Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Stylianopoulos T

PROVIDER: S-EPMC2980743 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

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

Stylianopoulos Triantafyllos T Diop-Frimpong Benjamin B Munn Lance L LL Jain Rakesh K RK

Biophysical journal 20101101 10

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 ap ...[more]

PMID: 21081058

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Project description:Diffusion magnetic resonance imaging (dMRI) is widely used to probe tissue microstructure, and is currently the only non-invasive way to measure the brain's fiber architecture. While a large number of approaches to recover the intra-voxel fiber structure have been utilized in the scientific community, a direct, 3D, quantitative validation of these methods against relevant histological fiber geometries is lacking. In this study, we investigate how well different high angular resolution diffusion imaging (HARDI) models and reconstruction methods predict the ground-truth histologically defined fiber orientation distribution (FOD), as well as investigate their behavior over a range of physical and experimental conditions. The dMRI methods tested include constrained spherical deconvolution (CSD), Q-ball imaging (QBI), diffusion orientation transform (DOT), persistent angular structure (PAS), and neurite orientation dispersion and density imaging (NODDI) methods. Evaluation criteria focus on overall agreement in FOD shape, correct assessment of the number of fiber populations, and angular accuracy in orientation. In addition, we make comparisons of the histological orientation dispersion with the fiber spread determined from the dMRI methods. As a general result, no HARDI method outperformed others in all quality criteria, with many showing tradeoffs in reconstruction accuracy. All reconstruction techniques describe the overall continuous angular structure of the histological FOD quite well, with good to moderate correlation (median angular correlation coefficient > 0.70) in both single- and multiple-fiber voxels. However, no method is consistently successful at extracting discrete measures of the number and orientations of FOD peaks. The major inaccuracies of all techniques tend to be in extracting local maxima of the FOD, resulting in either false positive or false negative peaks. Median angular errors are ?10° for the primary fiber direction and ?20° for the secondary fiber, if present. For most methods, these results did not vary strongly over a wide range of acquisition parameters (number of diffusion weighting directions and b value). Regardless of acquisition parameters, all methods show improved successes at resolving multiple fiber compartments in a voxel when fiber populations cross at near-orthogonal angles, with no method adequately capturing low to moderate angle (<60°) crossing fibers. Finally, most methods are limited in their ability to capture orientation dispersion, resulting in low to moderate, yet statistically significant, correlation with histologically-derived dispersion with both HARDI and NODDI methodologies. Together, these results provide quantitative measures of the reliability and limitations of dMRI reconstruction methods and can be used to identify relative advantages of competing approaches as well as potential strategies for improving accuracy.

Project description:Collagen is the most prominent protein of human tissues. Its content and organization define to a large extent the mechanical properties of tissue as well as its function. Methods that have been used traditionally to visualize and analyze collagen are invasive, provide only qualitative or indirect information, and have limited use in studies that aim to understand the dynamic nature of collagen remodeling and its interactions with the surrounding cells and other matrix components. Second harmonic generation (SHG) imaging emerged as a promising noninvasive modality for providing high-resolution images of collagen fibers within thick specimens, such as tissues. In this article, we present a fully automated procedure to acquire quantitative information on the content, orientation, and organization of collagen fibers. We use this procedure to monitor the dynamic remodeling of collagen gels in the absence or presence of fibroblasts over periods of 12 or 14 days. We find that an adaptive thresholding and stretching approach provides great insight to the content of collagen fibers within SHG images without the need for user input. An additional feature-erosion and feature-dilation step is useful for preserving structure and noise removal in images with low signal. To quantitatively assess the orientation of collagen fibers, we extract the orientation index (OI), a parameter based on the power distribution of the spatial-frequency-averaged, two-dimensional Fourier transform of the SHG images. To measure the local organization of the collagen fibers, we access the Hough transform of small tiles of the image and compute the entropy distribution, which represents the probability of finding the direction of fibers along a dominant direction. Using these methods we observed that the presence and number of fibroblasts within the collagen gel significantly affects the remodeling of the collagen matrix. In the absence of fibroblasts, gels contract, especially during the first few days, in a manner that allows the fibers to remain mostly disoriented, as indicated by small OI values. Subtle changes in the local organization of fibers may be taking place as the corresponding entropy values of these gels show a small decrease. The presence of fibroblasts affects the collagen matrix in a manner that is highly dependent on their number. A low density of fibroblasts enhances the rate of initial gel contraction, but ultimately leads to degradation of collagen fibers, which start to organize in localized clumps. This degradation and reorganization is seen within the first days of incubation with fibroblasts at a high density and is followed by de novo collagen fiber deposition by the fibroblasts. These collagen fibers are more highly oriented and organized than the fibers of the original collagen gel. These initial studies demonstrate that SHG imaging in combination with automated image analysis approaches offer a noninvasive and easily implementable method for characterizing important features of the content and organization of collagen in tissuelike specimens. Therefore, these studies could offer important insights for improving tissue engineering and disease diagnostic efforts.

Dataset Information

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

Publications

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

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