3 research outputs found

    MODELLING AND IN VIVO MONITORING OF THE TIME DEPENDENT MECHANICAL PROPERTIES OF TISSUE ENGINEERING SCAFFOLDS

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    When organs and tissue fail either due to pre-existing disease progression or by accidental damage, current state of the art treatment involves the replacement of the damaged or diseased tissue with new donor derived organs/tissue. The limitations of these current approaches include a limited supply of tissue for treatments and the immune response of the patient’s own body against the new implanted tissue/organs. To solve these issues, tissue engineering aims to develop artificial analogs derived from a patient’s own cells instead of donor tissue/organs for treatment. To this end, a promising approach, known as scaffold-based tissue engineering, is to seed engineered constructs or scaffolds with cells to form artificial analogs, which then develop with time into new tissue/organs for implantation. The mechanical properties of the scaffold play a critical role in the success of scaffold-based treatments, as the scaffold is expected to provide a temporary support for the generation of new tissue/organs without causing failure at any time during the treatment process. It is noted that due to the degradation of scaffold in the treatment process, the mechanical properties of the scaffold are not constant but change with time dynamically. This raises two scientific issues; one is the representation of the time-dependent mechanical properties and the other one is the monitoring of these properties, especially in the in vivo environments (i.e., upon the implantation of scaffolds into animal/patient bodies). To address these issues, this research is aimed at performing a novel study on the modelling and in vivo monitoring of the time dependent mechanical properties of tissue engineering scaffolds. To represent the time-dependent mechanical properties of a scaffold, a novel model based on the concept of finite element model updating is developed. The model development involves three steps: (1) development of a finite element model for the effective mechanical properties of the scaffold, (2) parametrizing the finite element model by selecting parameters associated with the scaffold microstructure and/or material properties, which vary with scaffold degradation, and (3) identifying selected parameters as functions of time based on measurements from the tests on the scaffold mechanical properties as they degrade. To validate the developed model, scaffolds were made from the biocompatible polymer polycaprolactone (PCL) mixed with hydroxyapatite (HA) nanoparticles and their mechanical properties were examined in terms of the Young modulus. Based on the bulk degradation exhibited by the PCL/HA scaffold, the molecular weight was selected for model updating. With the identified molecular weight, the finite element model v developed was effective for predicting the time-dependent mechanical properties of PCL/HA scaffolds during degradation . To monitor and characterize scaffold mechanical properties in vivo, novel methods based on synchrotron-based phase contrast imaging and finite element modeling were developed. The first method is to represent the scaffold mechanical properties from the measured deflection. In this method, the phase contrast imaging is used to characterize the scaffold deflection caused by ultrasound radiation forces; and the finite element modelling is used to represent the ultrasonic loading on the scaffold, thus predicting the mechanical properties from the measured deflection. The second method is to characterize the scaffold degradation due to surface erosion, which involves the remote sensing of the time dependent morphology of tissue scaffolds by phase contrast imaging and the estimation of time dependent mass loss of the scaffolds from the sensed morphology. The last method is to relate the elastic mechanical property and nonlinear stress-strain behavior to the scaffold geometry, both changing with time during surface erosion. To validate the above methods, scaffolds was made from varying biomaterials (PLGA and PCL) and their mechanical properties (degradation, mass loss, and elastic modulus) were examined experimentally. The results obtained illustrate the methods developed in this research are effective to monitor and characterize scaffold mechanical properties. The significance of this research is that the model developed for the scaffold mechanical properties can be used in the design of scaffolds with the desired mechanical properties, instead of the trial and error methods typical in current scaffold design; and that these novel monitoring methods based on synchrotron imaging can be used to characterize the scaffold time-dependent mechanical properties in the in vivo environments, representing an important advance in tissue engineering

    Synchrotron-Based in Situ Characterization of the Scaffold Mass Loss from Erosion Degradation

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    The mass loss behavior of degradable tissue scaffolds is critical to their lifespan and other degradation-related properties including mechanical strength and mass transport characteristics. This paper presents a novel method based on synchrotron imaging to characterize the scaffold mass loss from erosion degradation in situ, or without the need of extracting scaffolds once implanted. Specifically, the surface-eroding degradation of scaffolds in a degrading medium was monitored in situ by synchrotron-based imaging; and the time-dependent geometry of scaffolds captured by images was then employed to estimate their mass loss with time, based on the mathematical model that was adopted from the literature of surface erosion with the experimentally-identified model parameters. Acceptable agreement between experimental results and model predictions was observed for scaffolds in a cylindrical shape, made from poly(lactic-co-glycolic) acid (PLGA) and polycaprolactone (PCL). This study illustrates that geometry evaluation by synchrotron-based imaging is an effective means to in situ characterize the scaffold mass loss as well as possibly other degradation-related properties
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