An Early Investigation of Ytterbium Nanocolloids for Selective and Quantitative "Multicolor" Spectral CT Imaging

C-TRAIN and Division of Cardiology, Washington University School of Medicine, 4320 Forest Park Avenue, St. Louis, Missouri 63108, United States.
ACS Nano (Impact Factor: 12.88). 03/2012; 6(4):3364-70. DOI: 10.1021/nn300392x
Source: PubMed


We report a novel molecular imaging agent based on ytterbium designed for use with spectral "multicolor" computed tomography (CT). Spectral CT or multicolored CT provides all of the benefits of traditional CT, such as rapid tomographic X-ray imaging, but in addition, it simultaneously discriminates metal-rich contrast agents based on the element's unique X-ray K-edge energy signature. Our synthetic approach involved the use of organically soluble Yb(III) complex to produce nanocolloids of Yb of noncrystalline nature incorporating a high density of Yb (>500K/nanoparticle) into a stable metal particle. The resultant particles are constrained to vasculature (∼200 nm) and are highly selective for binding fibrin in the ruptured atherosclerotic plaque. Nanoparticles exhibited excellent signal sensitivity, and the spectral CT technique uniquely discriminates the K-edge signal (60 keV) of Yb from calcium (bones). Bioelimination and preliminary biodistribution reflected the overall safety and defined clearance of these particles in a rodent model.

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Available from: Anne H Schmieder, Jun 08, 2015
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    • "HE DEVELOPMENT of spectral X-ray computed tomography (CT) using binned photon-counting detectors has received great attention in recent years and is prompting a paradigm shift in X-ray CT imaging [1]. The availability of more than two spectral measurements has enabled a new imaging method named K-edge imaging [2] that can be used to selectively and quantitatively image contrast agents loaded with K-edge materials [3], [4]. "
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    ABSTRACT: The development of spectral X-ray computed tomography (CT) using binned photon-counting detectors has received great attention in recent years and has enabled selective imaging of contrast agents loaded with K-edge materials. A practical issue in implementing this technique is the mitigation of the highnoise levels often present in material-decomposed sinogram data. In this work, the spectral X-ray CT reconstruction problem is formulated within a multi-channel (MC) framework in which statistical correlations between the decomposed material sinograms can be exploited to improve image quality. Specifically, a MC penalized weighted least squares (PWLS) estimator is formulated in which the data fidelity term is weighted by the MC covariance matrix and sparsity-promoting penalties are employed. This allows the use of any number of basis materials and is therefore applicable to photon-counting systems and K-edge imaging. To overcome numerical challenges associated with use of the full covariance matrix as a data fidelity weight, a proximal variant of the alternating direction method of multipliers (ADMM) is employed to minimize the MC PWLS objective function. Computersimulation and experimental phantom studies are conducted to quantitatively evaluate the proposed reconstruction method.
    04/2014; 33(8). DOI:10.1109/TMI.2014.2321098
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    • "For example, K-edge CT has been investigated as a modality to image contrast agents such as iodine (Abudurexiti et al 2010, He et al 2012), gadolinium (Feuerlein et al 2008), bismuth (Pan et al 2010), and gold (Cormode et al 2010). Ytterbium was recently discussed as a contrast agent for conventional CT (Liu et al 2012) in general and K-edge imaging (Pan et al 2012). The task of image reconstruction in spectral CT can be implemented in a two-stage processing scheme. "
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    ABSTRACT: The development of spectral computed tomography (CT) using binned photon-counting detectors has garnered great interest in recent years and has enabled selective imaging of K-edge materials. A practical challenge in CT image reconstruction of K-edge materials is the mitigation of image artifacts that arise from reduced-view and/or noisy decomposed sinogram data. In this note, we describe and investigate sparsity-regularized penalized weighted least squares-based image reconstruction algorithms for reconstructing K-edge images from few-view decomposed K-edge sinogram data. To exploit the inherent sparseness of typical K-edge images, we investigate use of a total variation (TV) penalty and a weighted sum of a TV penalty and an ℓ1-norm with a wavelet sparsifying transform. Computer-simulation and experimental phantom studies are conducted to quantitatively demonstrate the effectiveness of the proposed reconstruction algorithms.
    Physics in Medicine and Biology 04/2014; 59(10):N65-N79. DOI:10.1088/0031-9155/59/10/N65 · 2.76 Impact Factor
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    ABSTRACT: Gold nanoparticles (AuNPs) have a number of physical properties that make them appealing for medical applications. For example, the attenuation of X-rays by gold nanoparticles has led to their use in computed tomography imaging and as adjuvants for radiotherapy. AuNPs have numerous other applications in imaging, therapy and diagnostic systems. The advanced state of synthetic chemistry of gold nanoparticles offers precise control over physicochemical and optical properties. Furthermore gold cores are inert and are considered to be biocompatible and non-toxic. The surface of gold nanoparticles can easily be modified for a specific application and ligands for targeting, drugs or biocompatible coatings can be introduced. AuNPs can be incorporated into larger structures such as polymeric nanoparticles or liposomes that deliver large payloads for enhanced diagnostic applications, efficiently encapsulate drugs for concurrent therapy or add additional imaging labels. This array of features has led to the afore-mentioned applications in biomedical fields, but more recently in approaches where multifunctional gold nanoparticles are used for multiple methods, such as concurrent diagnosis and therapy, so called theranostics. The following review covers basic principles and recent findings in gold nanoparticle applications for imaging, therapy and diagnostics, with a focus on reports of multifunctional AuNPs.
    Molecular Pharmaceutics 01/2013; DOI:10.1021/mp3005885 · 4.38 Impact Factor
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