complex array of interrelated physicochemical and biological factors, and an
in-depth knowledge of the nanoparticle-organ interaction is critical for not only the
nanoplatform design but also its potential clinical translation.
Semi-quantitative optical imaging technique has been the primary tool for
accessing the PK of the nanoparticles in small animals. However, due to the limitation in tissue penetration depth, the influence of autofluorescence and light
scattering, and the potential detachment of free organic dyes in vivo, achieving an
accurate nanoparticle biodistribution over time can be quite challenging. For
example, based on the ex vivo optical imaging of tissue slides, an early study
showed liver, spleen and renal excretion of over 80 nm sized dye-conjugated
spherical mesoporous silica nanoparticles (MSNs) after intravenous injection (i.v.)
injection in ICR mice [15]. The study might require additional validation to rule out
the possible leakage of the conjugated dyes since renal cut-off was generally
believed to be around 5.5 nm (or less than 10 nm) [16]. Over-estimated
tumor-to-organ ratios is another concern when using an optical imaging technique, since some organs, like liver, might absorb the emission light more than the
tumor tissue even when performing the optical imaging ex vivo. Although other
imaging modalities, such as Computed Tomography (CT) and Magnetic Resonance
Imaging (MRI), are also available for whole body non-invasive imaging, they are
not capable of providing a quantitative PK assessment.
So far, highly sensitive and quantitative nuclear imaging is perhaps the best tool
for assessing the PK profile of radiolabeled nanoparticles in vivo [17–21].
Non-invasive nuclear imaging (such as positron emission tomography, or PET) of
small animals could also allow for a serial imaging of live subjects, which obviates
the need to sacrifice animals and minimizes inter-individual variations. Although
previous review articles have summarized the effect of nanoparticle size, shape and
surface chemistry on the biological system (in vivo) [2, 3, 22, 23], most of them
have focused on PK of nanoparticles based on semi-quantitative optical imaging
technique. Here in this chapter, we will provide an overview of size-, shape- and
charge-dependent PK of the widely studied radiolabeled nanoparticles (such as
silica nanoparticles, quantum dots, gold nanoparticles, etc.) accessed by using
nuclear imaging technique.
17.2 Impact of Particle Size
It is generally accepted that the biodistribution of nanoparticle is determined by the
hydrodynamic (HD) size, shape, surface chemistry, in vivo stability and the
administration route of the injected nanoparticles [21]. It is worthy to mention that
protein adsorption on nanoparticle surface after i.v. injection could dramatically
increase the HD size, change the surface charge, cause aggregation, leading to
dramatic alterations in their fate in vivo. Studies also suggested that the extent of
non-specific binding (or adsorption) of proteins in the bloodstream is highly
dependent on the nanoparticle size, curvature, hydrophobicity, surface charge, etc.
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F. Chen
in-depth knowledge of the nanoparticle-organ interaction is critical for not only the
nanoplatform design but also its potential clinical translation.
Semi-quantitative optical imaging technique has been the primary tool for
accessing the PK of the nanoparticles in small animals. However, due to the limitation in tissue penetration depth, the influence of autofluorescence and light
scattering, and the potential detachment of free organic dyes in vivo, achieving an
accurate nanoparticle biodistribution over time can be quite challenging. For
example, based on the ex vivo optical imaging of tissue slides, an early study
showed liver, spleen and renal excretion of over 80 nm sized dye-conjugated
spherical mesoporous silica nanoparticles (MSNs) after intravenous injection (i.v.)
injection in ICR mice [15]. The study might require additional validation to rule out
the possible leakage of the conjugated dyes since renal cut-off was generally
believed to be around 5.5 nm (or less than 10 nm) [16]. Over-estimated
tumor-to-organ ratios is another concern when using an optical imaging technique, since some organs, like liver, might absorb the emission light more than the
tumor tissue even when performing the optical imaging ex vivo. Although other
imaging modalities, such as Computed Tomography (CT) and Magnetic Resonance
Imaging (MRI), are also available for whole body non-invasive imaging, they are
not capable of providing a quantitative PK assessment.
So far, highly sensitive and quantitative nuclear imaging is perhaps the best tool
for assessing the PK profile of radiolabeled nanoparticles in vivo [17–21].
Non-invasive nuclear imaging (such as positron emission tomography, or PET) of
small animals could also allow for a serial imaging of live subjects, which obviates
the need to sacrifice animals and minimizes inter-individual variations. Although
previous review articles have summarized the effect of nanoparticle size, shape and
surface chemistry on the biological system (in vivo) [2, 3, 22, 23], most of them
have focused on PK of nanoparticles based on semi-quantitative optical imaging
technique. Here in this chapter, we will provide an overview of size-, shape- and
charge-dependent PK of the widely studied radiolabeled nanoparticles (such as
silica nanoparticles, quantum dots, gold nanoparticles, etc.) accessed by using
nuclear imaging technique.
17.2 Impact of Particle Size
It is generally accepted that the biodistribution of nanoparticle is determined by the
hydrodynamic (HD) size, shape, surface chemistry, in vivo stability and the
administration route of the injected nanoparticles [21]. It is worthy to mention that
protein adsorption on nanoparticle surface after i.v. injection could dramatically
increase the HD size, change the surface charge, cause aggregation, leading to
dramatic alterations in their fate in vivo. Studies also suggested that the extent of
non-specific binding (or adsorption) of proteins in the bloodstream is highly
dependent on the nanoparticle size, curvature, hydrophobicity, surface charge, etc.
314
F. Chen