Clinical & Medical Biochemistry

Abstrait

One Computation Method of the Constant K3/K4 in Three-Compartment Modeling of 13N-NH3 PET Images Tractor

Zhenyou Wang, Xueling Huang and Changxiu Song

This study aims to quantitatively analyze and compute the velocity constant of three-compartment modeling, which is based on 13NNH 3 PET images of human brain tumors. We selected the parietal lobe, cerebellum, frontal lobe, and the average of these three reference regions to analyze the transfer constant ratio, K3/K4, in three-compartment modeling. The study was based on the results of threecompartment modeling. Data sampling was performed for a left frontal lobe tumor, and simultaneously, data sampling was performed for three reference regions (including the parietal lobe, cerebellum, and right frontal lobe). The dynamic frames were 4 × 10 s, 7 × 20 s, 4 × 60 s, and 1 × 480 s. The parietal lobe, cerebellum, frontal lobe and the average of the three reference regions, as determined by the slopes of the fitted curves, are 1.6207, 1.5931, 1.5293, and 1.5803, respectively. The F-test values are 5552.4, 2943.6, 3756.8, and 5650.2, respectively; the average F-test value is the largest. And we have experiment with 11 ROIs with REF in this way, they are the line relative. All the R2 and P for all the fitted curves are almost 1, and all the P of all the fitted curves are almost 0. Moreover, the 95% confidence interval, which is based on the variance test, are enough short respectively. The comparison results show that the deviation and relative deviation for mean of REF are within the acceptable level. Thus, we have thought the K3/K4 as 0.5803; therefore, the transfer constant K4 is about 1.72 times that of K3 for the clinical use of 13N-NH3 PET tracer for brain tumors. The 13N-NH3 PET tracer is feasible for clinical use with brain tumors. The transfer constant, K4, is approximately two times of K3 in the three-compartment modeling of the parietal lobe, cerebellum, frontal lobe and the average of the three reference regions. This method is feasible and effective.