Department of Radiology, Northwestern University Chicago, IL 60611, USA.
Phys Med Biol. 2013 Mar 21;58(6):1983-98. doi: 10.1088/0031-9155/58/6/1983. Epub 2013 Mar 4.
Accurate quantification of pharmacokinetic parameters in dynamic contrast-enhanced (DCE) MRI may be affected by the passive diffusion of contrast agent (CA) within the tissue. By introducing an additional term into the standard Tofts-Kety (STK) model, we correct for the effects of CA diffusion. We first develop the theory describing a CA diffusion corrected STK model (DTK). The model is then tested in simulation with simple models of diffusion. The DTK model is also fit to 18 in vivo DCE-MRI acquisitions from murine models of cancer and results are compared to those from the STK model. The DTK model returned estimates with significantly lower error than the STK model (p ≪ 0.001). In poorly perfused (i.e., K(trans) ≤ 0.05 min(-1)) regions the STK model returned unphysical ve values, while the DTK model estimated ve with less than 7% error in noise-free simulations. Results in vivo data revealed similar trends. For voxels with low K(trans) values and late peak concentration times the STK model returned ve estimates >1.0 in 40% of the voxels as compared to only 16% for the DTK model. The DTK model presented here shows promise in estimating accurate kinetic parameters in the presence of passive contrast agent diffusion.
在动态对比增强 (DCE) MRI 中，药代动力学参数的精确量化可能会受到对比剂 (CA) 在组织内被动扩散的影响。通过在标准 Tofts-Kety (STK) 模型中引入额外项，可以校正 CA 扩散的影响。我们首先开发了描述 CA 扩散校正 STK 模型 (DTK) 的理论。然后，使用 CA 扩散的简单模型对该模型进行了模拟测试。DTK 模型也适用于来自癌症小鼠模型的 18 个体内 DCE-MRI 采集，并将结果与 STK 模型进行比较。DTK 模型返回的估计值误差明显低于 STK 模型（p ≪ 0.001）。在灌注不良的区域（即 K(trans) ≤ 0.05 min(-1)），STK 模型返回的 ve 值不具有物理意义，而 DTK 模型在无噪声模拟中估计的 ve 值误差小于 7%。体内数据的结果显示出类似的趋势。对于 K(trans) 值较低且峰值浓度时间较晚的体素，STK 模型返回的 ve 值在 40%的体素中大于 1.0，而 DTK 模型仅为 16%。本文提出的 DTK 模型有望在存在被动对比剂扩散的情况下准确估计动力学参数。
