Koller Jonathan M, Vachon M Jonathan, Bretthorst G Larry, Black Kevin J
Department of Psychiatry, Washington University in St. Louis St. Louis, MO, USA.
College of Arts and Sciences, Washington University in St. Louis St. Louis, MO, USA.
Front Neurosci. 2016 Apr 8;10:144. doi: 10.3389/fnins.2016.00144. eCollection 2016.
We recently described rapid quantitative pharmacodynamic imaging, a novel method for estimating sensitivity of a biological system to a drug. We tested its accuracy in simulated biological signals with varying receptor sensitivity and varying levels of random noise, and presented initial proof-of-concept data from functional MRI (fMRI) studies in primate brain. However, the initial simulation testing used a simple iterative approach to estimate pharmacokinetic-pharmacodynamic (PKPD) parameters, an approach that was computationally efficient but returned parameters only from a small, discrete set of values chosen a priori. Here we revisit the simulation testing using a Bayesian method to estimate the PKPD parameters. This improved accuracy compared to our previous method, and noise without intentional signal was never interpreted as signal. We also reanalyze the fMRI proof-of-concept data. The success with the simulated data, and with the limited fMRI data, is a necessary first step toward further testing of rapid quantitative pharmacodynamic imaging.
我们最近描述了快速定量药效学成像，这是一种估算生物系统对药物敏感性的新方法。我们在具有不同受体敏感性和不同水平随机噪声的模拟生物信号中测试了其准确性，并展示了来自灵长类动物脑功能磁共振成像（fMRI）研究的初步概念验证数据。然而，最初的模拟测试使用了一种简单的迭代方法来估算药代动力学 - 药效学（PKPD）参数，该方法计算效率高，但仅从一组预先选择的小的离散值中返回参数。在这里，我们使用贝叶斯方法重新进行模拟测试以估算PKPD参数。与我们之前的方法相比，这提高了准确性，并且没有故意信号的噪声从未被解释为信号。我们还重新分析了fMRI概念验证数据。模拟数据以及有限的fMRI数据取得的成功，是朝着进一步测试快速定量药效学成像迈出的必要的第一步。
