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恶性脑肿瘤的2-[11C]胸腺嘧啶PET成像研究的动力学分析:房室模型研究与数学分析。

Kinetic analysis of 2-[11C]thymidine PET imaging studies of malignant brain tumors: compartmental model investigation and mathematical analysis.

作者信息

Wells Joanne M, Mankoff David A, Muzi Mark, O'Sullivan Finbarr, Eary Janet F, Spence Alexander M, Krohn Kenneth A

机构信息

University of Washington, USA.

出版信息

Mol Imaging. 2002 Jul;1(3):151-9. doi: 10.1162/15353500200202112.

Abstract

UNLABELLED

2-[11C]Thymidine (TdR), a PET tracer for cellular proliferation, may be advantageous for monitoring brain tumor progression and response to therapy. We previously described and validated a five-compartment model for thymidine incorporation into DNA in somatic tissues, but the effect of the blood-brain barrier on the transport of TdR and its metabolites necessitated further validation before it could be applied to brain tumors.

METHODS

We investigated the behavior of the model under conditions experienced in the normal brain and brain tumors, performed sensitivity and identifiability analysis to determine the ability of the model to estirmine whether it can distinguish between thymidine transport and retention.

RESULTS

Sensitivity and identifiability analysis suggested that the non-CO2 metabolite parameters could be fixed without significantly affecting thymidine parameter estimation. Simulations showed that K1t and KTdR could be estimated accurately (r = .97 and .98 for estimated vs. true parameters) with standard errors < 15%. The model was able to separate increased transport from increased retention associated with tumor proliferation.

CONCLUSION

Our model adequately describes normal brain and brain tumor kinetics for thymidine and its metabolites, and it can provide an estimate of the rate of cellular proliferation in brain tumors.

摘要

未标记

2-[11C]胸苷(TdR)是一种用于细胞增殖的正电子发射断层扫描(PET)示踪剂,可能有助于监测脑肿瘤的进展及对治疗的反应。我们之前描述并验证了一个用于胸苷掺入体细胞组织DNA的五室模型,但血脑屏障对TdR及其代谢物转运的影响使得在将其应用于脑肿瘤之前需要进一步验证。

方法

我们研究了该模型在正常脑和脑肿瘤所经历条件下的行为,进行了敏感性和可识别性分析,以确定模型估计胸苷转运和滞留的能力,判断其是否能够区分两者。

结果

敏感性和可识别性分析表明,非二氧化碳代谢物参数可以固定,而不会显著影响胸苷参数估计。模拟结果显示,K1t和KTdR能够被准确估计(估计参数与真实参数的r值分别为0.97和0.98),标准误差<15%。该模型能够区分与肿瘤增殖相关的转运增加和滞留增加。

结论

我们的模型充分描述了胸苷及其代谢物在正常脑和脑肿瘤中的动力学,并且能够提供脑肿瘤细胞增殖速率的估计值。

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