Alacam Burak, Yazici Birsen
Department of Electrical and Electronics Engineering, Middle East Technical University, Northern Cyprus.
IEEE Trans Med Imaging. 2009 Sep;28(9):1337-53. doi: 10.1109/TMI.2009.2015294. Epub 2009 Feb 27.
In this paper, we present a new method to form pharmacokinetic-rate images of optical fluorophores directly from near infra-red (NIR) boundary measurements. We first derive a mapping from spatially resolved pharmacokinetic rates to NIR boundary measurements by combining compartmental modeling with a diffusion based NIR photon propagation model. We express this mapping as a state-space equation. Next, we introduce a spatio-temporal prior model for the pharmacokinetic-rate images and combine it with the state-space equation. We address the image formation problem using the extended Kalman filtering framework. We analyze the computational complexity of the resulting algorithms and evaluate their performance in numerical simulations. An important feature of our approach is that the reconstruction of fluorescence concentrations and compartmental modeling are combined into a single step 1) to take advantage of the inherent temporal correlations in dynamic NIR measurements, and 2) to incorporate spatio-temporal a priori information on pharmacokinetic-rate images. Simulation results show that the resulting algorithms are more robust and lead to higher signal-to-noise ratio as compared to existing approaches where the reconstruction of concentrations and compartmental modeling are treated separately. Additionally, we reconstructed pharmacokinetic-rate images using in vivo data obtained from three patients with breast tumors. The reconstruction results show that the pharmacokinetic rates of indocyanine green are higher inside the tumor region as compared to the surrounding tissue.
在本文中，我们提出了一种直接从近红外（NIR）边界测量中形成光学荧光团药代动力学速率图像的新方法。我们首先通过将房室模型与基于扩散的近红外光子传播模型相结合，推导出从空间分辨的药代动力学速率到近红外边界测量的映射。我们将此映射表示为状态空间方程。接下来，我们为药代动力学速率图像引入时空先验模型，并将其与状态空间方程相结合。我们使用扩展卡尔曼滤波框架来解决图像形成问题。我们分析了所得算法的计算复杂度，并在数值模拟中评估了它们的性能。我们方法的一个重要特点是，荧光浓度的重建和房室模型被合并为一个步骤：1）利用动态近红外测量中固有的时间相关性；2）纳入药代动力学速率图像的时空先验信息。模拟结果表明，与将浓度重建和房室模型分开处理的现有方法相比，所得算法更稳健，且具有更高的信噪比。此外，我们使用从三名乳腺癌患者获得的体内数据重建了药代动力学速率图像。重建结果表明，与周围组织相比，肿瘤区域内吲哚菁绿的药代动力学速率更高。
