对许多难以直接追踪或测量的物理现象进行建模。SPECT/CT成像中的MC模拟特别适用于优化患者体内活性的定量分析,进而优化每个器官的吸收剂量。为此,必须用伽马相机采集的真实数据验证MC结果。本研究的目的是验证使用SIMIND蒙特卡罗代码获得的校准因子(CF)和恢复系数(RC),以对西门子Symbia Intevo Excel SPECT-CT伽马相机进行建模,确保锝和镥SPECT的最佳定量分析。

方法

使用锝和镥进行了体模实验,以测量空间分辨率和灵敏度,并从采集的数据中评估CF和RC。用于二维平面成像的几何形状为:(1)培养皿和(2)毛细管源;用于三维成像的几何形状为:(3)均匀填充的圆柱体模和(4)带有不同体积球体的Jaszczack体模。将实验结果与在相同几何形状下进行的蒙特卡罗模拟结果进行了比较。

结果

比较结果表明模拟数据与实验数据吻合良好。测得的平面空间分辨率,锝为8.3毫米,镥为11.8±0.6毫米。SIMIND获得的锝的相应数据为7.8±0.1毫米,镥为12.4±0.4毫米。锝的CF为110.1±5.5 cps/MBq,镥为18.3±1.0 cps/MBq。SIMIND获得的锝的相应CF为107.3±0.3 cps/MBq,镥为20.4±0.7 cps/MBq。此外,还确定了锝和镥的RC与体积(毫升)的完整曲线,以校正所有临床相关体积的部分容积效应(PVE)。在所有情况下,均未发现RC系数等于100。

结论

定量参数的验证表明,SIMIND可用于模拟西门子Symbia Intevo使用锝和镥放射性核素的伽马相机平面图像和SPECT图像,用于不同的医疗目的和治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/b3df225eafa1/40658_2023_547_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/f59adafed4ef/40658_2023_547_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/6d77620e3901/40658_2023_547_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/c94c2dbeefc9/40658_2023_547_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/fd68986623e9/40658_2023_547_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/1cbe67b6b066/40658_2023_547_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/fae3a7cd3abd/40658_2023_547_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/b8db87b7f4bd/40658_2023_547_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/b3df225eafa1/40658_2023_547_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/f59adafed4ef/40658_2023_547_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/6d77620e3901/40658_2023_547_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/c94c2dbeefc9/40658_2023_547_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/fd68986623e9/40658_2023_547_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/1cbe67b6b066/40658_2023_547_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/fae3a7cd3abd/40658_2023_547_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/b8db87b7f4bd/40658_2023_547_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8475/10082889/b3df225eafa1/40658_2023_547_Fig8_HTML.jpg

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