Literature DB >> 19258196

Direct reconstruction of pharmacokinetic-rate images of optical fluorophores from NIR measurements.

Burak Alacam1, Birsen Yazici.   

Abstract

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.

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Year:  2009        PMID: 19258196     DOI: 10.1109/TMI.2009.2015294

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  6 in total

1.  Acceleration of dynamic fluorescence molecular tomography with principal component analysis.

Authors:  Guanglei Zhang; Wei He; Huangsheng Pu; Fei Liu; Maomao Chen; Jing Bai; Jianwen Luo
Journal:  Biomed Opt Express       Date:  2015-05-08       Impact factor: 3.732

2.  Automatic selection of regularization parameters for dynamic fluorescence molecular tomography: a comparison of L-curve and U-curve methods.

Authors:  Maomao Chen; Han Su; Yuan Zhou; Chuangjian Cai; Dong Zhang; Jianwen Luo
Journal:  Biomed Opt Express       Date:  2016-11-09       Impact factor: 3.732

3.  Parameterized level-set based pharmacokinetic fluorescence optical tomography using the regularized Gauss-Newton filter.

Authors:  Omprakash Gottam; Naren Naik; Sanjay Gambhir
Journal:  J Biomed Opt       Date:  2018-10       Impact factor: 3.170

4.  In vivo accurate detection of the liver tumor with pharmacokinetic parametric images from dynamic fluorescence molecular tomography.

Authors:  Fei Liu; Peng Zhang; Zeyu Liu; Fan Song; Chenbin Ma; Yangyang Sun; Youdan Feng; Yufang He; Guanglei Zhang
Journal:  J Biomed Opt       Date:  2022-07       Impact factor: 3.758

5.  Temporal Unmixing of Dynamic Fluorescent Images by Blind Source Separation Method with a Convex Framework.

Authors:  Duofang Chen; Jimin Liang; Kui Guo
Journal:  Comput Math Methods Med       Date:  2015-05-24       Impact factor: 2.238

6.  Performance Enhancement of Pharmacokinetic Diffuse Fluorescence Tomography by Use of Adaptive Extended Kalman Filtering.

Authors:  Xin Wang; Linhui Wu; Xi Yi; Yanqi Zhang; Limin Zhang; Huijuan Zhao; Feng Gao
Journal:  Comput Math Methods Med       Date:  2015-05-19       Impact factor: 2.238

  6 in total

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