Quantification of collagen orientation in 3D engineered tissue Florie Daniels Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 1 of 36

Quantification of collagen orientation in 3D engineered tissue Outline Introduction Physiological background Algorithm for 3D orientation analysis Validation Experiments Results Discussion Conclusions Recommendations Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 2 of 36

Quantification of collagen orientation in 3D engineered tissue Introduction Position of the heart valves Heart valve disease Heart valve replacement Heart valve prostheses Mol et al. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 3 of 36

Quantification of collagen orientation in 3D engineered tissue Introduction Project goals: To design an image analysis tool for automatic 3D orientation analysis of collagen fibers in two-photon laser-scanning microscopy (TPLSM) images. To quantify collagen orientation in 3D unattached, attached and strained heart valve tissue engineered equivalents. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 4 of 36

Quantification of collagen orientation in 3D engineered tissue Physiological background The native aortic heart valve Collagen architecture of the native aortic heart valve Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 5 of 36

Quantification of collagen orientation in 3D engineered tissue Physiological background Collagen 1.5 nm in diameter, 300 nm in length diameter ranging from 10 to 500 nm, length ~10 to 30 μm. several hundred micrometers Hierarchy of collagen Fibrillogenesis Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 6 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Input: image stack of TPLSM 20 micron 5 micron Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 7 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Coherence- enhancing diffusion CED was introduced by Weickert et al. Diffusion occurs along the preferred orientation of the structures in the image NOT perpendicular to the structures Amount of diffusion increases when a structure is more oriented. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 8 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Coherence enhancing diffusion Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 9 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Principal Curvature Directions in 3D Hessian Matrix: Eigenvalues  Principal curvatures Eigenvectors  Principal directions (L = image) m-dimensional Gaussian: Second order derivative: Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 10 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Principal Curvature Directions in 3D Principal direction corresponding to minimal principal curvature points in the direction of the structure. Two angles describe the orientation of a vector in 3D: θ: the angle in the xy-plane φ: the angle from the z-axis Representation of the angles in 3D Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 11 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Why Scale Selection? Objects are only meaningfull at a certain scale Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 12 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Scale Selection The eigenvalues of the Hessian indicate the type of structure present in a voxel. The eigenvalues are ordered from small to large: Structure type Polarity Eigenvalues blob bright λ1<<0, λ2<<0, λ3<<0 dark λ1>>0, λ2>>0, λ3>>0 tubular λ1≈ 0, λ2<<0, λ3<< 0 λ1≈ 0, λ2>>0, λ3>>0 plane λ1≈ 0, λ2 ≈ 0, λ3<<0 λ1≈ 0, λ2 ≈ 0, λ3>> 0 Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 13 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Scale Selection Collagen fibers appear as bright tubular structures in a darker environment. The conditions for a bright tubular structure in 3D are: We use normalized Gaussian derivatives to compute the Hessian at different scales. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 14 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Scale Selection Two measures are used for scale selection. The confidence measure (Niessen): with The vesselness measure (Frangi et al.): if λ2>0 or λ3>0, otherwise if λ2>0 or λ3>0 Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 15 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Scale Selection Implementation Artificial image Response of measures over scale Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 16 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Tensor Voting (TV) in 3D TV takes into account the measurements in the neighborhood. The name “tensor voting” comes from the fact that information is encoded in tensors and these tensors communicate by means of a voting process. (Medioni et al.) Each tensor has the following form: Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 17 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Tensor Voting (TV) in 3D An second order symmetric tensor can be expressed as a linear combination of three cases; stickness, plateness and ballness. Stickness: orientation e1, saliency is λ1-λ2 Plateness: orientation is e3, saliency is λ2-λ3 Ballness: no orientation, saliency is λ3 Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 18 of 36

Quantification of collagen orientation in 3D engineered tissue Algorithm for 3D orientation analysis Tensor Voting mechanism Random walk Stick voting communication (E. Franken) Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 19 of 36

Quantification of collagen orientation in 3D engineered tissue Validation Artificial image formation Steps: Fibers of 1 voxel in diameter are created by stepping into a predefined direction Fibers are blurred with a Gaussian An intensity threshold is set including voxels with intensity higher then ¼ of the maximum intensity Subsampling to reduce the partial volume effect Ground truth with orientations at every voxel belonging to a fiber Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 20 of 36

Quantification of collagen orientation in 3D engineered tissue Validation Coherence Enhancing Diffusion The signal-to-noise ratio is determined before and after CED. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 21 of 36

Quantification of collagen orientation in 3D engineered tissue Validation Scale Selection Artificial images with their fibers in the z-direction are used. The diameter in pixels is determined by hand and compared to the scales found by the confidence and vesselness measure. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 22 of 36

Quantification of collagen orientation in 3D engineered tissue Validation Scale Selection The scales were plotted in color over the fiber diameter for both measures: Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 23 of 36

Quantification of collagen orientation in 3D engineered tissue Validation Minimal principal curvature directions Mean orientations for 13 artificial images are determined and compared to the mean of their ground truth in SPSS 14.0. No significant difference was found. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 24 of 36

Quantification of collagen orientation in 3D engineered tissue Validation Tensor Voting Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 25 of 36

Quantification of collagen orientation in 3D engineered tissue Experiments Setup Two experiments: Experiment 1: - E1: unattached - A1: attached (0% strain) B1: 4% strain Experiment 2: - E2: unattached - A2: attached - B2: 4% strain - C2: 8% strain Flexercell FX-4000T straining system Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 26 of 36

Quantification of collagen orientation in 3D engineered tissue Experiments Setup Two photon laser scanning microscopy: 60x magnification 1.0 NA water-dipping objective 1.2x optical zoom 512 x 512 x ± 30 (≈ 180 x 180 x 45 μm) Fluorescent probe: CNA35: High affinity for collagen type-I (Krahn, 2005) Preprocessing of TPLSM images: Memmory reduction Intensity correction Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 27 of 36

Quantification of collagen orientation in 3D engineered tissue Results TPLSM images: unattached sample Selected images of TPLSM data of experiment 1 (200 x 200 micron) 4% strain sample Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 28 of 36

Quantification of collagen orientation in 3D engineered tissue Results TPLSM images: unattached sample Selected images of TPLSM data of experiment 2 (170x 170 micron) 8% strained sample Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 29 of 36

Quantification of collagen orientation in 3D engineered tissue Results Orientation analysis results from algorithm Unattached Attached (0% strain) 4% strain Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 30 of 36

Quantification of collagen orientation in 3D engineered tissue Results Unattached Attached (0% strain) 4% strain 8% strain Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 31 of 36

Quantification of collagen orientation in 3D engineered tissue Results TPLSM-data Mean orientation of θ (in degrees) orientation of φ Variance in θ (in degrees2) Variance in φ Experiment 1 E1 (unattached) 46,8 90,0 31,9 5,4 A1 (0% strain) 22,8 4,3 B1 (4% strain) 90,1 30,4 11,7 Experiment 2 E2 (unattached) 21,6 34,7 4,7 A2 (0%strain) 93,6 34,3 7,0 B2 (4%strain) 176,5 23,6 13,3 C2 (8% strain) 169,2 90,2 22,6 7,8 Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 32 of 36

Quantification of collagen orientation in 3D engineered tissue Discussion Coherence enhancing diffusion The parameters involved in CED are chosen based on visual inspection. Principal curvature directions: Assumption tubular structures. 2nd order Gaussian derivative match with fibers. Scale selection Confidence measure was used based on validation but is not appropriate for differentiating between plate-like and tubular structures. Range of scales for analysis. Tensor Voting Not used in the final algorithm. Needs more investigation. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 33 of 36

Quantification of collagen orientation in 3D engineered tissue Conclusions 3D principal curvature directions are an effective way to determine local orientation of tubular structures. CED can be used to enhance collagen fibers in TPLSM images TPLSM makes it possible to study 3D collagen orientation in tissue engineered constructs. This study indicates that there is an increase in collagen alignment with increased strain magnitude based on visual inspection of the orientation histograms. The variance in orientation does not support the observations made from the orientation histograms. Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 34 of 36

Quantification of collagen orientation in 3D engineered tissue Recommendations Algorithm Faster implementation in e.g. C++. Fourier analysis. Tissue engineering Increasing the number of experiments. Imaging deeper into tissue and/or with less magnification. Investigate other properties of collagen (fiber thickness). Different straining methods. Follow same sample over time Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 35 of 36

Thank you for your attention! Questions/Remarks? Quantification of collagen orientation in 3D engineered tissue Thank you for your attention! Questions/Remarks? Msc. Thesis presentation Florie Daniels - June 29, 2006 Slide 36 of 36