Organic Nanoplatforms for Iodinated Contrast Media in CT Imaging

X-ray computed tomography (CT) imaging can produce three-dimensional and high-resolution anatomical images without invasion, which is extremely useful for disease diagnosis in the clinic. However, its applications are still severely limited by the intrinsic drawbacks of contrast media (mainly iodinated water-soluble molecules), such as rapid clearance, serious toxicity, inefficient targetability and poor sensitivity. Due to their high biocompatibility, flexibility in preparation and modification and simplicity for drug loading, organic nanoparticles (NPs), including liposomes, nanoemulsions, micelles, polymersomes, dendrimers, polymer conjugates and polymeric particles, have demonstrated tremendous potential for use in the efficient delivery of iodinated contrast media (ICMs). Herein, we comprehensively summarized the strategies and applications of organic NPs, especially polymer-based NPs, for the delivery of ICMs in CT imaging. We mainly focused on the use of polymeric nanoplatforms to prolong circulation time, reduce toxicity and enhance the targetability of ICMs. The emergence of some new technologies, such as theragnostic NPs and multimodal imaging and their clinical translations, are also discussed.     

频域近红外光学成像法的苹果内部病变检测精度

苹果组织内部的病变会导致其光学参数发生变化。用频域近红外光学成像法（FD-DOT）对苹果组织进行吸收系数和约化散射系数的检测,并结合三维重构技术得到的重构图像可以直观地了解苹果内部的病变情况,从而实现对苹果内部病变的无损检测。选择可最大程度区分苹果正常组织与病变组织所对应的波长为740 nm的光作为激光光源。当FD-DOT的入射光调制频率不同、苹果内部病变的程度不同、病变位置和大小不同时,会导致成像精度的变化,设计了一系列模拟仿真实验研究以上因素对苹果内部病变检测精度的影响：设定不同的激光调制频率,研究调制频率对重构图像精度的影响;在苹果模型中某一位置添加不同大小的球形病变,研究病变区域大小对重构图像精度的影响;在苹果模型中不同位置添加一定大小的异质体,研究病变位置不同对重构图像精度的影响。首先用Abaqus建立苹果有限元网格模型,设计了12个740 nm的近红外激光光源和6个检测器均匀排布在苹果模型表面,根据实验需要,在组织体模型中添加代表病变的球形异质体,用经过高频调制的光源照射进苹果,检测出射光的交流幅度和相位延迟,然后借助开源软件NIRFAST计算并反推出待测苹果内部的吸收系数和约化散射系数分布并进行三维重构,重构结果可以用重构图像的吸收系数对比度噪声比（CNR值）和吸收系数分布图进行评价。实验结果表明,想要检测到尺寸较大苹果的深处病变,需要较高的入射光调制频率;该方法可以检测到大小适宜的苹果中大部分半径大于5 mm的球形病变区域,且随着病变区域在一定范围内扩大,重构图像的精度逐渐增加,但病变区域过大时,图像精度开始降低;病变区域距离检测器越来越近时,重构图像的精度逐渐增加,但当病变区域与检测器距离过小时,重构图像的精度有降低的趋势;病变区域距离检测器平面的垂直距离越近,重构图像的精度越高。以上实验结果将为应用频域近红外光学成像法对苹果进行无损检测奠定良好基础。     

Flame propagation speed and Markstein length of spherically expanding flames: Assessment of extrapolation and measurement techniques

Laminar burning velocities are of great importance in many combustion models as well as for validation and improvement of chemical kinetic schemes. Determining laminar burning velocities with high accuracy is quite challenging and different approaches exist. Hence, a comparison of existing methods measuring and evaluating laminar burning velocities is of interest. Here, two optical diagnostics, high speed tomography and Schlieren cinematography, are simultaneously set up to investigate methods for evaluating laminar flame speed in a spherical flame configuration. The hypothesis to obtain the same flame propagation radii over time with the two different techniques is addressed. Another important aspect is the estimation of flame properties, such as the unstretched flame propagation speed and Markstein length in the burnt gas phase and if these are estimated satisfactorily by common experimental approaches. Thorough evaluation of the data with several extrapolation techniques is undertaken. A systematic extrapolation approach is presented to give more confidence into results generated experimentally. The significance of the linear extrapolation routine is highlighted in this context. Measurements of spherically expanding flames are carried out in two high-pressure, high-temperature, constant-volume vessels at RWTH in Aachen, Germany and at ICARE in Orleans, France. For the discussion of the systematic extrapolation approach, flame speed measurements of methane / air mixtures with mixture Lewis numbers moderately away from unity are used. Conditions were varied from lean to rich mixtures, at temperatures of 298–373 K, and pressures of 1 atm and 5 bar.     

Experimental investigation on the flame front resistance of gas channel growth with melt formation in iron ore sinter beds

The resistance of the flame front within the solid bed constitutes a fundamental and crucial area in porous bed combustion as the flame front propagation is highly related to the productivity and product quality. This paper focuses on the iron ore sintering, a thermal agglomeration process in steel mills. The results from a detailed experimental study of the pilot-scale pot tests under the conditions of a wide range of fuel rate are presented. The primary objective is to provide better understanding of the growth of gas channels relating to melt formation in the flame front and its resistance to flow. The sintering bed was divided into several zones based on the temperature profile and component distribution. Even though there is a continuous one-to-one replacement of humidified zone with porous sintered zone, a constant air flow rate during sintering could be obtained, indicating the ～100?mm high-temperature zone has a controlling effect on sintering bed permeability. The specific pressure drop value in high-temperature zone increases from ～3?kPa in upper bed to ～7?kPa in bottom bed, which varies with the bed temperature and structure properties. Both the green bed and sintered bed were scanned by X-ray computed tomography, the reconstruction and image analysis showed that the sintered bed has large gas channels and many more closed pores due to solid-melt-gas coalescence. More melt is generated when the heat is accumulated along the bed or input higher coke content, showing a propensity to suppress the gas channel growth and amplify the mismatch of gas transportation along the bed. Higher coke rate leads to a higher resistance in flame front, resulting in a slower flame front speed. These results are aimed to provide quantitative validation for improvements of a numerical sintering model in a future work.     

Insight into 3D micro‐CT data: exploring segmentation algorithms through performance metrics

Three‐dimensional (3D) micro‐tomography (µ‐CT) has proven to be an important imaging modality in industry and scientific domains. Understanding the properties of material structure and behavior has produced many scientific advances. An important component of the 3D µ‐CT pipeline is image partitioning (or image segmentation), a step that is used to separate various phases or components in an image. Image partitioning schemes require specific rules for different scientific fields, but a common strategy consists of devising metrics to quantify performance and accuracy. The present article proposes a set of protocols to systematically analyze and compare the results of unsupervised classification methods used for segmentation of synchrotron‐based data. The proposed dataflow for Materials Segmentation and Metrics (MSM) provides 3D micro‐tomography image segmentation algorithms, such as statistical region merging (SRM), k‐means algorithm and parallel Markov random field (PMRF), while offering different metrics to evaluate segmentation quality, confidence and conformity with standards. Both experimental and synthetic data are assessed, illustrating quantitative results through the MSM dashboard, which can return sample information such as media porosity and permeability. The main contributions of this work are: (i) to deliver tools to improve material design and quality control; (ii) to provide datasets for benchmarking and reproducibility; (iii) to yield good practices in the absence of standards or ground‐truth for ceramic composite analysis.     

A convolutional neural network approach to calibrating the rotation axis for X‐ray computed tomography

This paper presents an algorithm to calibrate the center‐of‐rotation for X‐ray tomography by using a machine learning approach, the Convolutional Neural Network (CNN). The algorithm shows excellent accuracy from the evaluation of synthetic data with various noise ratios. It is further validated with experimental data of four different shale samples measured at the Advanced Photon Source and at the Swiss Light Source. The results are as good as those determined by visual inspection and show better robustness than conventional methods. CNN has also great potential for reducing or removing other artifacts caused by instrument instability, detector non‐linearity, etc. An open‐source toolbox, which integrates the CNN methods described in this paper, is freely available through GitHub at tomography/xlearn and can be easily integrated into existing computational pipelines available at various synchrotron facilities. Source code, documentation and information on how to contribute are also provided.     

Artifact Reduction Based on Sinogram Interpolation for the 3D Reconstruction of Nanoparticles Using Electron Tomography

Electron tomography is a well‐known technique providing a 3D characterization of the morphology and chemical composition of nanoparticles. However, several reasons hamper the acquisition of tilt series with a large number of projection images, which deteriorate the quality of the 3D reconstruction. Here, an inpainting method that is based on sinogram interpolation is proposed, which enables one to reduce artifacts in the reconstruction related to a limited tilt series of projection images. The advantages of the approach will be demonstrated for the 3D characterization of nanoparticles using phantoms and several case studies.     

Reconstruction of Smoke Plume Concentration Peaks Based on Modified MAX-DOAS Tomography

Optical tomography system based on modified simultaneous iterative reconstruction tech-nique is designed to real-time monitor spatial distribution and diffusion process of smoke plume in a power plant. Concentration profiles, rather than just a point value, of smoke plume concentrations are the goal of this method, and the tomography algorithm is ana-lyzed. According to incomplete projection data in the process of reconstruction and exiting noise interference, the modified simultaneous iterative reconstruction technique (SIRT) is adopted to extract the information of the trace gas concentration by a fan beam scanning and is compared to the conventional SIRT. Three evaluation indexes show that the recon-struction effect is the best by choosing proper relaxation factor, which reduces the index d to 0.044 from 0.435 and reduces the index r to 0.044 from 0.376 for 5500 iterations. Hence, the modified algorithm performs better in estimating the shape of the plume, this method is used to process the measured spectra in field campaign, the reconstruction results and the measured data are basically consistent, which is further confirmed by the experimental results.     

光学相干层析术提取色散信息的初步研究

为了提取生物组织的色散信息,提出了一种基于Fourier变换以及多项式拟合的方法.该方法通过对光学相干层析术的干涉包络进行Fourier变换,再将得到的相位谱进行多项式拟合以实现色散信息的提取.通过数值模拟及相关实验验证了该方法的可行性.本文的分析结果不但有助于实现动态的色散补偿,而且可以用于区分不同的生物组织,以及同一生物组织的不同生理状态.     

光学多普勒层析三维矢量测速方法研究

光学多普勒层析术(ODT)是一种高分辨、非侵入的生物医学成像手段,能同时得到组织的结构信息和组织内血管的流速信息.提出了一种新型的基于相位分辨技术的ODT三维矢量测速方法.在ODT系统样品臂的准直镜和聚焦透镜之间加入窄带相位片,形成三个不同的相位延迟,通过计算多普勒频移和不同相位延迟下的多普勒展宽,可得到毛细管内的三维矢量流场分布.对已知浓度的聚苯乙烯溶液进行了一系列不同角度和不同流速的实验,结果证明这种新型的ODT矢量测速方法可以较精确的实现三维矢量流速的测量.