Dogu Baran Aydogan

Direct laser writing and geometrical analysis of scaffolds with designed pore architecture for three-dimensional cell culturing

Traditional scaffold fabrication methods used in tissue engineering enable only limited control over essential parameters such as porosity, pore size and pore interconnectivity. In this study, we designed and fabricated five different types of three-dimensionally interconnected, highly porous scaffolds with precise control over the scaffold characteristics. We used two-photon polymerization (2PP) with a commercial polymer?ceramic material (Ormocomp?) for scaffold fabrication. Also for the first time, we analyzed the 2PP fabrication accuracy with respect to scaffold design parameters. Our results showed that the porosity values decreased up to 13% compared to the design specifications due to the fabrication process and the shrinkage of the material. Finally, we showed that our scaffolds supported human adipose stem cell adhesion and proliferation in a six day culture. By precise tuning of scaffold parameters, our design and fabrication method provides a novel approach for studying the effect of scaffold architecture on cell behavior in vitro.

Direct laser writing of synthetic poly(amino acid) hydrogels and poly(ethylene glycol) diacrylates by two-photon polymerization.

The additive manufacturing technique of direct laser writing by two-photon polymerization (2PP-DLW) enables the fabrication of three-dimensional microstructures with superior accuracy and flexibility. When combined with biomimetic hydrogel materials, 2PP-DLW can be used to recreate the microarchitectures of the extracellular matrix. However, there are currently only a limited number of hydrogels applicable for 2PP-DLW. In order to widen the selection of synthetic biodegradable hydrogels, in this work we studied the 2PP-DLW of methacryloylated and acryloylated poly(α-amino acid)s (poly(AA)s). The performance of these materials was compared to widely used poly(ethylene glycol) diacrylates (PEGdas) in terms of polymerization and damage thresholds, voxel size, line width, post-polymerization swelling and deformation. We found that both methacryloylated and acryloylated poly(AA) hydrogels are suitable to 2PP-DLW with a wider processing window than PEGdas. The poly(AA) with the highest degree of acryloylation showed the greatest potential for 3D microfabrication.

2D texture based classification, segmentation and 3D orientation estimation of tissues using DT-CWT feature extraction methods

In this study, four different 2D dual-tree complex wavelet (DT-CWT) based texture feature extraction methods are developed and their applications are demonstrated in segmenting and classifying tissues. Two of the methods use rotation variant texture features and the other two use rotation invariant features. This paper also proposes a novel approach to estimate 3D orientations of tissues based on rotation variant DT-CWT features. The method updates the strongest structural anisotropy direction with an iterative approach and converges to a volume orientation in few steps. Although classification and segmentation results show that there is no significant difference in the performance between rotation variant and invariant features; the latter are more robust to changes in texture rotation, which is essential for classification and segmentation of objects from 3D datasets such as medical tomography images.

Texture Based Classification and Segmentation of Tissues Using DT-CWT Feature Extraction Methods

In this study, four different dual-tree complex wavelet (DT-CWT) based texture feature extraction methods are developed and compared to segment and classify tissues. Methods that are proposed in this study are based on local energy calculations of sub-bands. Two of the methods use rotation variant texture features and the other two use rotation invariant features. The methods are tested on two texture compositions from the Brodatz texture database and two actual magnetic resonance (MR) images. Results show that there is not a significant difference between using rotation variant or invariant features. On the other hand, for the same Brodatz textures, all DT-CWT based feature extraction methods are competitive with other filtering approaches.

Characterization of microstructures using contour tree connectivity for fluid flow analysis

Quantifying the connectivity of material microstructures is important for a wide range of applications from filters to biomaterials. Currently, the most used measure of connectivity is the Euler number, which is a topological invariant. Topology alone, however, is not sufficient for most practical purposes. In this study, we use our recently introduced connectivity measure, called the contour tree connectivity (CTC), to study microstructures for flow analysis. CTC is a new structural connectivity measure that is based on contour trees and algebraic graph theory. To test CTC, we generated a dataset composed of 120 samples and six different types of artificial microstructures. We compared CTC against the Euler parameter (EP), the parameter for connected pairs, the nominal opening dimension (dnom) and the permeabilities estimated using direct pore scale modelling. The results show that dnom is highly correlated with permeability (R2 = 0.91), but cannot separate the structural differences. The groups are best classified with feature combinations that include CTC. CTC provides new information with a different connectivity interpretation that can be used to analyse and design materials with complex microstructures.

Contour tree connectivity of binary images from algebraic graph theory

We propose a novel feature for binary images that provides connectivity information by taking into account the proximity of connected components and cavities. We start by applying the Euclidean distance transform and then we compute the contour tree. Finally, we assign the normalized algebraic connectivity of a contour tree derivative as a feature for connectivity. Our algorithm can be applied to any dimensions of data as well as topology. And the resultant connectivity index is a single real number between 0 and 1. We test and demonstrate interesting properties of our approach on various 2D and 3D images. With its intriguing properties, the proposed index is widely applicable for studying binary morphology. Especially, it is complementary to Euler number for studying connectivity of microstructures of materials such as soil, paper, filter, food products as well as biomaterials and biological tissues.

Binary image representation by contour trees

There is a growing need in medical image processing to analyze segmented objects. In this study we are interested in analyzing morphological properties of complex structures such as the trabecular bone. Although, there are various shape description approaches proposed in the literature, there is not an adequate method to represent foreground object(s) morphology with respect to the background. In this article, we propose a way of representing binary images of any dimensions using graphs that emphasize connectivity of level-sets to foreground and background. We start by calculating the euclidean distance transform (EDT) to create a scalar field. Then the contour tree of this scalar field is calculated using a modified version of the algorithm proposed by Carr. Contour trees are mostly used to visualize high dimensional scalar fields as they can put on view the critical points, i.e: local min, max and saddle points; however, their use in representing complex shapes have not been studied. We demonstrate the use of our method on artificial 2D images having different topologies as well as 3D μ-CT images of two bone biopsies. We show that the application of contour trees to complex binary data particularly prove useful when interpreting pore-networks at micro-scale. Further work to quantify foreground and background interconnectivity using certain graph theoretical methods is still under research.

Analysis of Trabecular Bone Microstructure Using Contour Tree Connectivity

Millions of people worldwide suffer from fragility fractures, which cause significant morbidity, financial costs and even mortality. The gold standard to quantify structural properties of trabecular bone is based on the morphometric parameters obtained from microCT images of clinical bone biopsy specimens. The currently used image processing approaches are not able to fully explain the variation in bone strength. In this study, we introduce the contour tree connectivity (CTC) as a novel morphometric parameter to study trabecular bone quality. With CTC, we calculate a new connectivity measure for trabecular bone by using contour tree representation of binary images and algebraic graph theory. To test our approach, we use trabecular bone biopsies obtained from 55 female patients. We study the correlation of CTC with biomechanical test results as well as other morphometric parameters obtained from microCT. The results based on our dataset show that CTC is the 3rd best predictive feature of ultimate bone strength after bone volume fraction and degree of anisotropy.

Simulation of Microporous Architecture's Effects on Fluid Flow Characteristics in Cell Seeding

Microscaffolds play a crucial role in cell culturing. They can be designed and produced in different ways depending on the applications and materials used. The cell medium (fluid) transports the cells into the microscaffold and is an effective factor for cell growth and stimulation. The architecture of microscaffolds influences fluid flow characteristics such as velocity and shear stress during cell seeding. Shear stress is known to stimulate the cells in scaffolds. Therefore, it is interesting for biomaterial researchers and scaffold designers, to understand how the shape and porosity of the microscaffold influences the dynamics of fluid flows. In this work, we modeled the flow in three-dimensional rectangular, cylindrical, and spherical micropore networks with various porosities. The velocity distribution and mean wall shear stress are computed and compared for a single-phase flow. It is noted that grid independency is achieved when any further increase in the number of cells did not adversely affect the simulation results. Results show that spherical micropores with porosity higher than 80% are suitable for those types of cells that must be stimulated with low shear stress. In contrast, rectangular and cylindrical micropore networks can be used for cells that should be stimulated with high shear stress.