Elastic Moduli of Collagen Gels Can Be Predicted from Two-Dimensional Confocal Microscopy

We quantitatively compare data obtained from imaging two-dimensional slices of three-dimensional unlabeled and fluorescently labeled collagen gels with confocal reflectance microscopy (CRM) and/or confocal fluorescence microscopy (CFM). Different network structures are obtained by assembling the gels over a range of concentrations at various temperatures. Comparison between CRM and CFM shows that the techniques are not equally sensitive to details of network structure, with CFM displaying higher fidelity in imaging fibers parallel to the optical axis. Comparison of CRM of plain and labeled collagen gels shows that labeling itself induces changes in gel structure, chiefly through inhibition of fibril bundling. Despite these differences, image analyses carried out on two-dimensional CFM and CRM slices of collagen gels reveal identical trends in structural parameters as a function of collagen concentration and gelation temperature. Fibril diameter approximated from either CRM or CFM is in good accord with that determined via electron microscopy. Two-dimensional CRM images are used to show that semiflexible polymer theory can relate network structural properties to elastic modulus successfully. For networks containing bundled fibrils, it is shown that average structural diameter, rather than fibril diameter, is the length scale that sets the magnitude of the gel elastic modulus.     

Collagen I Self-Assembly: Revealing the Developing Structures that Generate Turbidity

Type I collagen gels are routinely used in biophysical studies and bioengineering applications. The structural and mechanical properties of these fibrillar matrices depend on the conditions under which collagen fibrillogenesis proceeds, and developing a fuller understanding of this process will enhance control over gel properties. Turbidity measurements have long been the method of choice for monitoring developing gels, whereas imaging methods are regularly used to visualize fully developed gels. In this study, turbidity and confocal reflectance microscopy (CRM) were simultaneously employed to track collagen fibrillogenesis and reconcile the information reported by the two techniques, with confocal fluorescence microscopy (CFM) used to supplement information about early events in fibrillogenesis. Time-lapse images of 0.5 mg/ml, 1.0 mg/ml, and 2.0 mg/ml acid-solubilized collagen I gels forming at 27°C, 32°C, and 37°C were collected. It was found that in situ turbidity measured in a scanning transmittance configuration was interchangeable with traditional turbidity measurements using a spectrophotometer. CRM and CFM were employed to reveal the structures responsible for the turbidity that develops during collagen self-assembly. Information from CRM and transmittance images was collapsed into straightforward single variables; total intensity in CRM images tracked turbidity development closely for all collagen gels investigated, and the two techniques were similarly sensitive to fibril number and dimension. Complementary CRM, CFM, and in situ turbidity measurements revealed that fibril and network formation occurred before substantial turbidity was present, and the majority of increasing turbidity during collagen self-assembly was due to increasing fibril thickness.     

Rapid Quantification of 3D Collagen Fiber Alignment and Fiber Intersection Correlations with High Sensitivity

Metastatic cancers aggressively reorganize collagen in their microenvironment. For example, radially orientated collagen fibers have been observed surrounding tumor cell clusters in vivo. The degree of fiber alignment, as a consequence of this remodeling, has often been difficult to quantify. In this paper, we present an easy to implement algorithm for accurate detection of collagen fiber orientation in a rapid pixel-wise manner. This algorithm quantifies the alignment of both computer generated and actual collagen fiber networks of varying degrees of alignment within 5°°. We also present an alternative easy method to calculate the alignment index directly from the standard deviation of fiber orientation. Using this quantitative method for determining collagen alignment, we demonstrate that the number of collagen fiber intersections has a negative correlation with the degree of fiber alignment. This decrease in intersections of aligned fibers could explain why cells move more rapidly along aligned fibers than unaligned fibers, as previously reported. Overall, our paper provides an easier, more quantitative and quicker way to quantify fiber orientation and alignment, and presents a platform in studying effects of matrix and cellular properties on fiber alignment in complex 3D environments.     

Imaging of Scleral Collagen Deformation Using Combined Confocal Raman Microspectroscopy and Polarized Light Microscopy Techniques

This work presents an optospectroscopic characterization technique for soft tissue microstructure using site-matched confocal Raman microspectroscopy and polarized light microscopy. Using the technique, the microstructure of soft tissue samples is directly observed by polarized light microscopy during loading while spatially correlated spectroscopic information is extracted from the same plane, verifying the orientation and arrangement of the collagen fibers. Results show the response and orientation of the collagen fiber arrangement in its native state as well as during tensile and compressive loadings in a porcine sclera model. An example is also given showing how the data can be used with a finite element program to estimate the strain in individual collagen fibers. The measurements demonstrate features that indicate microstructural reorganization and damage of the sclera’s collagen fiber arrangement under loading. The site-matched confocal Raman microspectroscopic characterization of the tissue provides a qualitative measure to relate the change in fibrillar arrangement with possible chemical damage to the collagen microstructure. Tests and analyses presented here can potentially be used to determine the stress-strain behavior, and fiber reorganization of the collagen microstructure in soft tissue during viscoelastic response.     

Robust pore size analysis of filamentous networks from three-dimensional confocal microscopy

We describe a robust method for determining morphological properties of filamentous biopolymer networks, such as collagen or other connective tissue matrices, from confocal microscopy image stacks. Morphological properties including pore size distributions and percolation thresholds are important for transport processes, e.g., particle diffusion or cell migration through the extracellular matrix. The method is applied to fluorescently labeled fiber networks prepared from rat-tail tendon and calf-skin collagen, at concentrations of 1.2, 1.6, and 2.4 mg/ml. The collagen fibers form an entangled and branched network. The medial axes, or skeletons, representing the collagen fibers are extracted from the image stack by threshold intensity segmentation and distance-ordered homotopic thinning. The size of the fluid pores as defined by the radii of largest spheres that fit into the cavities between the collagen fibers is derived from Euclidean distance maps and maximal covering radius transforms of the fluid phase. The size of the largest sphere that can traverse the fluid phase between the collagen fibers across the entire probe, called the percolation threshold, was computed for both horizontal and vertical directions. We demonstrate that by representing the fibers as the medial axis the derived morphological network properties are both robust against changes of the value of the segmentation threshold intensity and robust to problems associated with the point-spread function of the imaging system. We also provide empirical support for a recent claim that the percolation threshold of a fiber network is close to the fiber diameter for which the Euler index of the networks becomes zero.     

Light scattering from collagen fiber networks: micro-optical properties of normal and neoplastic stroma

Development of epithelial precancer and cancer leads to well-documented molecular and structural changes in the epithelium. Recently, it has been recognized that stromal biology is also altered significantly with preinvasive disease. We used the finite-difference time-domain method, a popular technique in computational electromagnetics, to model light scattering from heterogeneous collagen fiber networks and to analyze how neoplastic changes alter stromal scattering properties. Three-dimensional optical images from the stroma of fresh normal and neoplastic oral-cavity biopsies were acquired using fluorescence confocal microscopy. These optical sections were then processed to create realistic three-dimensional collagen networks as model input. Image analysis revealed that the volume fraction of collagen fibers in the stroma decreases with precancer and cancer progression, and fibers tend to be shorter and more disconnected in neoplastic stroma. The finite-difference time-domain modeling results showed that neoplastic fiber networks have smaller scattering cross sections compared to normal networks. Computed scattering-phase functions indicate that high-angle scattering probabilities tend to be higher for neoplastic networks. These results provide valuable insight into the micro-optical properties of normal and neoplastic stroma. Characterization of optical signals obtained from epithelial tissues can aid in development of optical spectroscopic and imaging techniques for noninvasive monitoring of early neoplastic changes.     

Estimating the 3D Pore Size Distribution of Biopolymer Networks from Directionally Biased Data

The pore size of biopolymer networks governs their mechanical properties and strongly impacts the behavior of embedded cells. Confocal reflection microscopy and second harmonic generation microscopy are widely used to image biopolymer networks; however, both techniques fail to resolve vertically oriented fibers. Here, we describe how such directionally biased data can be used to estimate the network pore size. We first determine the distribution of distances from random points in the fluid phase to the nearest fiber. This distribution follows a Rayleigh distribution, regardless of isotropy and data bias, and is fully described by a single parameter—the characteristic pore size of the network. The bias of the pore size estimate due to the missing fibers can be corrected by multiplication with the square root of the visible network fraction. We experimentally verify the validity of this approach by comparing our estimates with data obtained using confocal fluorescence microscopy, which represents the full structure of the network. As an important application, we investigate the pore size dependence of collagen and fibrin networks on protein concentration. We find that the pore size decreases with the square root of the concentration, consistent with a total fiber length that scales linearly with concentration.     

Estimating the 3D Pore Size Distribution of Biopolymer Networks from Directionally Biased Data

The pore size of biopolymer networks governs their mechanical properties and strongly impacts the behavior of embedded cells. Confocal reflection microscopy and second harmonic generation microscopy are widely used to image biopolymer networks; however, both techniques fail to resolve vertically oriented fibers. Here, we describe how such directionally biased data can be used to estimate the network pore size. We first determine the distribution of distances from random points in the fluid phase to the nearest fiber. This distribution follows a Rayleigh distribution, regardless of isotropy and data bias, and is fully described by a single parameter—the characteristic pore size of the network. The bias of the pore size estimate due to the missing fibers can be corrected by multiplication with the square root of the visible network fraction. We experimentally verify the validity of this approach by comparing our estimates with data obtained using confocal fluorescence microscopy, which represents the full structure of the network. As an important application, we investigate the pore size dependence of collagen and fibrin networks on protein concentration. We find that the pore size decreases with the square root of the concentration, consistent with a total fiber length that scales linearly with concentration.     

Structure-Function Relations and Rigidity Percolation in the Shear Properties of Articular Cartilage

Among mammalian soft tissues, articular cartilage is particularly interesting because it can endure a lifetime of daily mechanical loading despite having minimal regenerative capacity. This remarkable resilience may be due to the depth-dependent mechanical properties, which have been shown to localize strain and energy dissipation. This paradigm proposes that these properties arise from the depth-dependent collagen fiber orientation. Nevertheless, this structure-function relationship has not yet been quantified. Here, we use confocal elastography, quantitative polarized light microscopy, and Fourier-transform infrared imaging to make same-sample measurements of the depth-dependent shear modulus, collagen fiber organization, and extracellular matrix concentration in neonatal bovine articular cartilage. We find weak correlations between the shear modulus |G^∗| and both the collagen fiber orientation and polarization. We find a much stronger correlation between |G^∗| and the concentration of collagen fibers. Interestingly, very small changes in collagen volume fraction v_c lead to orders-of-magnitude changes in the modulus with |G^∗| scaling as (v_c – v₀)^ξ. Such dependencies are observed in the rheology of other biopolymer networks whose structure exhibits rigidity percolation phase transitions. Along these lines, we propose that the collagen network in articular cartilage is near a percolation threshold that gives rise to these large mechanical variations and localization of strain at the tissue’s surface.     

Structure-Function Relations and Rigidity Percolation in the Shear Properties of Articular Cartilage

Among mammalian soft tissues, articular cartilage is particularly interesting because it can endure a lifetime of daily mechanical loading despite having minimal regenerative capacity. This remarkable resilience may be due to the depth-dependent mechanical properties, which have been shown to localize strain and energy dissipation. This paradigm proposes that these properties arise from the depth-dependent collagen fiber orientation. Nevertheless, this structure-function relationship has not yet been quantified. Here, we use confocal elastography, quantitative polarized light microscopy, and Fourier-transform infrared imaging to make same-sample measurements of the depth-dependent shear modulus, collagen fiber organization, and extracellular matrix concentration in neonatal bovine articular cartilage. We find weak correlations between the shear modulus |G^∗| and both the collagen fiber orientation and polarization. We find a much stronger correlation between |G^∗| and the concentration of collagen fibers. Interestingly, very small changes in collagen volume fraction v_c lead to orders-of-magnitude changes in the modulus with |G^∗| scaling as (v_c – v₀)^ξ. Such dependencies are observed in the rheology of other biopolymer networks whose structure exhibits rigidity percolation phase transitions. Along these lines, we propose that the collagen network in articular cartilage is near a percolation threshold that gives rise to these large mechanical variations and localization of strain at the tissue’s surface.     

Fiber finding algorithm using stepwise tracing to identify biopolymer fibers in noisy 3D images

We present a novel fiber finding algorithm (FFA) that will permit researchers to detect and return traces of individual biopolymers. Determining the biophysical properties and structural cues of biopolymers can permit researchers to assess the progression and severity of disease. Confocal microscopy images are a useful method for observing biopolymer structures in three dimensions, but their utility for identifying individual biopolymers is impaired by noise inherent in the acquisition process, including convolution from the point spread function (PSF). The new, iterative FFA we present here 1) measures a microscope’s PSF and uses it as a metric for identifying fibers against the background; 2) traces each fiber within a cone angle; and 3) blots out the identified trace before identifying another fiber. Blotting out the identified traces in each iteration allows the FFA to detect and return traces of single fibers accurately and efficiently—even within fiber bundles. We used the FFA to trace unlabeled collagen type I fibers—a biopolymer used to mimic the extracellular matrix in in vitro cancer assays—imaged by confocal reflectance microscopy in three dimensions, enabling quantification of fiber contour length, persistence length, and three-dimensional (3D) mesh size. Based on 3D confocal reflectance microscopy images and the PSF, we traced and measured the fibers to confirm that colder gelation temperatures increased fiber contour length, persistence length, and 3D mesh size—thereby demonstrating the FFA’s use in quantifying biopolymers’ structural and physical cues from noisy microscope images.     

On the Presence of Affine Fibril and Fiber Kinematics in the Mitral Valve Anterior Leaflet

In this study, we evaluated the hypothesis that the constituent fibers follow an affine deformation kinematic model for planar collagenous tissues. Results from two experimental datasets were utilized, taken at two scales (nanometer and micrometer), using mitral valve anterior leaflet (MVAL) tissues as the representative tissue. We simulated MVAL collagen fiber network as an ensemble of undulated fibers under a generalized two-dimensional deformation state, by representing the collagen fibrils based on a planar sinusoidally shaped geometric model. The proposed approach accounted for collagen fibril amplitude, crimp period, and rotation with applied macroscopic tissue-level deformation. When compared to the small angle x-ray scattering measurements, the model fit the data well, with an r² = 0.976. This important finding suggests that, at the homogenized tissue-level scale of ∼1 mm, the collagen fiber network in the MVAL deforms according to an affine kinematics model. Moreover, with respect to understanding its function, affine kinematics suggests that the constituent fibers are largely noninteracting and deform in accordance with the bulk tissue. It also suggests that the collagen fibrils are tightly bounded and deform as a single fiber-level unit. This greatly simplifies the modeling efforts at the tissue and organ levels, because affine kinematics allows a straightforward connection between the macroscopic and local fiber strains. It also suggests that the collagen and elastin fiber networks act independently of each other, with the collagen and elastin forming long fiber networks that allow for free rotations. Such freedom of rotation can greatly facilitate the observed high degree of mechanical anisotropy in the MVAL and other heart valves, which is essential to heart valve function. These apparently novel findings support modeling efforts directed toward improving our fundamental understanding of tissue biomechanics in healthy and diseased conditions.     

Diffusion anisotropy in collagen gels and tumors: the effect of fiber network orientation

The interstitial matrix is comprised of cross-linked collagen fibers, generally arranged in nonisotropic orientations. Spatial alignment of matrix components within the tissue can affect diffusion patterns of drugs. In this study, we developed a methodology for the calculation of diffusion coefficients of macromolecules and nanoparticles in collagenous tissues. The tissues are modeled as three-dimensional, stochastic, fiber networks with varying degrees of alignment. We employed a random walk approach to simulate diffusion and a Stokesian dynamics method to account for hydrodynamic hindrance. We performed our analysis for four different structures ranging from nearly isotropic to perfectly aligned. We showed that the overall diffusion coefficient is not affected by the orientation of the network. However, structural anisotropy results in diffusion anisotropy, which becomes more significant with increase in the degree of alignment, the size of the diffusing particle, and the fiber volume fraction. To test our model predictions we performed diffusion measurements in reconstituted collagen gels and tumor xenografts. We measured fiber alignment and diffusion with second harmonic generation and multiphoton fluorescent recovery after photobleaching techniques, respectively. The results showed for the first time in tumors that the structure and orientation of collagen fibers in the extracellular space leads to diffusion anisotropy.     

Modeling the effect of collagen fibril alignment on ligament mechanical behavior

Ligament mechanical behavior is primarily regulated by fibrous networks of type I collagen. Although these fibrous networks are typically highly aligned, healthy and injured ligament can also exhibit disorganized collagen architecture. The objective of this study was to determine whether variations in the collagen fibril network between neighboring ligaments can predict observed differences in mechanical behavior. Ligament specimens from two regions of bovine fetlock joints, which either exhibited highly aligned or disorganized collagen fibril networks, were mechanically tested in uniaxial tension. Confocal microscopy and FiberFit software were used to quantify the collagen fibril dispersion and mean fibril orientation in the mechanically tested specimens. These two structural parameters served as inputs into an established hyperelastic constitutive model that accounts for a continuous distribution of planar fibril orientations. The ability of the model to predict differences in the mechanical behavior between neighboring ligaments was tested by (1) curve fitting the model parameters to the stress response of the ligament with highly aligned fibrils and then (2) using this model to predict the stress response of the ligament with disorganized fibrils by only changing the parameter values for fibril dispersion and mean fibril orientation. This study found that when using parameter values for fibril dispersion and mean fibril orientation based on confocal imaging data, the model strongly predicted the average stress response of ligaments with disorganized fibrils (\(R^{2}=0.97\)); however, the model only successfully predicted the individual stress response of ligaments with disorganized fibrils in half the specimens tested. Model predictions became worse when parameters for fibril dispersion and mean fibril orientation were not based on confocal imaging data. These findings emphasize the importance of collagen fibril alignment in ligament mechanics and help advance a mechanistic understanding of fibrillar networks in healthy and injured ligament.     

Experimental investigation of collagen waviness and orientation in the arterial adventitia using confocal laser scanning microscopy

Mechanical properties of the adventitia are largely determined by the organization of collagen fibers. Measurements on the waviness and orientation of collagen, particularly at the zero-stress state, are necessary to relate the structural organization of collagen to the mechanical response of the adventitia. Using the fluorescence collagen marker CNA38-OG488 and confocal laser scanning microscopy, we imaged collagen fibers in the adventitia of rabbit common carotid arteries ex vivo. The arteries were cut open along their longitudinal axes to get the zero-stress state. We used semi-manual and automatic techniques to measure parameters related to the waviness and orientation of fibers. Our results showed that the straightness parameter (defined as the ratio between the distances of endpoints of a fiber to its length) was distributed with a beta distribution (mean value 0.72, variance 0.028) and did not depend on the mean angle orientation of fibers. Local angular density distributions revealed four axially symmetric families of fibers with mean directions of 0°, 90°, 43° and ?43°, with respect to the axial direction of the artery, and corresponding circular standard deviations of 40°, 47°, 37° and 37°. The distribution of local orientations was shifted to the circumferential direction when measured in arteries at the zero-load state (intact), as compared to arteries at the zero-stress state (cut-open). Information on collagen fiber waviness and orientation, such as obtained in this study, could be used to develop structural models of the adventitia, providing better means for analyzing and understanding the mechanical properties of vascular wall.     

Fluorescence and confocal laser scanning microscopy imaging of elastic fibers in hematoxylin-eosin stained sections

 We have studied the possibility of associating fluorescence microscopy and hematoxylin-eosin staining for the identification of elastic fibers in elastin-rich tissues. Elastic fibers and elastic laminae were consistently identified by the proposed procedure, which revealed itself to be easy and useful for the determination of such structures and their distribution. The fluorescence properties of stained elastic fibers are due to eosin staining as revealed by fluorescence analysis of the dye in solution, with no or only minor contribution by the elastin auto-fluorescence. The main advantage of this technique resides in the possibility of studying the distribution of elastic fibers in file material without further sectioning and staining. The use of the confocal laser scanning microscope greatly improved the resolution and selectivity of imaging elastic fibers in different tissues. The determination of the three-dimensional distribution and structure of elastic fiber and laminae using the confocal laser scanning microscope was evaluated and also produced excellent results. Accepted: 28 August 1996     

Rheology and Confocal Reflectance Microscopy as Probes of Mechanical Properties and Structure during Collagen and Collagen/Hyaluronan Self-Assembly

In this work, the gelation of three-dimensional collagen and collagen/hyaluronan (HA) composites is studied by time sweep rheology and time lapse confocal reflectance microscopy (CRM). To investigate the complementary nature of these techniques, first collagen gel formation is investigated at concentrations of 0.5, 1.0, and 1.5 mg/mL at 37°C and 32°C. The following parameters are used to describe the self-assembly process in all gels: the crossover time (t_c), the slope of the growth phase (k_g), and the arrest time (t_a). The first two measures are determined by rheology, and the third by CRM. A frequency-independent rheological measure of gelation, t_g, is also measured at 37°C. However, this quantity cannot be straightforwardly determined for gels formed at 32°C, indicating that percolation theory does not fully capture the dynamics of collagen network formation. The effects of collagen concentration and gelation temperature on k_g, t_c, and t_a as well as on the mechanical properties and structure of these gels both during gelation and at equilibrium are elucidated. Composite collagen/HA gels are also prepared, and their properties are monitored at equilibrium and during gelation at 37°C and 32°C. We show that addition of HA subtly alters mechanical properties and structure of these systems both during the gelation process and at equilibrium. This occurs in a temperature-dependent manner, with the ratio of HA deposited on collagen fibers versus that distributed homogeneously between fibers increasing with decreasing gelation temperature. In addition to providing information on collagen and collagen/HA structure and mechanical properties during gelation, this work shows new ways in which rheology and microscopy can be used complementarily to reveal details of gelation processes.     

Label-free 3D visualization of cellular and tissue structures in intact muscle with second and third harmonic generation microscopy

Second and Third Harmonic Generation (SHG and THG) microscopy is based on optical effects which are induced by specific inherent physical properties of a specimen. As a multi-photon laser scanning approach which is not based on fluorescence it combines the advantages of a label-free technique with restriction of signal generation to the focal plane, thus allowing high resolution 3D reconstruction of image volumes without out-of-focus background several hundred micrometers deep into the tissue. While in mammalian soft tissues SHG is mostly restricted to collagen fibers and striated muscle myosin, THG is induced at a large variety of structures, since it is generated at interfaces such as refraction index changes within the focal volume of the excitation laser. Besides, colorants such as hemoglobin can cause resonance enhancement, leading to intense THG signals. We applied SHG and THG microscopy to murine (Mus musculus) muscles, an established model system for physiological research, to investigate their potential for label-free tissue imaging. In addition to collagen fibers and muscle fiber substructure, THG allowed us to visualize blood vessel walls and erythrocytes as well as white blood cells adhering to vessel walls, residing in or moving through the extravascular tissue. Moreover peripheral nerve fibers could be clearly identified. Structure down to the nuclear chromatin distribution was visualized in 3D and with more detail than obtainable by bright field microscopy. To our knowledge, most of these objects have not been visualized previously by THG or any label-free 3D approach. THG allows label-free microscopy with inherent optical sectioning and therefore may offer similar improvements compared to bright field microscopy as does confocal laser scanning microscopy compared to conventional fluorescence microscopy.     

Glioma expansion in collagen I matrices: analyzing collagen concentration-dependent growth and motility patterns

We study the growth and invasion of glioblastoma multiforme (GBM) in three-dimensional collagen I matrices of varying collagen concentration. Phase-contrast microscopy studies of the entire GBM system show that invasiveness at early times is limited by available collagen fibers. At early times, high collagen concentration correlates with more effective invasion. Conversely, high collagen concentration correlates with inhibition in the growth of the central portion of GBM, the multicellular tumor spheroid. Analysis of confocal reflectance images of the collagen matrices quantifies how the collagen matrices differ as a function of concentration. Studying invasion on the length scale of individual invading cells with a combination of confocal and coherent anti-Stokes Raman scattering microscopy reveals that the invasive GBM cells rely heavily on cell-matrix interactions during invasion and remodeling.     

The three-dimensional micro- and nanostructure of the aortic medial lamellar unit measured using 3D confocal and electron microscopy imaging.

Changes in arterial wall composition and function underlie all forms of vascular disease. The fundamental structural and functional unit of the aortic wall is the medial lamellar unit (MLU). While the basic composition and organization of the MLU is known, three-dimensional (3D) microstructural details are tenuous, due (in part) to lack of three-dimensional data at micro- and nano-scales. We applied novel electron and confocal microscopy techniques to obtain 3D volumetric information of aortic medial microstructure at micro- and nano-scales with all constituents present. For the rat abdominal aorta, we show that medial elastin has three primary forms: with approximately 71% of total elastin as thick, continuous lamellar sheets, 27% as thin, protruding interlamellar elastin fibers (IEFs), and 2% as thick radial struts. Elastin pores are not simply holes in lamellar sheets, but are indented and gusseted openings in lamellae. Smooth muscle cells (SMCs) weave throughout the interlamellar elastin framework, with cytoplasmic extensions abutting IEFs, resulting in approximately 20 degrees radial tilt (relative to the lumen surface) of elliptical SMC nuclei. Collagen fibers are organized as large, parallel bundles tightly enveloping SMC nuclei. Quantification of the orientation of collagen bundles, SMC nuclei, and IEFs reveal that all three primary medial constituents have predominantly circumferential orientation, correlating with reported circumferentially dominant values of physiological stress, collagen fiber recruitment, and tissue stiffness. This high resolution three-dimensional view of the aortic media reveals MLU microstructure details that suggest a highly complex and integrated mural organization that correlates with aortic mechanical properties.