Department of Radiology, University of Washington, Seattle, Washington 98109, USA.
Magn Reson Med. 2011 Sep;66(3):868-78. doi: 10.1002/mrm.22819. Epub 2011 Mar 9.
Kinetic analysis with mathematical models has become increasingly important to quantify physiological parameters in computed tomography (CT), positron emission tomography (PET), and dynamic contrast-enhanced MRI (DCE-MRI). The modified Kety/Tofts model and the graphical (Patlak) model have been widely applied to DCE-MRI results in disease processes such as cancer, inflammation, and ischemia. In this article, an intermediate model between the modified Kety/Tofts and Patlak models is derived from a mathematical expansion of the modified Kety/Tofts model. Simulations and an in vivo experiment involving DCE-MRI of carotid atherosclerosis were used to compare the new extended graphical model with the modified Kety/Tofts model and the Patlak model. In our simulated circumstances and the carotid artery application, we found that the extended graphical model exhibited lower noise sensitivity and provided more accurate estimates of the volume transfer constant (K(trans)) and fractional plasma volume (v(p)) than the modified Kety/Tofts model for DCE-MRI acquisitions of total duration less than 100-300 s, depending on kinetic parameters. In comparison with the Patlak model, we found that the extended graphical model exhibited 74.4-99.8% less bias in estimates of K(trans). Thus, the extended graphical model may allow kinetic modeling of DCE-MRI results with shortened data acquisition periods, without sacrificing accuracy in estimates of K(trans) and v(p).
运用数学模型进行动力学分析对于量化计算机断层扫描 (CT)、正电子发射断层扫描 (PET) 和动态对比增强磁共振成像 (DCE-MRI) 中的生理参数变得越来越重要。改良的 Kety/Tofts 模型和图形 (Patlak) 模型已广泛应用于癌症、炎症和缺血等疾病过程的 DCE-MRI 结果。在本文中，从改良的 Kety/Tofts 模型的数学扩展中推导出了改良的 Kety/Tofts 模型和 Patlak 模型之间的中间模型。模拟和涉及颈动脉粥样硬化的 DCE-MRI 的体内实验用于比较新的扩展图形模型与改良的 Kety/Tofts 模型和 Patlak 模型。在我们的模拟情况和颈动脉应用中，我们发现对于总持续时间小于 100-300 秒的 DCE-MRI 采集，扩展图形模型比改良的 Kety/Tofts 模型表现出更低的噪声敏感性，并能更准确地估计体积转移常数 (K(trans)) 和分数血浆体积 (v(p))。与 Patlak 模型相比，我们发现扩展图形模型在估计 K(trans)方面的偏差减少了 74.4-99.8%。因此，扩展图形模型可以在不牺牲 K(trans)和 v(p)估计准确性的情况下，允许使用缩短的数据采集期进行 DCE-MRI 结果的动力学建模。
