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

Abstract

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.

Acceleration of dynamic fluorescence molecular tomography with principal component analysis

“…Although the proposed acceleration direct method for parametric image reconstruction is based on regularization framework, the acceleration strategy of the proposed method can also be extended to other direct methods [3,4,36]. In addition, the reconstruction process of dynamic FMT may be further accelerated by applying compression approaches in parametric image domain [25].…”

“…In this work, the line-shaped excitation source is employed for whole-body imaging. (4) where the Green's function ( , ) x s G LS r describes the light propagation from the line-shaped excitation source LS at a project angle s to an arbitrary position r inside the medium at the excitation wavelength; the Green's function ( , ) m d G r r describes the light propagation from the position r inside the medium to the detector position d r at the emission wavelength; Θ is a calibration factor which accounts for the unknown gain of the system.…”

“…The time-varying concentration ( , ) n t r is usually caused by the metabolism of fluorophores in the body, and can provide valuable physiological information for biological studies, disease diagnosis and drug development [7]. Recently, indocyanine green (ICG) has been widely used in the field of optical imaging because of its low toxicity and approval for human use [4,5,14,15]. Based on compartmental modeling, the metabolic processes of ICG in the organs and tissues can be described by a bi-exponential model [5,14] ( ) ( )…”

“…Dynamic fluorescence molecular tomography (FMT) is a promising imaging technique that allows dynamically and three-dimensionally investigating the metabolic process of fluorescent biomarkers within small animals in vivo [1][2][3][4][5][6][7]. Meanwhile, compartmental modeling is a well-known method for pharmacokinetic analysis, and the pharmacokinetic parameters defined in the compartmental model can be utilized to describe the uptake and excretion of substances such as drugs, radiotracers and fluorophores in the body [6].…”

“…Meanwhile, compartmental modeling is a well-known method for pharmacokinetic analysis, and the pharmacokinetic parameters defined in the compartmental model can be utilized to describe the uptake and excretion of substances such as drugs, radiotracers and fluorophores in the body [6]. The boundary measurements of dynamic FMT can be transformed into three-dimensional (3-D) images of pharmacokinetic parameters through compartmental modeling [4][5][6][7], as has been done in positron emission tomography (PET) [8][9][10] and magnetic resonance imaging (MRI) [11][12][13]. Images of pharmacokinetic parameters are also known as parametric images, which can provide valuable physiological information for tumor detection [14][15][16], therapy assessment [17], and organ function evaluation [5][6][7]18].…”