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通过电化学建模对正电子发射断层扫描缺氧示踪剂摄取和组织氧合进行表征。

Characterization of positron emission tomography hypoxia tracer uptake and tissue oxygenation via electrochemical modeling.

机构信息

University of Wisconsin School of Medicine and Public Health, Department of Medical Physics, Madison, WI 53706, USA.

出版信息

Nucl Med Biol. 2011 Aug;38(6):771-80. doi: 10.1016/j.nucmedbio.2011.02.002. Epub 2011 May 5.

DOI:10.1016/j.nucmedbio.2011.02.002
PMID:21843774
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3157049/
Abstract

PURPOSE

Unique uptake and retention mechanisms of positron emission tomography (PET) hypoxia tracers make in vivo comparison between them challenging. Differences in imaged uptake of two common hypoxia radiotracers, [(61)Cu]Cu-ATSM and [(18)F]FMISO, were characterized via computational modeling to address these challenges.

MATERIALS AND METHODS

An electrochemical formalism describing bioreductive retention mechanisms of these tracers under steady-state conditions was adopted to relate time-averaged activity concentration to tissue partial oxygen tension (PO(2)), a common metric of hypoxia. Chemical equilibrium constants of product concentration to reactant concentration ratios were determined from free energy changes and reduction potentials of pertinent reactions reported in the literature. Resulting transformation functions between tracer uptake and PO(2) were compared against measured values in preclinical models. Additionally, calculated PO(2) distributions from imaged Cu-ATSM tracer activity concentrations of 12 head and neck squamous cell carcinoma (HNSCC) patients were validated against microelectrode PO(2) measurements in 69 HNSCC patients.

RESULTS

Both Cu-ASTM- and FMISO-modeled PO(2) transformation functions were in agreement with preclinical measured values within single-deviation confidence intervals. High correlation (r(2)=0.94, P<.05) was achieved between modeled PO(2) distributions and measured distributions in the patient populations. On average, microelectrode hypoxia thresholds (2.5 and 5.0 mmHg) corresponded to higher Cu-ATSM uptake [2.5 and 2.0 standardized uptake value (SUV)] and lower FMISO uptake (2.0 and 1.4 SUV). Uncertainties in the models were dominated by variations in the estimated specific activity and intracellular acidity.

CONCLUSIONS

Results indicated that the high dynamic range of Cu-ATSM uptake was representative of a narrow range of low oxygen tension whose values were dependent on microenvironment acidity, while FMISO uptake was representative of a wide range of PO(2) values that were independent of acidity. The models shed light on possible causes of these discrepancies, particularly as it pertains to image contrast, and may prove to be a useful methodology in quantifying relationships between other hypoxia tracers. Comprehensive and robust assessment of tumor hypoxia prior to as well as in response to therapy may be best provided by imaging of multiple hypoxia markers that provide complementary rather than interchangeable information.

摘要

目的

正电子发射断层扫描(PET)缺氧示踪剂具有独特的摄取和保留机制,使得它们之间的体内比较具有挑战性。通过计算建模来描述这两种常见的缺氧放射性示踪剂[(61)Cu]Cu-ATSM 和 [(18)F]FMISO 的摄取差异,以解决这些挑战。

材料和方法

采用描述这些示踪剂在稳态条件下生物还原保留机制的电化学公式,将时间平均的放射性示踪剂活性浓度与组织部分氧张力(PO2)相关联,PO2 是缺氧的常用指标。通过文献报道的相关反应的自由能变化和还原电位,确定产物浓度与反应物浓度比的化学平衡常数。将示踪剂摄取与 PO2 之间的转换函数与临床前模型中的测量值进行比较。此外,将从 12 例头颈部鳞状细胞癌(HNSCC)患者的 Cu-ATSM 示踪剂活性浓度成像中计算出的 PO2 分布与 69 例 HNSCC 患者的微电极 PO2 测量值进行验证。

结果

Cu-ATSM 和 FMISO 模型化的 PO2 转换函数都在单偏差置信区间内与临床前测量值一致。在患者群体中,模型化的 PO2 分布与测量分布之间实现了高度相关性(r2=0.94,P<.05)。平均而言,微电极缺氧阈值(2.5 和 5.0 mmHg)对应于更高的 Cu-ATSM 摄取[2.5 和 2.0 标准化摄取值(SUV)]和更低的 FMISO 摄取(2.0 和 1.4 SUV)。模型中的不确定性主要由估计的比活度和细胞内酸度的变化引起。

结论

结果表明,Cu-ATSM 摄取的高动态范围代表了一个狭窄的低氧张力范围,其值取决于微环境酸度,而 FMISO 摄取则代表了一个广泛的 PO2 值范围,与酸度无关。这些模型揭示了这些差异的可能原因,特别是就图像对比度而言,并且可能被证明是量化其他缺氧示踪剂之间关系的有用方法。在治疗前和治疗后全面和稳健地评估肿瘤缺氧,最好通过成像多个提供互补而非可互换信息的缺氧标志物来实现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/175bb1af2f1a/nihms293993f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/f030d83b3d4f/nihms293993f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/40aaa8b580ac/nihms293993f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/c646d0c15864/nihms293993f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/515a9a8d1bcb/nihms293993f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/175bb1af2f1a/nihms293993f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/f030d83b3d4f/nihms293993f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/40aaa8b580ac/nihms293993f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/c646d0c15864/nihms293993f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/515a9a8d1bcb/nihms293993f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16e2/3157049/175bb1af2f1a/nihms293993f5.jpg

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