Comparison of three physiologically-based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging
Comparison of three physiologically-based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging
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DOI：
10.1002/jmri.21344
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发表时间：
2008-06-01
影响因子：
4.4
通讯作者：
Dewhirst, Mark W.
中科院分区：
文献类型：
--
作者：
Barboriak, Daniel P.;MacFall, James R.;Dewhirst, Mark W.
目的：比较三种基于生理的药代动力学(PBPK)模型预测Gd的性能。获得上矢状窦、大脑皮质和腰大肌的造影剂浓度-时间曲线。材料和方法：对已发表的3种全身PBPK模型进行改进，以预测正常组织中的造影剂浓度-时间曲线。这些模型在建模器官的数量和隔室的总数上有所不同，并被指定为“混合良好”、“延迟”和“分散”模型。使用10例多形性胶质母细胞瘤患者1.5T和5例肝转移瘤患者3.0T的动态增强MR灌注成像数据，研究三种模型预测Gd-CTC的适用性。结果：离散模型在SSs(P<；0.0001)和大脑皮层(P<；0.0001)中的拟合效果好于延迟模型，在腰大肌中的拟合效果好于混合模型(P<；0.005)。在这三个位置中，没有一个模型比弥散模型拟合得更好。结论：在这项评估中，弥散模型对动态增强(DCE)磁共振成像获得的Gd-CTCs的预测是最稳健的。这代表了开发PBPK模型的第一步，该模型可用于在适合动态MRI应用的时间分辨率下预测Gd-CTCs。
Purpose: To compare the performance of three physiologically-based pharmacokinetic (PBPK) models for predicting gadolinium. contrast agent concentration-time curves (Gd-CTCs) obtained in superior sagittal sinus (SSS), cerebral cortex, and psoas muscle.Materials and Methods: Three published whole-body PBPK models were modified to predict Gd-CTCs in normal-appearing tissue. The models differed in the number of organs modeled and total number of compartments, and were designated as the "well-mixed," "delay," and "dispersion" models. The suitability of the three models to predict Gd-CTC was studied using data from dynamic contrast-enhanced MR perfusion imaging obtained at 1.5T from 10 patients with glioblastoma multiforme and at 3.0T from five patients with liver metastases.Results: The dispersion model produced better fits than the delay model in the SSS (P < 0.0001) and cerebral cortex (P < 0.0001), and better fits than the well-mixed model in psoas muscle (P < 0.005). No model produced better fits than the dispersion model at any of the three locations.Conclusion: In this evaluation, the dispersion model was most robust for prediction of Gd-CTCs derived from dynamic contrast-enhanced (DCE)-MRI. This represents a preliminary step in the development of a PBPK model useful for predicting Gd-CTCs at a time resolution appropriate for dynamic MRI applications.