Matrix remodeling and cytological changes during spontaneous cartilage repair

During the repair of articular cartilage, type I collagen (COL1)-based fibrous tissues change into a mixture of COL1 and type II collagen (COL2) and finally form hyaline cartilaginous tissues consisting of COL2. In order to elucidate the changes that occur in the matrix during cartilage repair and the roles of fibroblasts and chondrocytes in this process, we generated a minimal cartilage defect model that could be spontaneously repaired. Defects of 0.3?mm were created on the patellofemoral articular cartilage of rats using an Er:YAG laser and were observed histologically, ultrastructurally and histochemically. At week 2 after this operation, fibroblastic cells were found to be surrounded by COL1 throughout the area of the defect. These cells became acid phosphatase positive by week 4, both taking in and degrading collagen fibrils. Thereafter, the cells became rounded, with both COL1 and 2 evident in the matrix, and showed immunolocalized matrix metalloproteinase-1 or -9. In the region of the bone marrow, the cells became hypertrophic and were surrounded mainly by COL2 and proteoglycans. By the eighth week, the cartilaginous matrix was found to contain abundant COL2, in which collagen fibrils of various diameters were arranged irregularly. These morphological changes suggested that the fibroblastic cells both produce and resolve the matrix and undertake remodeling to become chondrocytes by converting from a COL1- into a COL2-dominant matrix. This process eventually forms new articular cartilage, but this is not completely identical to normal articular cartilage at the ultrastructural level.     

Segmenting articular cartilage automatically using a voxel classification approach

We present a fully automatic method for articular cartilage segmentation from magnetic resonance imaging (MRI) which we use as the foundation of a quantitative cartilage assessment. We evaluate our method by comparisons to manual segmentations by a radiologist and by examining the interscan reproducibility of the volume and area estimates. Training and evaluation of the method is performed on a data set consisting of 139 scans of knees with a status ranging from healthy to severely osteoarthritic. This is, to our knowledge, the only fully automatic cartilage segmentation method that has good agreement with manual segmentations, an interscan reproducibility as good as that of a human expert, and enables the separation between healthy and osteoarthritic populations. While high-field scanners offer high-quality imaging from which the articular cartilage have been evaluated extensively using manual and automated image analysis techniques, low-field scanners on the other hand produce lower quality images but to a fraction of the cost of their high-field counterpart. For low-field MRI, there is no well-established accuracy validation for quantitative cartilage estimates, but we show that differences between healthy and osteoarthritic populations are statistically significant using our cartilage volume and surface area estimates, which suggests that low-field MRI analysis can become a useful, affordable tool in clinical studies.     

Quantitative and morphological observations on the ultrastructure of articular tissue generated from free periosteal grafts.

This study investigates the ultrastructure of articular tissue generated on osteochondral defects in skeletally immature rabbits from free reversed periosteal allografts after 50 and 100 days of post-operative intermittent active motion. Tissue samples prepared for transmission electron microscopy were compared with normal cartilage and periosteum in terms of cell morphology and the pattern of intercellular collagen deposition. Well-differentiated tissue demonstrated many ultrastructural features of normal articular cartilage while poorly differentiated samples contained cells and intercellular collagen profiles which were somewhat similar to those observed in periosteum.     

Dissociated and Reconstituted Cartilage Microparticles in Densified Collagen Induce Local hMSC Differentiation

Current use of decellularized articular cartilage as a regenerative platform suffers from limited implant diffusion characteristics and cellular infiltration. Attempts to address this concern using decellularized cartilage microparticles allow for customized implant shape, tailored porosity, and improved cell infiltration. However, these developments utilize severe crosslinking agents that adversely affect cell differentiation, and fail to attain clinically relevant mechanical properties required for the implant survival. These issues have been overcome through the formation of a composite approach, combining the advantages of mature, decellularized tissue with tunable features of a reconstituted collagen hydrogel system. Through the application of a plastic compression regime, cellularized composite structures are formed that exceeded the percolation threshold of the cartilage microparticles and exhibited clinically relevant mechanical properties. Chemical reduction and mechanical reconstitution methods to investigate the contributions of glycosaminoglycan and collagenous components to chondrogenic induction and matrix properties have been utilized. With the inclusion of human mesenchymal stem cells into the composite system, microenvironment‐dependent cell morphology and phenotype when in contact with cartilage microparticles are shown. This work demonstrates a cartilage microparticle composite matrix with clinically relevant mechanical properties, and chondrogenic differentiation of human mesenchymal stem that infiltrate both native and chemically reduced cartilage microparticles.     

3D Fiber‐Deposited Electrospun Integrated Scaffolds Enhance Cartilage Tissue Formation

Despite the periodical and completely interconnected pore network that characterizes rapid prototyped scaffolds, cell seeding efficiency remains still a critical factor for optimal tissue regeneration. This can be mainly attributed to the current resolution limits in pore size. We present here novel three‐dimensional (3D) scaffolds fabricated by combining 3D fiber deposition (3DF) and electrospinning (ESP). Scaffolds consisted of integrated 3DF periodical macrofiber and random ESP microfiber networks (3DFESP). The 3DF scaffold provides structural integrity and mechanical properties, while the ESP network works as a “sieving” and cell entrapment system and offers?at the same time?cues at the extracellular matrix (ECM) scale. Primary bovine articular chondrocytes were isolated, seeded, and cultured for four weeks on 3DF and 3DFESP scaffolds to evaluate the influence of the integrated ESP network on cell entrapment and on cartilage tissue formation. 3DFESP scaffolds enhanced cell entrapment as compared to 3DF scaffolds. This was accompanied by a higher amount of ECM (expressed in terms of sulphated glycosaminoglycans or GAG) and a significantly higher GAG/DNA ratio after 28 days. SEM analysis revealed rounded cell morphology on 3DFESP scaffolds. Spread morphology was observed on 3DF scaffolds, suggesting a direct influence of fiber dimensions on cell differentiation. Furthermore, the ESP surface topology also influenced cell morphology. Thus, the integration of 3DF and ESP techniques provide a new set of “smart” scaffolds for tissue engineering applications.     

Surface extraction and thickness measurement of the articular cartilage from MR images using directional gradient vector flow snakes

The accuracy of the surface extraction of magnetic resonance images of highly congruent joints with thin articular cartilage layers has a significant effect on the percentage errors and reproducibility of quantitative measurements (e.g., thickness and volume) of the articular cartilage. Traditional techniques such as gradient-based edge detection are not suitable for the extraction of these surfaces. This paper studies the extraction of articular cartilage surfaces using snakes, and a gradient vector flow (GVF)-based external force is proposed for this application. In order to make the GVF snake more stable and converge to the correct surfaces, directional gradient is used to produce the gradient vector flow. Experimental results show that the directional GVF snake is more robust than the traditional GVF snake for this application. Based on the newly developed snake model, an articular cartilage surface extraction algorithm is developed. Thickness is computed based on the surfaces extracted using the proposed algorithm. In order to make the thickness measurement more reproducible, a new thickness computation approach, which is called T-norm, is introduced. Experimental results show that the thickness measurement obtained by the new thickness computation approach has better reproducibility than that obtained by the existing thickness computation approaches.     

Unsupervised segmentation and quantification of anatomical knee features: data from the Osteoarthritis Initiative

This paper presents a fully automated method for segmenting articular knee cartilage and bone from in vivo 3-D dual echo steady state images. The magnetic resonance imaging (MRI) datasets were obtained from the Osteoarthritis Initiative (OAI) pilot study and include longitudinal images from controls and subjects with knee osteoarthritis (OA) scanned twice at each visit (baseline, 24 month). Initially, human experts segmented six MRI series. Five of the six resultant sets served as reference atlases for a multiatlas segmentation algorithm. The methodology created precise knee segmentations that were used to extract articular cartilage volume, surface area, and thickness as well as subchondral bone plate curvature. Comparison to manual segmentation showed Dice similarity coefficient (DSC) of 0.88 and 0.84 for the femoral and tibial cartilage. In OA subjects, thickness measurements showed test-retest precision ranging from 0.014 mm (0.6%) at the femur to 0.038 mm (1.6%) at the femoral trochlea. In the same population, the curvature test-retest precision ranged from 0.0005 mm(-1) (3.6%) at the femur to 0.0026 mm(-1) (11.7%) at the medial tibia. Thickness longitudinal changes showed OA Pearson correlation coefficient of 0.94 for the femur. In conclusion, the fully automated segmentation methodology produces reproducible cartilage volume, thickness, and shape measurements valuable for the study of OA progression.     

Analytical calculation of volumes-of-intersection for iterative, fully 3-D PET reconstruction

Use of iterative algorithms to reconstruct three-dimensional (3-D) positron emission tomography (PET) data requires the computation of the system probability matrix. The pure geometrical contribution can easily be approximated by the length-of-intersection (LOI) between lines-of-response (LOR) and individual voxels. However, more accurate geometrical projectors are desirable. Therefore, we have developed a fast method for the analytical calculation of the 3-D shape and volume of volumes-of-intersection (VOI). This method provides an alternative robust projector with a uniformly continuous sampling of the image space. The enhanced calculation effort is facilitated by using several speedup techniques. Exploiting intrinsic symmetry relations and the sparseness of the system matrix allows to create an efficiently compressed matrix which can be precomputed and completely stored in memory. In addition, a new voxel addressing scheme has been implemented. This scheme avoids time-consuming symmetry transformations of voxel addresses by using an octant-wise symmetrically ordered field of voxels. The above methods have been applied for a fully 3-D, iterative reconstruction of 3-D sinograms recorded with a Siemens/CTI ECAT HR+ PET scanner. A comparison of the performance of the reconstruction using LOI weighting and VOI weighting is presented.     

Monitoring osteoarthritis in the rat model using optical coherence tomography

OBJECTIVE: A need exists for an animal model to assess therapeutics for osteoarthritis (OA) without sacrificing the animal. Our goal is to assess the progression of experimentally induced osteoarthritis in the rat knee joint by monitoring articular cartilage thickness, surface abnormalities, and collagen organization using a new technology known as optical coherence tomography (OCT). DESIGN: OA was generated in Wistar Hanover rats via injection of sodium iodoacetate into the left articular joint of the knee while normal saline was injected as a control in the contralateral right knee. Rats were sacrificed at 1-, 2-, 3-, 4-, and 8-week intervals and the knee joints were subsequently harvested and imaged using normal and polarization sensitive OCT (PS-OCT). Treated knees were compared to normal counterparts in the contralateral leg. Following imaging, knees underwent both routine histological processing and picrosirus staining for organized collagen. RESULTS: OCT images indicate that injection of sodium iodoacetate resulted in a progressive decrease in cartilage thickness and loss of the bone-cartilage interface which correlated with histology. In addition, PS-OCT was able to detect collagen disorganization, an early indicator of OA. CONCLUSIONS: The use of OCT in combination with the induction of OA in rats is a promising new animal model for assessing articular changes with the goal of monitoring therapeutics longitudinally. Future work will extend the model to in vivo assessments.     

Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model

The primary objective of this study was to develop a computer-aided method for the quantification of three-dimensional (3-D) cartilage changes over time in knees with osteoarthritis (OA). We introduced a local coordinate system (LCS) for the femoral and tibial cartilage boundaries that provides a standardized representation of cartilage geometry, thickness, and volume. The LCS can be registered in different data sets from the same patient so that results can be directly compared. Cartilage boundaries are segmented from 3-D magnetic resonance (MR) slices with a semi-automated method and transformed into offset-maps, defined by the LCS. Volumes and thickness are computed from these offset-maps. Further anatomical labeling allows focal volumes to be evaluated in predefined subregions. The accuracy of the automated behavior of the method was assessed, without any human intervention, using realistic, synthetic 3-D MR images of a human knee. The error in thickness evaluation is lower than 0.12 mm for the tibia and femur. Cartilage volumes in anatomical subregions show a coefficient of variation ranging from 0.11% to 0.32%. This method improves noninvasive 3-D analysis of cartilage thickness and volume and is well suited for in vivo follow-up clinical studies of OA knees.     

Mechanisms and Microenvironment Investigation of Cellularized High Density Gradient Collagen Matrices via Densification

Biological tissues and biomaterials are often defined by unique spatial gradients in physical properties that impart specialized function over hierarchical scales. The structure of these materials forms continuous transitional gradients and discrete local microenvironments between adjacent (or within) tissues, and across matrix–cell boundaries, which is difficult to replicate with common scaffold systems. Here, the matrix densification of collagen leading to gradients in density, mechanical properties, and fibril morphology is studied. High‐density regions form via a fluid pore pressure and flow‐driven mechanism, with increased relative fibril density (10×), mechanical properties (20×, to 94.40 ± 18.74 kPa), and maximum fibril thickness (1.9×, to >1 μm) compared to low‐density regions, while maintaining porosity and fluid/mass transport to support viability of encapsulated cells. Similar to the organization of the articular cartilage zonal structure, it is found that high‐density collagen regions induce cell and nuclear alignment of primary chondrocytes. Chondrocyte gene expression is maintained in collagen matrices, and no phenotypic changes are observed as a result of densification. Collagen densification provides a tunable platform for the creation of gradient systems to study complex cell–matrix interactions. These methods are easily generalized to compression and boundary condition modalities useful to mimic a broad range of tissues.     

Web-Based Multilayer Viewing Interface for Knee Cartilage

Many adults suffer from osteoarthritis (OA) with the majority of people over 65 showing radiographic evidence of the disease. To carry out effective diagnosis and treatment, it is necessary to understand the progression of cartilage loss and study the effectiveness of therapeutic interventions. Hence, it is important to have accurate, fast diagnosis of the disease. In this paper, we describe a Web-based user interface that enables the direct viewing of 2-D and 3-D image data from the visceral and tissue levels of the biological continuum (i.e., the continuum comprising systems, viscera, tissue, cells, proteins, and genes)–-while preserving geometric integrity. This is achieved despite the fact that the data are from different modalities (i.e., magnetic resonance (MR) and light microscopy). The user interface was tested using image data acquired from a study of articular cartilage thickness in the porcine knee. The interface allows the clinician to view both MR and light microscopy images in an integrated manner—with the information linked geometrically.      

空间通信应用的微波功率模块

由半导体器件、电真空器件和微组装电源构成的微波功率模块(MPM)已成为构建各种军用电子装备和民用系统的基本单元。MPM的技术正在向空间应用领域扩展。本文将讨论有关空间MPM研制的若干问题。     

3维荧光光谱测定白酒年份酒中乙酸的体积分数

为了快速测定白酒年份酒中乙酸的体积分数，采用3维荧光光谱结合交替拟合残差算法，首先将不同体积分数的乙酸乙醇水溶液的3维荧光光谱作为校正集，然后将白酒的3维荧光光谱作为预测集，利用交替拟合残差算法进行解析分辨，采用标准添加法来验证结果的准确性。结果表明，预测体积分数与真实体积分数的相关系数为0.9926，平均回收率为101.97%；3维荧光光谱结合交替拟合残差算法可以快速有效地测定白酒年份酒中乙酸的体积分数。这一结果对白酒年份酒中单体体积分数的检测是有帮助的。     

A Layered Finite Element Method for Electromagnetic Analysis of Large-Scale High-Frequency Integrated Circuits

A high-capacity electromagnetic solution, layered finite element method, is proposed for high-frequency modeling of large-scale three-dimensional on-chip circuits. In this method, first, the matrix system of the original 3-D problem is reduced to that of 2-D layers. Second, the matrix system of 2-D layers is further reduced to that of a single layer. Third, an algorithm of logarithmic complexity is proposed to further speed up the analysis. In addition, an excitation and extraction technique is developed to limit the field unknowns needed for the final circuit extraction to a single layer only, as well as keep the right-hand side intact during the matrix reduction process. The entire procedure is numerically rigorous without making any theoretical approximation. The computational complexity only involves solving a single layer irrespective of the original problem size. Hence, the proposed method is equipped with a high capacity to solve large-scale IC problems. The proposed method was used to simulate a set of large-scale interconnect structures that were fabricated on a test chip using conventional Si processing techniques. Excellent agreement with the measured data has been observed from dc to 50 GHz     

微波功率模块——雷达发射机的新型功率器件

微波功率模块(MPM)是80年代末提出的一种新概念的功率器件。它有效地把固态器件与真空器件的优点有机地结合在一起,为雷达、电子战、通讯、精密制导等领域提供了关键的功率器件。本文侧重于微波功率模块的基本知识的介绍。     

低强度激光对软骨胶原合成和细胞增殖影响

研究了810 nm低强度Ga-Al-As半导体激光对兔软骨细胞增殖和胶原合成的影响.取新西兰白兔的关节软骨细胞,用浓度为2%的新生牛血清(NCS)培养媒介培养.激光功率密度分别为1.75、3.50、5.25、7.00和8.75 mW/cm2,以连续方式每天照射软骨细胞5 min,共5 d.分别用四甲基氮唑盐(MTT)法和氯胺T消化法检测细胞的增殖和胶原蛋白合成.结果发现:第8天实验结束时,各激光照射组细胞数量随激光强度线性增加,与无激光照射组的差异有统计学意义(P＜0.01),其中最佳照射功率密度为7.00 mW/cm2;第8天实验结束时,激光照射组胶原含量显著低于对照组(P＜0.01),8.75 mW/cm2组与3.50～7.00 mW/cm2组有显著差异(P＜0.05).激光照射7.00 mW/cm2组与对照组第2、4、6和8天胶原含量的测定表明,照射组胶原含量先增加后降低,其中第6天照射组胶原含量最高,与相应对照组有极显著差异(P＜0.01),对照组胶原含量在第6天后急剧增加,第8天与照射组有极显著差异(P＜0.01).研究结果表明,低强度Ga-Al-As半导体激光能促进兔关节软骨细胞的生长,有望成为临床治疗软骨损伤的一种有效方法.     

Estimation of dynamically evolving ellipsoids with applications to medical imaging

The estimation of dynamically evolving ellipsoids from noisy lower-dimensional projections is examined. In particular, this work describes a model-based approach using geometric reconstruction and recursive estimation techniques to obtain a dynamic estimate of left-ventricular ejection fraction from a gated set of planar myocardial perfusion images. The proposed approach differs from current ejection fraction estimation techniques both in the imaging modality used and in the subsequent processing which yields a dynamic ejection fraction estimate. For this work, the left ventricle is modeled as a dynamically evolving three-dimensional (3-D) ellipsoid. The left-ventricular outline observed in the myocardial perfusion images is then modeled as a dynamic, two-dimensional (2-D) ellipsoid, obtained as the projection of the former 3-D ellipsoid. This data is processed in two ways: first, as a 3-D dynamic ellipsoid reconstruction problem; second, each view is considered as a 2-D dynamic ellipse estimation problem and then the 3-D ejection fraction is obtained by combining the effective 2-D ejection fractions of each view. The approximating ellipsoids are reconstructed using a Rauch-Tung-Striebel smoothing filter, which produces an ejection fraction estimate that is more robust to noise since it is based on the entire data set; in contrast, traditional ejection fraction estimates are based only on true frames of data. Further, numerical studies of the sensitivity of this approach to unknown dynamics and projection geometry are presented, providing a rational basis for specifying system parameters. This investigation includes estimation of ejection fraction from both simulated and real data.     

Smart Biomaterials for Articular Cartilage Repair and Regeneration

Articular cartilage defects bring about disability and worldwide socioeconomic loss, therefore, articular cartilage repair and regeneration is recognized as a global issue. However, due to its avascular and nearly acellular characteristic, cartilage tissue regeneration ability is limited to some extent. Despite the availability of various treatment methods, including palliative drugs and surgical regenerative therapy, articular cartilage repair and regeneration still face major challenges due to the lack of appropriate methods and materials. Smart biomaterials can regulate cell behavior and provide excellent tissue repair and regeneration microenvironment, thus inducing articular cartilage repair and regeneration. This process is adjusted by controlling drug/bioactive factors release via responding to exogenous/endogenous stimuli, tailoring materials’ structure and function similar to native cartilage or providing physiochemical and physical signaling factors. Herein, smart biomaterials, recently applied in articular cartilage repair and regeneration, are elaborated from two aspects: smart drug release system and smart scaffolds. Furthermore, articular cartilage and its defects and advanced manufacturing techniques of smart biomaterials are discussed in brief. Finally, perspectives for smart biomaterials used in articular cartilage repair and regeneration are presented and the clinical translation of smart biomaterials is emphasized.     

Model-based automated extraction of microtubules from electron tomography volume.

We propose a model-based automated approach to extracting microtubules from noisy electron tomography volume. Our approach consists of volume enhancement, microtubule localization, and boundary segmentation to exploit the unique geometric and photometric properties of microtubules. The enhancement starts with an anisotropic invariant wavelet transform to enhance the microtubules globally, followed by a three-dimensional (3-D) tube-enhancing filter based on Weingarten matrix to further accentuate the tubular structures locally. The enhancement ends with a modified coherence-enhancing diffusion to complete the interruptions along the microtubules. The microtubules are then localized with a centerline extraction algorithm adapted for tubular objects. To perform segmentation, we novelly modify and extend active shape model method. We first use 3-D local surface enhancement to characterize the microtubule boundary and improve shape searching by relating the boundary strength with the weight matrix of the searching error. We then integrate the active shape model with Kalman filtering to utilize the longitudinal smoothness along the microtubules. The segmentation improved in this way is robust against missing boundaries and outliers that are often present in the tomography volume. Experimental results demonstrate that our automated method produces results close to those by manual process and uses only a fraction of the time of the latter.