This Title All WIREs
How to cite this WIREs title:
WIREs Nanomed Nanobiotechnol
Impact Factor: 6.35

Sugar‐based biopolymers as novel imaging agents for molecular magnetic resonance imaging

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Sugar‐based biopolymers have been recognized as attractive materials to develop macromolecule‐ and nanoparticle‐based cancer imaging and therapy. However, traditional biopolymer‐based imaging approaches rely on the use of synthetic or isotopic labeling, and because of it, clinical translation often is hindered. Recently, a novel magnetic resonance imaging (MRI) technology, chemical exchange saturation transfer (CEST), has emerged, which allows the exploitation of sugar‐based biopolymers as MRI agents by their hydroxyl protons‐rich nature. In the study, we reviewed recent studies on the topic of CEST MRI detection of sugar‐based biopolymers. The CEST MRI property of each biopolymer was briefly introduced, followed by the pre‐clinical and clinical applications. The findings of these preliminary studies imply the enormous potential of CEST detectable sugar‐based biopolymers in developing highly sensitive and translatable molecular imaging agents and constructing image‐guided biopolymer‐based drug delivery systems. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Emerging Technologies
Illustration of chemical exchange saturation transfer magnetic resonance imaging (MRI) detection of natural dextran, which is achieved by the continuous transfer of saturated protons (red) from hydroxyl groups to surrounding water molecules, generating a reduction in the water signal (MRI contrast) proportional to the dextran concentration and the rate of exchange. The unsaturated hydroxyl protons are shown in blue. Ssat, the water (MRI) signal in the presence of saturation RF pulses. (Reprinted with permission from G. Liu et al. (). Copyright 2017 Nature Publishing Group)
[ Normal View | Magnified View ]
Changes in the dynamic CEST signal in PSMA(+) and PSMA(−) tumors. (a) T2‐weighted image and dynamic CEST maps at 1 ppm after the injection of 375 mg/kg urea‐10 kD‐dextran (injection volume = 100 μL). (b) Mean changes in the CEST signal in PSMA(+) and PSMA(−) tumors in one of the mice for which time dependence was measured. CEST signal enhancement was quantified by ΔMTRasym = MTRasym(t) ‑ MTRasym (t = 0), where the error bars are the standard errors of the CEST signal of all the pixels in each tumor. All CEST images were acquired using a 1.8 μT and 3 s‐long CW pulse. (c) Average CEST signal in the tumor for five mice before (blue) and 1 hr after (red) the injection of urea‐Dex10. The signal difference is shown in black. Error bars are standard deviations of the CEST signal of all five tumors. (d) Bar plots showing the mean changes in CEST signal as quantified by ΔMTRasym (1 hr) in each type tumor (n = 5 and 3 for urea‐Dex10 and nontargeted Dex10, respectively). *p < 0.05 (Student's t test, two‐tailed and unpaired). (e) in vivo fluorescence image of a representative mouse showing a distinctive tumor uptake of urea‐Dex10 at 60 min after injection. (f) Sections of PSMA(+) PC3‐PIP (top) and PSMA(−) PC3‐flu (bottom) tumors stained with anti‐PSMA. Images were acquired at ×40 magnification. (g) Fluorescence microscopy of nuclei (blue, stained with DAPI) dextran (red, NIR‐600‐labeled). Scale bar = 500 μm for the left three panels and 100 μm for the most right panels, which are the zoomed view of area enclosed in dashed green box in the image on the left. On the right, a scatter plot shows the comparison of the normalized mean fluorescence intensity of three different field of views in the tumors. (Reprinted with permission from G. Liu et al. (). Copyright 2017 Nature Publishing Group)
[ Normal View | Magnified View ]
(a) T2‐weighted image, marked with regions of U87, LS174T, and control white matter (dashed square). (b) CEST contrast map created by averaging 1.2 and 0.9 ppm. Superimposed onto (a) for B1 = 3.6 μT. (c) MTRasym curves of the three ROIs marked in (a). (d) MTRasym values of the two cell lines showing a significant difference (*p < 0.05, Student's t test). Error bars represent standard deviation (n = 3). (Reprinted with permission from Song et al. (). Copyright 2015 Nature Publishing Group)
[ Normal View | Magnified View ]
gagCEST MR images of a human patella in vivo with irradiation at −1.0, +1.0 ppm, and the difference image (a) along with the extracted CEST contrast from the femur and the lateral and medial sides of the patella (b). The total duration of the presaturation pulse sequence was 320 ms at an average RF power of 42 Hz. (Reprinted with permission from Ling et al. (). Copyright 2008 National Academy of Sciences)
[ Normal View | Magnified View ]
glycoCEST imaging of a perfused fed‐mouse liver at 4.7 T and 37°C. The first image (gray scale) marks the beginning of perfusion (t = 0) with glucose‐free media containing 500 pg/mL glucagon. The liver tissue is darkened because of the CEST effect from presaturation at 1.0 ppm for 1 s at 3.0 μT. Upon further perfusion with glucagon, the liver signal increased, corresponding to a decrease in CEST effect. The colorized glycoCEST images as a function of time during perfusion show the relative CEST intensity [MTRasym (1 ppm)] of liver tissue as a function of perfusion time. The color scale shows that there are regions of liver where the initial asymmetry difference between ±1 ppm is as high as 55% (orange pixels) and as low as 5% (blue pixels). With time, as glycogen disappears, the CEST images become more uniformly dark blue, corresponding to minimal glycogen. The corresponding glycogen depletion for a homogeneous region of interest is quantified in the graph (n = 4). (Reprinted with permission from P. C. van Zijl et al. (). Copyright 2007 National Academy of Sciences)
[ Normal View | Magnified View ]
Structure illustration of four sugar‐based biopolymers: (a) glycogen, (b) GAG, (c) Mucin1, and (d) dextran
[ Normal View | Magnified View ]

Browse by Topic

Therapeutic Approaches and Drug Discovery > Emerging Technologies
Diagnostic Tools > In Vitro Nanoparticle-Based Sensing

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts