Three-dimensional (3-D) imaging of chondrocytes in articular cartilage: Growth-associated changes in cell organization

Abstract

Three-dimensional (3-D) imaging and analysis techniques can be used to assess the organization of cells in biological tissues, providing key insights into the role of cell arrangement in growth, homeostasis, and degeneration. The objective of the present study was to use such methods to assess the growth-related changes in cell organization of articular cartilage from different sites in the bovine knee. Three-dimensional images of fetal, calf, and adult cartilage were obtained and processed to identify cell nuclei. The density of cells was lower with growth and with increasing depth from the articular surface. The cell organization, assessed by the angle to the nearest neighboring cell, also varied with growth, and reflected the classical organization of cells in adult tissue, with neighboring cells arranged horizontally in the superficial zone (average angle of 20°) and vertically in the deep zone (60°). In all other regions and growth stages of cartilage, the angle was ∼32°, indicative of an isotropic organization. On the contrary, the nearest neighbor distance did not vary significantly with growth or depth. Together, these results indicate that cartilage growth is associated with distinctive 3-D arrangements of groups of chondrocytes.

Introduction

A variety of biomaterial scaffolds have been introduced in tissue engineering in an effort to induce repair or regeneration after damage or disease. Such materials have been employed to harbor cells and tissues and to guide tissue formation either in vitro or in vivo. The microstructure and biological activity of the scaffold dictate the formation of tissue by regulating cell infiltration and cell activities. Scaffold features, such as pore size, attachment sites, and fluid channels, may be of critical importance in organizing cells, and, subsequently, generating tissue with structural and functional properties effective for use as a replacement tissue.

The organization of cells into groups often dictates their behavior in functional subunits [1] within tissues. Such organization can affect cells through their regulation, via direct cell–cell contact, and paracrine and autocrine factors. Such organization can also affect the local solid and fluid mechanical environment in which the cells reside, when exposed to external mechanical or chemical stimuli. Thus, it would be useful to assess the precise three-dimensional (3-D) organization of cells within native and engineered tissues, as well as biomaterial grafts after cellular infiltration following an in vivo implantation. Such analysis of 3-D cell organization would also be relevant to the study the cell organization in tissues during development, such as in genetically manipulated animals, and during disease progression and treatment.

Biomedical imaging techniques are used frequently to characterize the changing microstructure of biological tissues at various stages of development, growth, aging, injury, and disease. Often, the constituent cells are of interest because of their role in mediating tissue formation, repair and degeneration. The changing function of a population of cells may be reflected by the changes in their organization. Thus, delineation of cell organization may lead to a tissue-scale understanding of cell-guided formation, responses to injury, and degradation. This paper provides a brief review of imaging techniques used to examine cells in a 3-D environment, and then describes an investigation of changes in cell organization in the context of articular cartilage development and growth by analysis of fetal, calf, and adult tissue.

The traditional method of assessing the organization of groups of cells in tissue has been by analysis of thin sections with 2-D light microscopy. Using such 2-D images, stereological analysis has evolved to allow for unbiased estimation of cell morphology and number per volume [2], [3], [4], [5]. In the case of quantifying cell number per volume, new cells are counted in sequential image sections and the number divided by the total volume of tissue inspected. These procedures have proven useful in tabulating depth-varying cellularity in articular cartilage [3], [5]. However, evaluation of higher levels of cell organization is difficult because cells are not spatially localized in these procedures and sample thickness may not be large enough to identify entire clusters of cells.

Three-dimensional imaging and image processing modalities have been used to directly analyze cell organization within tissues. Laser-scanning confocal microscopy allows for the capture of 3-D tissue features stained with specific fluorescent probes by using pinhole apertures to exclude the excitation beam and collect fluorescence from a thin (in the z direction) optical section [6]. More recently, two-photon excitation laser scanning confocal microscopy has been employed on a variety of tissues, and can detect endogenous fluorophores excited by absorption of two-photons of twice the wavelength (half the energy) that is normally needed for excitation [7]. Using this technique, cellular components can be visualized to a depth of up to several hundred microns. Another technique, optical coherence tomography, uses a different strategy to collect a series of z data at a single x–y point in combination with scanning in the x–y plane to form a 3-D image [8]. In this technique, broadband light is split and passed into the tissue sample and an adjustable path length reference mirror, and the magnitude of the interference between the light reflected from these two targets represents the image intensity. This technique is in contrast to a newer approach, Optical projection tomography, in which a series of images are collected from different angles, either of transmitted brightfield light, or by emitted fluorescence signal from excited molecules [9]. Using this method, a 3-D image is formed by mathematical reconstruction of the series of views from 0° to 360°, with algorithms similar to those used in micro-computed tomography. This method has the potential to resolve groups of stained molecules (either fluorescent or colorimetric) on the cellular level, up to a depth of 1 cm.

Finally, methods have been developed to obtain a 3-D image by reconstruction of serial images acquired using sequential imaging and physical sectioning. Using one such technique, brain tissue was imaged at a surface using two-photon laser scanning confocal microscopy, and then laser-ablated to expose the next deeper layer [10]. This process was repeated to form a 3-D image with high resolution achieved by two-photon confocal microscopy, and size sufficient to visualize 3-D structures on the millimeter length scale. In another commercial procedure, called digital volumetric imaging (DVI), 2-D images of a tissue surface are captured using conventional fluorescence microscopy, and thin sections are sequentially removed by a diamond knife microtome [11]. This procedure involves (A) fluorescence staining and fixation of tissue and embedding with an opacified polymer, (B) automated serial sectioning and imaging through a 3-D tissue block, and (C) post-processing for viewing the image data and extracting image features. In the plane (x–y) of sectioning, resolution and field of view are determined by the objective lens and imaging camera. In the depth (z-axis) direction, resolution is determined by section thickness (with opacity of the polymer matched to achieve a surface measure), and the number of z-sections is effectively unlimited. This technique was originally developed using specific fluorescent markers for cell nuclei (Acridine Orange) and extracellular matrix (Eosin-Y), and its capability may be extended to identify cell subpopulations with distinct phenotypes by incorporation of more specific fluorescent markers such as tagged antibodies. Recent studies have demonstrated the accuracy of DVI imaging (versus confocal imaging) [12], and the efficacy in quantifying the depth-varying organization of cells in conjunction with validated image processing routines, with high sensitivity and specificity, in bovine articular cartilage at different stages of growth [13]. The current study uses these DVI methods to localize cells in a series of samples from animals at distinct growth stages, and to analyze cell organization by computing novel metrics of distance and angle from each cell to neighboring cells.

Articular cartilage undergoes substantial growth and functional maturation between the time of joint cavitation and attainment of skeletal maturity [14]. The organization of chondrocytes in cartilage reflects, and may contribute to, articular cartilage dynamics during fetal development, post-natal growth, and skeletal maturity [15]. In particular, the decrease in cell density during growth may result from the separation of the cells from each other due to accretion of extracellular matrix molecules. The relatively high density of evenly spaced chondrocytes in immature tissue are arranged favorably to actively deposit and remodel nearby extracellular matrix, essential to tissue growth and maturation. The higher density of cells, and tight vertical packing of horizontally-oriented clusters of cells, near the articular surface [16], may enhance growth in this region. On the other hand, in mature articular cartilage, the low density of cells together with their clustering leads to regions of tissue relatively far from the nearest cells. This structure may predispose tissue to ineffective remodeling and repair and make it highly susceptible to structural and functional deterioration. This effect may be exacerbated in the deeper tissue regions, where cells are sparsely arranged in vertical columns [17]. Analysis of the depth-variation in cell organization at different stages of growth and maturation allows further understanding of the role of the indwelling cells in articular cartilage growth and homeostasis.

In immature articular cartilage, the population of cells is situated to contribute to a highly anabolic state of tissue growth. From previous 3-D analysis of cell locations in immature tissue, a large proportion of the tissue is within ∼10 μm of the nearest cell [13], within the distance over which a cell can actively metabolize proteoglycan molecules [18]. This proximity to tissue results from both the high density of chondrocytes, as well as their arrangement. Near the articular surface, horizontal clusters of tightly packed, flattened chondrocytes are observed, whereas deeper in the tissue, cells are less dense but have a more homogeneous arrangement [17]. The way in which the cells reach this arrangement is not known; however, the increase in the distance between cells with growth suggests that accretion of extracellular matrix may be pushing cells apart, while the closely situated and horizontally oriented cell groups at the articular surface may be generated by cell proliferation. Recently, proliferating chondrocytes have been identified near the articular surface of immature tissue [19], [20], [21], [22], [23], as have progenitor or stem cells [24], [25], [26], [27]. The organization of cells in immature tissue is likely to facilitate a high rate of tissue growth, and the position of cells relative to one another may provide insight into key features of growth, such as matrix accretion and cell proliferation.

Upon maturation, the cartilage attains a classical cell organization that is associated with maintenance of tissue homeostasis [17]. In particular, cell density decreases with depth from the articular surface [5], [28], [29], and cells are arranged into characteristic groups ranging from horizontal clusters at the surface to vertical columns in the deep regions [5], [16], [17]. Previous studies have also found that the cell density varies across the joint surface, and may depend on the magnitude of load which it bears [3], [30]. Thus, the intrinsic and extrinsic cellular cues may be different across a joint surface and lead to variable growth and evolution of distinct cell groups. The progression of articular cartilage cell organization to the final heterogeneous state may be better understood by quantifying the local organization of cells and cell groups as a function of depth and joint site at a sequence of developmental stages.

We recently described a 3-D histological method for determining the location of chondrocytes in cartilage in conjunction with DVI [13]. Although the study focused on determining cellularity in 3-D image data sets, these methodologies could be extended to other higher-order metrics of chondrocyte organization, particularly the relative arrangements of small groups of cells. 3-D imaging and image processing techniques could be applied to quantify features of cell organization, and assess the variation with growth.

The objective of the present study was to use DVI imaging and 3-D image processing methods in order to quantify the cellularity and local organization of cells in bovine articular cartilage, as a function of depth from the surface, at different stages of growth, both for the weight-bearing femoral condyle (FC) and the intermittently loaded patellofemoral groove (PFG).