1,720,984 research outputs found
On the biomechanical function of scaffolds for engineering load-bearing soft tissues
No full textReplacement or regeneration of load-bearing soft tissues has long been the impetus for the development bioactive materials. While maturing, current efforts continue to be confounded by our lack of understanding of the intricate multi-scale hierarchical arrangements and interactions typically found in native tissues. The current state of the art in biomaterial processing enables a degree of controllable microstructure that can be used for the development of model systems to deduce fundamental biological implications of matrix morphologies on cell function. Furthermore, the development of computational frameworks which allow for the simulation of experimentally derived observations represents a positive departure from what has mostly been an empirically driven field, enabling a deeper understanding of the highly complex biological mechanisms we wish to ultimately emulate. Ongoing research is actively pursuing new materials and processing methods to control material structure down to the micro-scale to sustain or improve cell viability, guide tissue growth, and provide mechanical integrity, all while exhibiting the capacity to degrade in a controlled manner. The purpose of this review is not to focus solely on material processing but to assess the ability of these techniques to produce mechanically sound tissue surrogates, highlight the unique structural characteristics produced in these materials, and discuss how this translates to distinct macroscopic biomechanical behaviors
Micro Scale Based Mechanical Models for Electrospun Poly (Ester Urethane) Urea Scaffolds
No full textMicro scale based mechanical models can provide a tool to guide tissue engineering scaffold design and to investigate on how the cellular mechanical and metabolic response are related to local micro-structural deformations. The present study proposes a novel approach to automatically collect micro-architectural data from SEM images of electrospun poly (ester urethane) urea (PEUU) and to recreate statistically equivalent scaffold mechanical models. Sets of contiguous SEM images for each of the three mandrel velocities (1.5, 4.5, 9.0 m/s) were analyzed. A combination of thresholding and morphological procedures enabled fibers overlaps to be detected. The algorithm precision was tested on regular grids of known characteristics. A modified Delanauy network was generated starting from the detected 2D fiber overlap coordinates. The following micro-architectural data were extracted from the generated network: (1) fiber overlap number and position, (2) connectivity distribution, (3) fiber angle distribution. Appropriate representative volume element (RVE) size was determined. A finite element model of the meso scale system (250 x 250 μm) was constructed respecting the micro-architectural data characterized by the image analysis. FEM and image analysis results revealed the capacity of the approach to characterize the material mechanical behavior at both the fiber and the global levels
A novel approach to fully characterize fiber network morphology of planar fibrous tissues and scaffolds
No full textUnderstanding how scaffold structure influences cell morphology, metabolism, phenotypic expression, and predicting mechanical behaviors have increasingly become crucial goals in the development of engineered tissue scaffolds. A novel image-based analysis algorithm that provides an automatic tool to characterize engineered tissue fiber network topology is presented. Micro architectural descriptors that unambiguously define the fiber network topology were detected, which include fiber orientation distribution, connectivity, intersection spatial density, and diameter. Algorithm performance was tested using actual sample scanning electron microscopy (SEM) images of (1) electrospun poly(ester urethane)urea (ES-PEUU) scaffolds, (2) rabbit MSCs seeded collagen gel scaffolds, and (3) decellularized rat carotid arteries. Qualitative and quantitative validation was performed comparing fiber network topology manually detected by human operators (n=5) with the one automatically detected by the algorithm. R2 correlation values defining the correlation between manual detected and algorithm detected results for the fiber angle distribution and for the fiber connectivity distribution were 0.86 and 0.93 respectively. Algorithm detected fiber intersections and fiber diameter values were inside the (mean ± standard deviation) range detected by human operators. The algorithm’s ability to automatically identify and quantify the complete fiber network morphology regardless of the scaffold typology and of the scale of the problem was proven analyzing three different scaffold models. While the presented validation shows strong consistency between the human operators and the algorithm analysis results the automatic procedure guaranties objectivity and a significant reduction of the analysis time
Micro - Architectural Data Extraction for Electrospun Poly (Ester Urethane) Urea Scaffolds for Biomechanical Modeling.
No full textProblem: Soft tissue engineered applications have raised the need for accurate descriptions of tissue microstructure and their contributions to global mechanical behavior [1]. Accurate material image analysis is crucial to model engineered tissue biomechanics. The present study proposes a novel method to automatically collect micro-architectural data from electron micrographs (SEM) of electrospun poly (ester urethane) urea (PEUU).
Methods: Sets of contiguous SEM images for electrospun PEUU scaffolds made using three mandrel collection tangential velocities (1.5, 4.5, 9.0 m/s) were analyzed. A combination of thresholding and morphological procedures enabled overlaps of fibers to be detected. The algorithm detection precision was tested on regular grids of known characteristics. A modified Delanauy network was generated starting from the detected 2D fiber overlap coordinates. The following micro-architectural data were extracted from the generated network: (1) fiber overlap number and position, (2) connectivity distribution, (3) fiber angle distribution. Appropriate representative volume element (RVE) size was determined performing the image analysis over material areas of different sizes.
Results: The number of overlaps, the total number of connections and the estimated porosity all decreased as the mandrel velocity was raised. Fiber orientation results were consistent with previous findings [1]. The RVE size increased as the mandrel velocity increased consistent with a higher degree of structural organization and fiber alignment. The number of fiber overlaps was predicted for a given mandrel velocity and scaffold area.
Conclusions: The detected fiber overlaps, connectivity and angle distribution showed consistency with the known relationship between mandrel velocity and fiber alignment. The extracted data are considered to be highly relevant for electrospun PEUU scaffolds and collagenous tissue biomechanical modeling. The proposed approach enables a detailed analysis of the micro-architecture to be performed on electrospun PEUU scaffolds.
References: 1) Courtney et al. Biomaterials 2006. 27, 3631-3638.
Acknowledgements: The authors would like to acknowledge financial support from the NIH grant R01 HL-068816.
Disclosures: None of the authors have financial interests related to the topic of the abstract
Effects of fabrication on the mechanics, microstructure and micromechanical environment of small intestinal submucosa scaffolds for vascular tissue engineering.
No full textIn small intestinal submucosa scaffolds for functional tissue engineering, the impact of scaffold fabrication parameters on success rate may be related to the mechanotransductory properties of the final microstructural organization of collagen fibers. We hypothesized that two fabrication parameters, 1) preservation (P) or removal (R) of a dense collagen layer present in SIS and 2) SIS in a final dehydrated (D) or hydrated (H) state, have an effect on scaffold void area, microstructural anisotropy (fiber alignment) and mechanical anisotropy (global mechanical compliance). We further integrated our experimental measurements in a constitutive model to explore final effects on the micromechanical environment inside the scaffold volume. Our results indicated that PH scaffolds might exhibit recurrent and large force fluctuations between layers (up to 195 pN), while fluctuations in RH scaffolds might be larger (up to 256 pN) but not as recurrent. In contrast, both PD and RD groups were estimated to produce scarcer and smaller fluctuations (not larger than 50 pN). We concluded that the hydration parameter strongly affects the micromechanics of SIS and that an adequate choice of fabrication parameters, assisted by the herein developed method, might leverage the use of SIS for functional tissue engineering applications, where forces at the cellular level are of concern in the guidance of new tissue formation
A Custom Image-Based Analysis Tool for Quantifying Elastin and Collagen Micro-Architecture in the Wall of the Human Aorta from Multi-Photon Microscopy
No full textThe aorta possesses a micro-architecture that imparts and supports a high degree of compliance and mechanical strength. Alteration of the quantity and/or arrangement of the main load-bearing components of this micro-architecture - the elastin and collagen fibers - leads to mechanical, and hence functional, changes associated with aortic disease and aging. Therefore, in the future, the ability to rigorously characterize the wall fiber micro-architecture could provide insight into the complicated mechanisms of aortic wall remodeling in aging and disease. Elastin and collagen fibers can be observed using state-of-the-art multi-photon microscopy. Image-analysis algorithms have been effective at characterizing fibrous constructs using various microscopy modalities. The objective of this study was to develop a custom MATLAB-language automated image-based analysis tool to describe multiple parameters of elastin and collagen micro-architecture in human soft fibrous tissue samples using multi-photon microscopy images. Human aortic tissue samples were used to develop the code. The tool smooths, cleans and equalizes fiber intensities in the image before segmenting the fibers into a binary image. The binary image is cleaned and thinned to a fiber skeleton representation of the image. The developed software analyzes the fiber skeleton to obtain intersections, fiber orientation, concentration, porosity, diameter distribution, segment length and tortuosity. In the future, the developed custom image-based analysis tool can be used to describe the micro-architecture of aortic wall samples in a variety of conditions. While this work targeted the aorta, the software has the potential to describe the architecture of other fibrous materials, tube-like networks and connective tissue
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