TY - JOUR ID - 13664 TI - Effect of Bias in Contrast Agent Concentration Measurement on Estimated Pharmacokinetic Parameters in Brain Dynamic Contrast-Enhanced Magnetic Resonance Imaging Studies JO - Iranian Journal of Medical Physics JA - IJMP LA - en SN - AU - Dehkordi, Azimeh NV AD - Islamic Azad University Najafabad Branch, Najafabad, Iran Y1 - 2020 PY - 2020 VL - 17 IS - 3 SP - 142 EP - 152 KW - Dynamic Contrast-Enhanced Magnetic Resonance Imaging KW - Kinetic Analysis KW - Contrast Concentration Bias KW - MPE of PK Parameters DO - 10.22038/ijmp.2019.41400.1598 N2 - Introduction: Pharmacokinetic (PK) modeling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely applied in tumor diagnosis and treatment evaluation. Precision analysis of the estimated PK parameters is essential when they are used as a measure for therapy evaluation or treatment planning. In this study, the accuracy of PK parameters in brain DCE-MRI studies was quantified in relation to two major sources of error(including pre-contrast longitudinal-relaxation time, T1,0 and flip angle, α). Material and Methods: 3470 dynamic contrast-enhanced-curves were simulated using a wide variation of the PK parameters. The bias of contrast concentration due to the systematic biases in α and T1,0 was calculated and added to both contrast concentration and AIF profiles. Thereafter, the PK parameters were estimated for each simulated curve in the presence of different percentages of relative biases in α and T1,0. The mean percentage error (MPE) of PK parameters was then calculated for all simulated curves. Results: The results indicated that plasma volume(vp) was the most sensitive parameter to bias of contrast concentration, which may overestimate up to 700% in 10% coincidence relative bias in α and T1,0. The lowest MPE was related to the backward transfer constant (kep), which was ~2%-15% in 10% coincidence relative bias in each α and T1, 0. Conclusion: Utilization of a nested model selection technique, along with an accurate estimator, such as maximum-likelihood estimation, created a unique approach for investigating the effect of the bias in the concentration measurement to the estimated PK parameters without the addition of any extra biases to the parameters during the estimation. UR - https://ijmp.mums.ac.ir/article_13664.html L1 - https://ijmp.mums.ac.ir/article_13664_ca4bc25a67a9b52d85a698628cbce7d4.pdf ER -