Yokoi T, Kanno I, Iida H, Miura S, Uemura K
Department of Radiology and Nuclear Medicine, Research Institute for Brain and Blood Vessels-AKITA, Japan.
Kaku Igaku. 1990 Mar;27(3):273-7.
We developed a new technique for fast estimation of local cerebral blood flow and partition coefficient based on time integration of Kety-Schmidt equation. This technique has two advantages concerning statistical noise. Firstly, it does not need a Ci(T) image which contains high statistical noise because of low activity in brain. Secondly, statistical noise is minimized by time integration of Kety-Schmidt equation before multiplied by weighting function. The error analyses in flow and partition coefficient caused by statistical noise were performed using computer simulation, and dynamic PET human study using H(2)15O bolus injection. Both simulation and PET study indicated that uncertainties of flow and partition coefficient were confirmed to be lower in this technique than in the original weighted integration method.
我们基于Kety-Schmidt方程的时间积分开发了一种快速估计局部脑血流量和分配系数的新技术。该技术在统计噪声方面有两个优点。首先，它不需要包含由于脑部低活性而具有高统计噪声的Ci(T)图像。其次，在乘以加权函数之前，通过Kety-Schmidt方程的时间积分将统计噪声降至最低。使用计算机模拟以及使用H(2)15O团注注射的动态PET人体研究对由统计噪声引起的血流量和分配系数误差进行了分析。模拟和PET研究均表明，该技术中血流量和分配系数的不确定性经证实低于原始加权积分方法。
