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.
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.
复制标题
基于输入输出函数曲线单调性的定量18F-FDG PET研究中生成图像衍生输入函数的方法
DOI:
10.1097/mnm.0b013e32834f262e
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发表时间:
2012-04
影响因子:
1.5
通讯作者:
Shan B
中科院分区:
文献类型:
--
作者:
Zhou S;Chen K;Reiman EM;Li DM;Shan B
ObjectiveA 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. MethodsThe 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. ResultsThe 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. ConclusionThe method used in the present work is feasible and accurate.