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A method for generating image-derived input function in quantitative 18F-FDG PET study based on the monotonicity of the input and output function curve

机译:基于输入和输出函数曲线单调性的定量18F-FDG PET研究中生成图像输入函数的方法

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OBJECTIVE: A method of defining the image-derived input function (IDIF) was introduced and evaluated for the quantification of the regional cerebral metabolic rate of glucose in PET studies. METHODS: The voxels in the brain vasculature are extracted on the basis of the different monotonicities between the input and the output function curves. Time activity curves (TACs) of such voxels are averaged to obtain the uncorrected TAC of the brain vasculature. The IDIF was obtained from the raw TAC after correcting for the partial volume and spillover effects by an empirical formula in conjunction with a single blood sample and the TAC of the brain tissue. Data from 16 patients were used to test the proposed method. The Patlak approach is used to calculate the net fluoro-2-deoxyglucose clearance with plasma-derived input function and our generated IDIF, respectively. RESULTS: The net fluoro-2-deoxyglucose clearances calculated with the IDIF generated by our approach are not only highly correlated (correlation coefficients close to 1) to, but also highly comparable (regression slopes close to 1 and intercepts close to 0) with those calculated with plasma-derived input function. CONCLUSION: The method used in the present work is feasible and accurate.
机译:目的:介绍一种定义图像来源的输入函数(IDIF)的方法,并对其在PET研究中对葡萄糖的局部脑代谢率进行定量评估。方法:根据输入和输出函数曲线之间的不同单调性,提取脑血管中的体素。将此类体素的时间活动曲线(TAC)取平均值,以获得未校正的脑血管系统TAC。 IDIF是在通过经验公式结合单个血样和脑组织的TAC校正了部分体积和溢出效应后,从原始TAC中获得的。来自16位患者的数据用于测试该方法。 Patlak方法用于分别利用血浆来源的输入函数和我们生成的IDIF来计算氟-2-脱氧葡萄糖的净清除率。结果:用我们的方法生成的IDIF计算得到的氟-2-脱氧葡萄糖净清除率不仅与它们的相关性高(相关系数接近1),而且具有高度可比性(回归斜率接近1且截距接近0)。用血浆来源的输入函数计算。结论:本文方法​​是可行和准确的。

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