Direct Reconstruction of Pharmacokinetic-Rate Images of Optical Fluorophores From NIR Measurements

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2009-09-01
Alacam, Burak
Yazici, Birsen
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.
IEEE TRANSACTIONS ON MEDICAL IMAGING

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Citation Formats
B. Alacam and B. Yazici, “Direct Reconstruction of Pharmacokinetic-Rate Images of Optical Fluorophores From NIR Measurements,” IEEE TRANSACTIONS ON MEDICAL IMAGING, pp. 1337–1353, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65968.