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# Magnetic resonance susceptibility based perfusion imaging of tumors using iron oxide nanoparticles

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Abundant preclinical and preliminary clinical data have convincingly supported antiangiogenic therapy as an effective strategy for the inhibition of tumor growth. This has led to an acute need for developing biological markers (biomarkers) of vascular remodeling that can be monitored in vivo, at repeated intervals in large numbers of patients with a variety of tumors in a noninvasive manner. Recently, magnetic resonance (MR) perfusion imaging with iron oxide nanoparticles has demonstrated the potential to be such a surrogate endpoint, that is, a biomarker intended to substitute for a clinical endpoint and predictive of clinical benefit. Consequently, both US Food and Drug Administration (FDA) and the National Cancer Institute (NCI) have major initiatives underway to improve the development of cancer therapies and the outcomes for cancer patients via biomarker development and evaluation. The biophysical principles, physiological relevance and range of imaging techniques underlying the success of susceptibility based contrast MR perfusion imaging with iron oxide nanoparticles as such a biomarker, are the subject of this review. Copyright © 2008 John Wiley & Sons, Inc.

Figure 1.

Schematic illustrating the origins of susceptibility based Magnetic resonance (MR) contrast. (a) In the absence of any susceptibility difference between blood (χ1) and the surrounding tissue (χ2), no microscopic magnetic field gradient is set up and diffusing water protons experience the same local magnetic field. (b) When a susceptibility difference (Δ χ) arises between the intravascular space and the surrounding tissue, say as a result of the presence of superparamagnetic iron oxide (SPIO) contrast agent, a microscopic field gradient (‐‐‐) is set up that perturbs the local magnetic field, and diffusing water protons experience different local magnetic fields, leading to loss of phase coherence, and MR signal attenuation that can be followed dynamically using either T2‐ or \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$T_{2}^{\ast}$\end{document}‐weighted MR pulse sequences. This constitutes the basis of dynamic susceptibility based contrast (DSC) magnetic resonance imaging (MRI). (c) Surface plot illustrating the three‐dimensional aspects of mathematically simulated microscopic magnetic field gradients induced around a microvessel. The orientation of the applied field (B0) and the axis along which the normalized field change (Δ B/B0 Δ χ) is plotted are shown in the inset. (Reprinted, with permission, from Ref.14. Copyright 2004 Elsevier).

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Figure 2.

(a) Schematic illustrating the three different regimes of susceptibility induced relaxation effects and the differential sensitivity of gradient‐echo (GE) (\documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}) and spin‐echo (SE) (ΔR2) relaxation rates to vessel caliber. This sensitivity to vessel size constitutes the basis for imaging macro‐ and microvascular blood volume as well as imaging vessel‐size. (b) Size dependence of \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document} and ΔR2 for fractional volume = 2% and Δχ = 1 × 10−7. ΔR2 peaks for microvessels, while \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2} \ast >\Delta R_{2}$\end{document} for all radii and plateaus for macrovessels. (Reprinted, with permission, from Refs.14,21).

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Figure 3.

Schematic illustrating: (a) random orientations of the magnetic domains in a superparamagnetic iron oxide (SPIO) particle in the absence of any applied magnetic field, and (b) application of an external magnetic field B0 causing the magnetic domains of the SPIO particle to orient along B0. (c) Superparamagnetic particles (S) (open arrows) have a very high magnetic susceptibility and can be magnetized (M) to saturation (MS = saturation magnetization) even in weak external magnetic fields (H). Unmagnetized ferromagnetic and ferrimagnetic materials (F) (solid arrows) also become magnetized along this curve. However, once magnetized, ferromagnetic and ferrimagnetic materials retain their magnetization (MR = remnant magnetization), even if the external field is reduced to zero. However, at ambient temperatures superparamagnetic materials do not retain their magnetization in the absence of an applied field. (Reprinted, with permission, from Ref. 25 Copyright 2001 Springer and Ref. 30 Copyright 1972 Addison‐Wesley).

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Figure 4.

(a) Post‐Gd MR image of a 9L gliosarcoma bearing rat brain illustrating the tumor ROI (yellow hatched ellipse). (b) Post‐monocrystalline iron oxide nanoparticle (MION) ratio \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}R2 map of a 9L gliosarcoma bearing rat brain wherein one can clearly see the elevated ratio values in the angiogenic tumor rim (yellow hatched ellipse). (c) A histogram of the \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}R2 data showing that for the tumor ROI (over all slices), \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}R2 is shifted to the right i.e., larger caliber vessels with respect to the contralateral brain ROI (over all slices) \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}R2, a difference that is also apparent from (d) the histogram of the stereologically calculated vessel radii. (Reprinted, with permission, from Ref.62. Copyright 2001).

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Figure 5.

(a) Post‐Gd axial magnetic resonance imaging (MRI) of the rat brain illustrating the ROIs for the tumor (red) and contralateral (yellow) brain. (b) Post‐monocrystalline iron oxide nanoparticle (MION) axial MRI of the rat illustrating the ROIs for the gray (gray) and white (white) matter, respectively. Binarized images of tissue sections of microfilled vessels at 20× magnification of: (c) tumor, (d) contralateral brain, (e) gray matter, and (f) white matter ROIs. The color of each frame on the lower panel corresponds to the color of the ROI from which the tissue sections were sampled for histology. (g) Comparison of the ratios of fractional volumes obtained from MRI and histology for the tumor versus contralateral, and gray versus white ROIs, respectively. The error bars represent the standard error of the mean for each technique (N = 6 rats for the gray/white and N = 8 rats for the contra/tumor). There was no significant (P = 0.525) difference between \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}gray/\documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}white and the ratio gray/white fractional volume but a significant (P = 0.005) difference between \documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}tumor/\documentclass{article}\usepackage{amsmath}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{amsfonts}\pagestyle{empty}\begin{document}$\Delta R_{2}^{\ast}$\end{document}contra and the ratio tumor/contralateral fractional volume. This result indicates that the GE calibration factor is the same for gray and white matter but not the same for brain and tumor tissue. (Reprinted, with permission, from Ref. 39. Copyright 1994).

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Figure 6.

(a) Post‐Gd MR image of a 9L gliosarcoma bearing rat brain illustrating the contralateral (C) and tumor (T) ROIs employed for MR relative cerebral blood volume (rCBV) histogram analyses. (b) rCBV map computed from the first‐pass of monocrystalline iron oxide nanoparticle (MION), overlaid on a high‐resolution anatomical image: note elevated rCBV in the tumor, a finding consistent with a larger fractional blood volume (FV) relative to the contralateral brain. (c) Post‐Gd MR image illustrating the contralateral (C) and tumor (T) grids that were sampled for stereological analyses. H&E stained tissue section of vessels perfused with Microfil (a silicone injection compound) at 20× magnification of (d) tumor tissue and (e) normal brain. (f) A histogram of the GE rCBV data showing that the tumor rCBV is shifted to the right with respect to the contralateral rCBV, a difference that is also apparent from (g) the histogram of the stereologically calculated FV. (Reprinted, with permission, from Ref. 35. Copyright 2000 Springer Verlag).

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