Assessing pharmacokinetics of indocyanine green-loaded nanoparticle
in tumor with a dynamic diffuse fluorescence tomography system
Yanqi Zhang
a
, Guoyan Yin
a
, Huijuan Zhao
a,b
, Wenjuan Ma
c
, Feng Gao
a,b
, Limin Zhang
a,b,#
a
School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin
300072, China;
b
Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments,
Tianjin 300072, China;
c
Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060,
China
#
Corresponding author: zhanglm@tju.edu.cn
ABSTRACT
Real-time and continuous monitoring of drug release in vivo is an important task in pharmaceutical development. Here,
we devoted to explore a real-time continuous study of the pharmacokinetics of free indocyanine green (ICG) and ICG
loaded in the shell-sheddable nanoparticles in tumor based on a dynamic diffuse fluorescence tomography (DFT) system:
A highly-sensitive dynamic DFT system of CT-scanning mode generates informative and instantaneous sampling
datasets; An analysis procedure extracts the pharmacokinetic parameters from the reconstructed time curves of the mean
ICG concentration in tumor, using the Gauss-Newton scheme based on two-compartment model. Compared with the
pharmacokinetic parameters of free ICG in tumor, the ICG loaded in the shell-sheddable nanoparticles shows efficient
accumulation in tumor. The results demonstrate our proposed dynamic-DFT can provide an integrated and continuous
view of the drug delivery of the injected agents in different formulations, which is helpful for the development of
diagnosis and therapy for tumors.
Keywords: Pharmacokinetic parameters, Diffuse fluorescence tomography, Indocyanine green, Nanoparticles
1. INTRODUCTION
Nano-drug is by far a promising pathway for reducing side effects and enhancing the therapeutic index of
chemotherapeutic drugs, thereby improving the life quality of cancer patients
[1-3]
. It has the characteristics of long blood
circulation time, high loading capacities, efficient protection of bioactive drugs and distinct in vivo pharmacokinetic
pathways in comparison to the traditional free drugs
[4-7]
. Currently, the nano-drugs content is achieved by the vehicles
responding to the specific endogenous or exogenous stimuli in tumor tissues. Despite some exciting results obtained at
the cellular level, in vivo experiments were rarely performed
[8-14]
.
When designing new nano-drugs or nanoparticles, the important preliminary information of the materials, such as the
real-time delivery of the nanoparticles and the drug-release process in tumor, is necessary. Traditional methods to such
research would sacrifice subsets of animals (often mice) at different time points to collect plasma or tumor and measure
the drug concentration in each
[8-10]
. Then the delivery of the nanoparticles can be determined by using a high number of
replicates at each time point. This method has disadvantages of high cost, lengthy process, using large numbers of
animals and decreasing statistical power. Conversely, in vivo measurement is able to non-invasively detect the
nanoparticle concentration at multiple time points to track the metabolic progress and observe the real-time delivery of
the nanoparticles within a single animal
[11-13]
. Currently, some commercial instruments for in vivo imaging can only
continuously show the distribution and accumulation of nanoparticles in planar hierarchy, but not accurately trace the
quantitative fate of nanoparticles inside the tumor in spatial level
[14-15]
. Additionally, some traditional biomedical
imaging techniques such as position-emission tomography (PET)
[16]
and magnetic resonance imaging (MRI)
[17]
, have
the shortages of high cost and radiation. Diffuse fluorescence tomography (DFT) is an emerging imaging technique that
has the advantages of lower cost, radiation-free, noninvasive and allows quantitatively resolving the 3D distribution of
fluorescence in vivo
[18-19]
. When conjugating the drugs or drug nanoparticles with fluorescent probes, DFT is able to
monitor the content of drug released by combining pharmacokinetic principles with mathematical models. Therefore, an
Daniel L. Farkas, Dan V. Nicolau, Robert C. Leif, Proc. of SPIE Vol. 10497, 1049724
Proc. of SPIE Vol. 10497 1049724-1