Dual-energy micro-CT functional imaging of primary lung cancer in mice using gold and iodine nanoparticle contrast agents: a validation study

A neural network-based method for spectral distortion correction in photon counting x-ray CT

Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables both 4 energy bins acquisition, as well as full-spectrum mode in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical effects in the detector and can be very noisy due to photon starvation in narrow energy bins. To address spectral distortions, we propose and demonstrate a novel artificial neural network (ANN)-based spectral distortion correction mechanism, which learns to undo the distortion in spectral CT, resulting in improved material decomposition accuracy. To address noise, post-reconstruction denoising based on bilateral filtration, which jointly enforces intensity gradient sparsity between spectral samples, is used to further improve the robustness of ANN training and material decomposition accuracy. Our ANN-based distortion correction method is calibrated using 3D-printed phantoms and a model of our spectral CT system. To enable realistic simulations and validation of our method, we first modeled the spectral distortions using experimental data acquired from (109)Cd and (133)Ba radioactive sources measured with our PCXD. Next, we trained an ANN to learn the relationship between the distorted spectral CT projections and the ideal, distortion-free projections in a calibration step. This required knowledge of the ground truth, distortion-free spectral CT projections, which were obtained by simulating a spectral CT scan of the digital version of a 3D-printed phantom. Once the training was completed, the trained ANN was used to perform distortion correction on any subsequent scans of the same system with the same parameters. We used joint bilateral filtration to perform noise reduction by jointly enforcing intensity gradient sparsity between the reconstructed images for each energy bin. Following reconstruction and denoising, the CT data was spectrally decomposed using the photoelectric effect, Compton scattering, and a K-edge material (i.e. iodine). The ANN-based distortion correction approach was tested using both simulations and experimental data acquired in phantoms and a mouse with our PCXD-based micro-CT system for 4 bins and full-spectrum acquisition modes. The iodine detectability and decomposition accuracy were assessed using the contrast-to-noise ratio and relative error in iodine concentration estimation metrics in images with and without distortion correction. In simulation, the material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with 50% and 20% reductions in material concentration measurement error in full-spectrum and 4 energy bins cases, respectively. Overall, experimental data confirms that full-spectrum mode provides superior results to 4-energy mode when the distortion corrections are applied. The material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with as much as a 41% reduction in material concentration measurement error for full-spectrum mode, while also bringing the iodine detectability to 4-6 mg ml(-1). Distortion correction also improved the 4 bins mode data, but to a lesser extent. The results demonstrate the experimental feasibility and potential advantages of ANN-based distortion correction and joint bilateral filtration-based denoising for accurate K-edge imaging with a PCXD. Given the computational efficiency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.

Engineering iodine-doped carbon dots as dual-modal probes for fluorescence and X-ray CT imaging

X-ray computed tomography (CT) is the most commonly used imaging technique for noninvasive diagnosis of disease. In order to improve tissue specificity and prevent adverse effects, we report the design and synthesis of iodine-doped carbon dots (I-doped CDs) as efficient CT contrast agents and fluorescence probe by a facile bottom-up hydrothermal carbonization process. The as-prepared I-doped CDs are monodispersed spherical nanoparticles (a diameter of ~2.7 nm) with favorable dispersibility and colloidal stability in water. The aqueous solution of I-doped CDs showed wavelength-dependent excitation and stable photoluminescence similar to traditional carbon quantum dots. Importantly, I-doped CDs displayed superior X-ray attenuation properties in vitro and excellent biocompatibility. After intravenous injection, I-doped CDs were distributed throughout the body and excreted by renal clearance. These findings validated that I-doped CDs with high X-ray attenuation potency and favorable photoluminescence show great promise for biomedical research and disease diagnosis.

In vivo small animal micro-CT using nanoparticle contrast agents

Computed tomography (CT) is one of the most valuable modalities for in vivo imaging because it is fast, high-resolution, cost-effective, and non-invasive. Moreover, CT is heavily used not only in the clinic (for both diagnostics and treatment planning) but also in preclinical research as micro-CT. Although CT is inherently effective for lung and bone imaging, soft tissue imaging requires the use of contrast agents. For small animal micro-CT, nanoparticle contrast agents are used in order to avoid rapid renal clearance. A variety of nanoparticles have been used for micro-CT imaging, but the majority of research has focused on the use of iodine-containing nanoparticles and gold nanoparticles. Both nanoparticle types can act as highly effective blood pool contrast agents or can be targeted using a wide variety of targeting mechanisms. CT imaging can be further enhanced by adding spectral capabilities to separate multiple co-injected nanoparticles in vivo. Spectral CT, using both energy-integrating and energy-resolving detectors, has been used with multiple contrast agents to enable functional and molecular imaging. This review focuses on new developments for in vivo small animal micro-CT using novel nanoparticle probes applied in preclinical research.

Integration of imaging into clinical practice to assess the delivery and performance of macromolecular and nanotechnology-based oncology therapies

Functional and molecular imaging has become increasingly used to evaluate interpatient and intrapatient tumor heterogeneity. Imaging allows for assessment of microenvironment parameters including tumor hypoxia, perfusion and proliferation, as well as tumor metabolism and the intratumoral distribution of specific molecular markers. Imaging information may be used to stratify patients for targeted therapies, and to define patient populations that may benefit from alternative therapeutic approaches. It also provides a method for non-invasive monitoring of treatment response at earlier time-points than traditional cues, such as tumor shrinkage. Further, companion diagnostic imaging techniques are becoming progressively more important for development and clinical implementation of targeted therapies. Imaging-based companion diagnostics are likely to be essential for the validation and FDA approval of targeted nanotherapies and macromolecular medicines. This review describes recent clinical advances in the use of functional and molecular imaging to evaluate the tumor microenvironment. Additionally, this article focuses on image-based assessment of distribution and anti-tumor effect of nano- and macromolecular systems.

Imaging of Hsp70-positive tumors with cmHsp70.1 antibody-conjugated gold nanoparticles

Real-time imaging of small tumors is still one of the challenges in cancer diagnosis, prognosis, and monitoring of clinical outcome. Targeting novel biomarkers that are selectively expressed on a large variety of different tumors but not normal cells has the potential to improve the imaging capacity of existing methods such as computed tomography. Herein, we present a novel technique using cmHsp70.1 monoclonal antibody-conjugated spherical gold nanoparticles for quantification of the targeted uptake of gold nanoparticles into membrane Hsp70-positive tumor cells. Upon binding, cmHsp70.1-conjugated gold nanoparticles but not nanoparticles coupled to an isotype-matched IgG1 antibody or empty nanoparticles are rapidly taken up by highly malignant Hsp70 membrane-positive mouse tumor cells. After 24 hours, the cmHsp70.1-conjugated gold nanoparticles are found to be enriched in the perinuclear region. Specificity for membrane Hsp70 was shown by using an Hsp70 knockout tumor cell system. Toxic side effects of the cmHsp70.1-conjugated nanoparticles are not observed at a concentration of 1–10 µg/mL. Experiments are ongoing to evaluate whether cmHsp70.1 antibody-conjugated gold nanoparticles are suitable for the detection of membrane-Hsp70-positive tumors in vivo.

A Plasmonic Gold Nanostar Theranostic Probe for In Vivo Tumor Imaging and Photothermal Therapy

Nanomedicine has attracted increasing attention in recent years, because it offers great promise to provide personalized diagnostics and therapy with improved treatment efficacy and specificity. In this study, we developed a gold nanostar (GNS) probe for multi-modality theranostics including surface-enhanced Raman scattering (SERS) detection, x-ray computed tomography (CT), two-photon luminescence (TPL) imaging, and photothermal therapy (PTT). We performed radiolabeling, as well as CT and optical imaging, to investigate the GNS probe's biodistribution and intratumoral uptake at both macroscopic and microscopic scales. We also characterized the performance of the GNS nanoprobe for in vitro photothermal heating and in vivo photothermal ablation of primary sarcomas in mice. The results showed that 30-nm GNS have higher tumor uptake, as well as deeper penetration into tumor interstitial space compared to 60-nm GNS. In addition, we found that a higher injection dose of GNS can increase the percentage of tumor uptake. We also demonstrated the GNS probe's superior photothermal conversion efficiency with a highly concentrated heating effect due to a tip-enhanced plasmonic effect. In vivo photothermal therapy with a near-infrared (NIR) laser under the maximum permissible exposure (MPE) led to ablation of aggressive tumors containing GNS, but had no effect in the absence of GNS. This multifunctional GNS probe has the potential to be used for in vivo biosensing, preoperative CT imaging, intraoperative detection with optical methods (SERS and TPL), as well as image-guided photothermal therapy.

Nanotoxic profiling of novel iron oxide nanoparticles functionalized with perchloric acid and SiPEG as a radiographic contrast medium

Emerging syntheses and findings of new metallic nanoparticles (MNPs) have become an important aspect in various fields including diagnostic imaging. To date, iodine has been utilized as a radiographic contrast medium. However, the raise concern of iodine threats on iodine-intolerance patient has led to search of new contrast media with lower toxic level. In this animal modeling study, 14 nm iron oxide nanoparticles (IONPs) with silane-polyethylene glycol (SiPEG) and perchloric acid have been assessed for toxicity level as compared to conventional iodine. The nanotoxicity of IONPs was evaluated in liver biochemistry, reactive oxygen species production (ROS), lipid peroxidation mechanism, and ultrastructural evaluation using transmission electron microscope (TEM). The hematological analysis and liver function test (LFT) revealed that most of the liver enzymes were significantly higher in iodine-administered group as compared to those in normal and IONPs groups (P < 0.05). ROS production assay and lipid peroxidation indicator, malondialdehyde (MDA), also showed significant reductions in comparison with iodine group (P < 0.05). TEM evaluation yielded the aberration of nucleus structure of iodine-administered group as compared to those in control and IONPs groups. This study has demonstrated the less toxic properties of IONPs and it may postulate that IONPs are safe to be applied as radiographic contrast medium.

Spectral diffusion: an algorithm for robust material decomposition of spectral CT data

Clinical successes with dual energy CT, aggressive development of energy discriminating x-ray detectors, and novel, target-specific, nanoparticle contrast agents promise to establish spectral CT as a powerful functional imaging modality. Common to all of these applications is the need for a material decomposition algorithm which is robust in the presence of noise. Here, we develop such an algorithm which uses spectrally joint, piecewise constant kernel regression and the split Bregman method to iteratively solve for a material decomposition which is gradient sparse, quantitatively accurate, and minimally biased. We call this algorithm spectral diffusion because it integrates structural information from multiple spectral channels and their corresponding material decompositions within the framework of diffusion-like denoising algorithms (e.g. anisotropic diffusion, total variation, bilateral filtration). Using a 3D, digital bar phantom and a material sensitivity matrix calibrated for use with a polychromatic x-ray source, we quantify the limits of detectability (CNR = 5) afforded by spectral diffusion in the triple-energy material decomposition of iodine (3.1 mg mL(-1)), gold (0.9 mg mL(-1)), and gadolinium (2.9 mg mL(-1)) concentrations. We then apply spectral diffusion to the in vivo separation of these three materials in the mouse kidneys, liver, and spleen.

Micro-CT of rodents: state-of-the-art and future perspectives

Micron-scale computed tomography (micro-CT) is an essential tool for phenotyping and for elucidating diseases and their therapies. This work is focused on preclinical micro-CT imaging, reviewing relevant principles, technologies, and applications. Commonly, micro-CT provides high-resolution anatomic information, either on its own or in conjunction with lower-resolution functional imaging modalities such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). More recently, however, advanced applications of micro-CT produce functional information by translating clinical applications to model systems (e.g., measuring cardiac functional metrics) and by pioneering new ones (e.g. measuring tumor vascular permeability with nanoparticle contrast agents). The primary limitations of micro-CT imaging are the associated radiation dose and relatively poor soft tissue contrast. We review several image reconstruction strategies based on iterative, statistical, and gradient sparsity regularization, demonstrating that high image quality is achievable with low radiation dose given ever more powerful computational resources. We also review two contrast mechanisms under intense development. The first is spectral contrast for quantitative material discrimination in combination with passive or actively targeted nanoparticle contrast agents. The second is phase contrast which measures refraction in biological tissues for improved contrast and potentially reduced radiation dose relative to standard absorption imaging. These technological advancements promise to develop micro-CT into a commonplace, functional and even molecular imaging modality.