Imaging and 3D morphological analysis of collagen fibrils

Altendorf, Hellen; Decencière, Étienne; Jeulin, Dominique; Peixoto, Paulo De Sa; Deniset‐Besseau, Ariane; Angelini, Elsa D.; Mosser, Gervaise; Schanne-Klein, Marie-Claire

doi:10.1111/j.1365-2818.2012.03629.x

Cited by 38 publications

(30 citation statements)

References 39 publications

(61 reference statements)

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“…For example, a directional gradient method developed by Altendorf et al . [34] provides three-dimensional orientation and radius information about fibers in SHG images. Due to the fibrous nature of the collagen matrix, SHG images are particularly well-suited for the curvelet transform (CT), which is a multiscale, orientation sensitive version of the wavelet transform.…”

Section: Introductionmentioning

confidence: 99%

Automated quantification of aligned collagen for human breast carcinoma prognosis

Bredfeldt

Liu

Conklin

et al. 2014

Journal of Pathology Informatics

177

152

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Background:Mortality in cancer patients is directly attributable to the ability of cancer cells to metastasize to distant sites from the primary tumor. This migration of tumor cells begins with a remodeling of the local tumor microenvironment, including changes to the extracellular matrix and the recruitment of stromal cells, both of which facilitate invasion of tumor cells into the bloodstream. In breast cancer, it has been proposed that the alignment of collagen fibers surrounding tumor epithelial cells can serve as a quantitative image-based biomarker for survival of invasive ductal carcinoma patients. Specific types of collagen alignment have been identified for their prognostic value and now these tumor associated collagen signatures (TACS) are central to several clinical specimen imaging trials. Here, we implement the semi-automated acquisition and analysis of this TACS candidate biomarker and demonstrate a protocol that will allow consistent scoring to be performed throughout large patient cohorts.Methods:Using large field of view high resolution microscopy techniques, image processing and supervised learning methods, we are able to quantify and score features of collagen fiber alignment with respect to adjacent tumor-stromal boundaries.Results:Our semi-automated technique produced scores that have statistically significant correlation with scores generated by a panel of three human observers. In addition, our system generated classification scores that accurately predicted survival in a cohort of 196 breast cancer patients. Feature rank analysis reveals that TACS positive fibers are more well-aligned with each other, are of generally lower density, and terminate within or near groups of epithelial cells at larger angles of interaction.Conclusion:These results demonstrate the utility of a supervised learning protocol for streamlining the analysis of collagen alignment with respect to tumor stromal boundaries.

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Section: Introductionmentioning

confidence: 99%

Automated quantification of aligned collagen for human breast carcinoma prognosis

Bredfeldt

Liu

Conklin

et al. 2014

Journal of Pathology Informatics

177

152

View full text Add to dashboard Cite

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“…Yet, the ability to automatically generate fiber orientation information at each voxel within an image would be advantageous for many applications. Further approaches include the chord length transform [28], Gaussian orientation space [29,30] and inertia moments [31]; however there are some restrictions on the characteristics of fibers (e.g., shape, cross section or thickness) when using these techniques.…”

Section: Introductionmentioning

confidence: 99%

Rapid three-dimensional quantification of voxel-wise collagen fiber orientation

Liu¹,

Quinn²,

Speroni³

et al. 2015

Biomed. Opt. Express

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Abstract:Defining fiber orientation at each voxel within a 3D biomedical image stack is potentially useful for a variety of applications, including cancer, wound healing and tissue regeneration. Current methods are typically computationally intensive or inaccurate. Herein, we present a 3D weighted orientation vector summation algorithm, which is a generalization of a previously reported 2D vector summation technique aimed at quantifying collagen fiber orientations simultaneously at each voxel of an image stack. As a result, voxel-wise fiber orientation information with 4° to 5° accuracy can be determined, and the computational time required to analyze a typical stack with the size of 512x512x100 voxels is less than 5 min. Thus, this technique enables the practical extraction of voxel-specific orientation data for characterizing structural anisotropy in 3D specimens. As examples, we use this approach to characterize the fiber organization in an excised mouse mammary gland and a 3D breast tissue model. Schanne-Klein, "Three-dimensional investigation and scoring of extracellular matrix remodeling during lung fibrosis using multiphoton microscopy," Microsc.

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“…Similarly, the invention of atomic force microscopy (AFM) is a significant improvement in the field of nanosurface characterization and in the field of molecular structures imaging (Stylianou et al, 2011). AFM images of collagen-bilirubin complexes are examined to understand the pattern and order of collagen in the presence of bilirubin (Altendorf et al, 2012). Using AFM, properties of films surface, such as height and roughness, can be estimated without destroying the fibrillar structure (Kadler et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

A microscopic evaluation of collagen–bilirubin interactions: in vitro surface phenomenon

Nagarajan

Jayakumar

Rao

et al. 2013

Journal of Microscopy

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SummaryThis study is carried out to understand the morphology variations of collagen I matrices influenced by bilirubin. The characteristics of bilirubin interaction with collagen ascertained using various techniques like XRD, CLSM, fluorescence, SEM and AFM. These techniques are used to understand the distribution, expression and colocalization patterns of collagenbilirubin complexes. The present investigation mimic the in vivo mechanisms created during the disorder condition like jaundice. Fluorescence technique elucidates the crucial role played by bilirubin deposition and interaction during collagen organization. Influence of bilirubin during collagen fibrillogenesis and banding patterns are clearly visualize using SEM. As a result, collagen-bilirubin complex provides different reconstructed patterns because of the influence of bilirubin concentration. Selectivity, specificity and spatial organization of collagen-bilirubin are determined through AFM imaging. Consequently, it is observed that the morphology and quantity of the bilirubin binding to collagen varied by the concentrations and the adsorption rate in protein solutions. Microscopic studies of collagen-bilirubin interaction confirms that bilirubin influence the fibrillogenesis and alter the rate of collagen organization depending on the bilirubin concentration. This knowledge helps to develop a novel drug to inhibit the interface point of interaction between collagen and bilirubin.

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Imaging and 3D morphological analysis of collagen fibrils

Cited by 38 publications

References 39 publications

Automated quantification of aligned collagen for human breast carcinoma prognosis

Automated quantification of aligned collagen for human breast carcinoma prognosis

Rapid three-dimensional quantification of voxel-wise collagen fiber orientation

A microscopic evaluation of collagen–bilirubin interactions: in vitro surface phenomenon

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