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Non-invasively monitoring the extent of cell growth, scaffold degradation and tissue development will greatly help tissue engineers to monitor in vivo regenerate tissue function and scaffold degradation. Currently available methods for tissue and scaffold degradation analysis, such as histology and direct mechanical measurements, are not suitable for continuous monitoring of the same sample in vivo as they destroy cells, tissue matrix and scaffolds. In addition, different samples are prepared and measured at varying times, but high tissue growth deviation between specimens and the need for monitoring tissue growth and scaffold degradation at different times requires large sample numbers for statistical analysis. Ultrasound elasticity imaging (UEI) based on phase-sensitive speckle tracking can characterize the internal structural, compositional and functional change of biomaterial scaffolds and engineered tissues at high resolution. In this study, UEI resolution was 250 lm (axial) by 500 μm (lateral) using a commercial ultrasound transducer centered at 5 MHz. This method allows characterization of both globally and locally altered scaffold and engineered tissue elastic properties. Preliminary in vitro and in vivo results with poly(1,8-octanediol-co-citrate) scaffolds support the feasibility of UEI as a non-invasive quantitative monitoring tool for scaffold degradation and engineered tissue formation. This novel non-invasive monitoring tool will provide direct, time-dependent feedback on scaffold degradation and tissue ingrowth for tissue engineers to improve the design process.
In tissue engineering, biodegradable polymer scaffolds are used to deliver cells and regenerate tissue as well as provide temporary mechanical support. There are two main challenges in creating the ideal biodegradable polymer scaffold: (i) the scaffold must have a defined shape and porous internal architecture suitable to direct tissue ingrowth with appropriate mechanical and degradation properties; and (ii) the scaffold must have appropriate surface properties to provide favorable conditions for cells to attach, proliferate, differentiate and produce extracellular matrix . The success of aliphatic polyesters in tissue engineering relies largely on their degradability and biocompatibility, as well as on their mechanical properties. In principle, the degradation rate of the scaffold should match the rate of tissue formation, hence the degradation behavior of a scaffold has a critical impact on the long-term performance of a tissue-engineered cell/scaffold construct in vivo.
Therefore, non-invasively monitoring the extent of scaffold degradation and tissue development will greatly help tissue engineers better evaluate regenerative therapies. It would also be valuable to measure matrix development, such as collagen, elastin and hard tissues, which could determine the load-bearing capability of the scaffold/tissue construct. To optimize therapies, it is highly desirable to understand relative rates of tissue regeneration and scaffold degradation for the same specimen as a function of time. Currently, available analysis methods for quantifying tissue formation are histology and direct mechanical measurements. Even though these methods provide good images for cell phenotype and proliferation, and mechanical characterization such as compressive moduli of scaffolds, they require animal sacrifice and scaffolds destruction, hence samples cannot be reused after characterization. In addition, different samples are prepared and measured at varying times, but high tissue growth deviation between specimens requires large sample numbers for statistical analysis. Ideally, tissue engineers need a system that can non-invasively monitor tissue growth and consequent scaffold degradation in the same specimen over time. Other imaging methods, such as magnetic resonance imaging and computed tomography (CT), provide internal scaffold structural information, but they are limited to providing only morphological information, and scanning and image reconstruction procedures are quite extensive .
Ultrasound elasticity imaging (UEI) has been found to be a valuable non-invasive tool to investigate mechanical characteristics of biological tissue [3–6]. It estimates tissue motion based on speckle tracking between two frames before and after deformation of the tissue. In UEI the excitation is produced by actually pushing on tissue with an ultrasound transducer itself and recording the tissue deformation with real-time ultrasound images [4,7]. This constitutes a near static deformation with an external force. Combinations of static or dynamic deformations with internal or external surface forces to induce deformations have also been explored [8,9]. Speckle tracking was initially introduced in one dimension (1-D) to estimate tissue motion along the axial direction (the beam propagation direction) [4,10] and has been expanded into 2-D. 2-D speckle tracking measures displacements of the speckles in both axial and lateral (perpendicular to the beam direction in the imaging plane) directions [11–15]. The most commonly used elasticity imaging techniques are based on 2-D correlation-based speckle tracking methods [12–15]. Speckle displacements are estimated from correlation lags corresponding to the maximum correlation coefficient between the frames. In the past decade, elasticity imaging based on speckle tracking has been shown to have great potential for clinical use [3,4,7,16–20], where several groups have also explored high spatial resolution ultrasound speckle tracking systems for intravascular applications [18,21–23]. UEI using transcutaneous linear probes has also been successfully applied to other in vivo applications, including, thrombus aging/maturational evaluation in human lower limb deep venous thrombosis [24,25], breast cancer diagnosis [26,27], differentiation of benign and malignant thyroid masses , differentiation of benign and malignant cervical lymph nodes , prostate cancer detection [30,31], renal transplant graft nephropathy evaluation , characterization of arterial wall stiffness for early atherosclerosis diagnosis [8,33], assessment of myocardial wall stiffness for detection of contractile dysfunction  and atheromata assessment for determining vulnerable plaque [35,36].
UEI combines two procedures: (i) the application of controlled deformation to the study object; and (ii) phase-sensitive, 2-D ultrasound speckle tracking and evaluation of internal tissue motion, i.e. measurement of displacement and strain components. UEI will provide full internal mechanical and structural characteristics of the biomaterial tissue scaffold and engineered tissue as a measure of the scaffold degradation and tissue regeneration process. In this paper, the feasibility of UEI is demonstrated by applying this technique to monitor the in vitro and in vivo degradation processes of poly(1,8-octanediol-co-citrate) (POC) scaffolds.
POC is a strong, elastomeric, biodegradable, hydrophilic “cell-friendly” material which shows promise for soft tissue engineering. Furthermore, it has the following advantages: non-toxic monomers, a relatively simple synthesis without addition of catalysts or cross-linking reagents, cost-effective scale-up, controllable mechanical and biodegradation properties and easy processing, and inherent surface affinity for various cell types including chondrocytes and bone marrow stromal cells. Recently, Yang et al. have shown that POC has properties favorable for cartilage matrix regeneration . POC is synthesized by reacting the polyfunctional monomer citric acid with the difunctional monomer 1,8-octanediol to create a polyester network with a controllable number of crosslinks to tailor the elasticity and biodegradability of the resulting material.
POC is degraded by hydrolysis of its ester linkages in physiological conditions and its byproducts, citric acid and 1,8-octanediol, are excreted by the body. Citric acid is a non-toxic metabolic product of the Krebs cycle in the body and 1,8-octanediol enables ester bonds to form with citric acid and is water-soluble with no reported toxicity. These monomers ensure a beneficial property of the degradation process leaving no insoluble or toxic complexes in the body. One of the unique properties of POC is that its mechanical properties can easily be tailored by changing curing temperature and time, monomer molar ratio, and the presence of vacuum when curing. Even though Kang et al.  have shown POC degradation profiles in vitro using phosphate buffered solution (PBS) at 37 °C, the degradation behavior in vivo has not been elucidated. Since POC is known as a relatively fast-degradable polymer, careful monitoring of mechanical property changes due to degradation behavior will be required to relate to tissue formation.
In this study, we focus on showing the feasibility of noninvasive monitoring of scaffold degradation using UEI by comparing UEI measures with standard mechanical testing and weight measures of degradation. UEI is applied in vitro to POC scaffolds embedded in a gelatin phantom. In vivo UEI on POC scaffolds implanted subcutaneously in a mouse is also performed to investigate the feasibility of this technique as a non-invasive monitoring tool of scaffold degradation.
Previously developed image-based design processes and software were used to design POC scaffold architecture [39–41]. In image-based design, 3-D topology is represented as densities from 0 to 255 in a structured voxel data-set. Thresholding the voxel data into materials and void gives the final topology. To design scaffolds with hierarchical features, image databases are developed for each scale of structure. For the cartilage scaffolds in this study, the cubical pore architectures designed at the 0.1–1 mm scale were generated using software written in the program Interactive Data Language (IDL, ITT Industries, Inc. Boulder, CO). Scaffold external shape for mechanical testing and subcutaneous implantation was also generated using specially written IDL programs. Finally, these two scale levels of databases were merged using Boolean operations to define the final image-based scaffold design. For this study, we used a 3-D cylindrical shaped scaffold with cubical pore shapes where the final 3-D architecture is created by first designing a unit mathematical cell  and repeating this cell periodically in 3-D space.
Poly(1,8-octanediol-co-citrate) pre-polymer (pPOC) was synthesized following protocols described by Ameer and colleagues [37,38] with some modification. Briefly, an equi-molar ratio of 1,8-octanediol and citric acid was reacted at 162.5 °C (160–165 °C) for 15 min with gentle stirring and a constant flow of N2 into the system. Then the system temperature was subsequently lowered to 140 °C and the mixture stirred for another 30–45 min to react further. Post-polymerization of the pre-polymer was done through a modified protocol in order to fabricate designed architecture scaffolds using solid freeform (SFF) fabrication methods. Before post-polymerization of the pre-polymer into architecture scaffolds, wax molds with architecture were built by a Solidscape Patternmaster™ machine. Then hydroxyapatite (HA) molds (inverse of the wax molds) were fabricated using thermally curable HA slurry poured into the wax molds. The pre-polymer was poured into PTFE molds and pre-prepared inverse HA molds were embedded within the pPOC. The pPOC/HA construct inside the PTFE mold was post-polymerized at 80 °C for 4 days without vacuum in an oven. The HA + POC construct was removed from the PTFE mold and the HA mold was then dissolved from the construct using an acid solvent, RDO (APEX Engineering Products Corp., Plainfield, IL) to obtain the final POC scaffold. The fabrication procedure is illustrated in Fig. 1.
In vitro and in vivo scaffold degradation was evaluated using both conventional methods and a novel ultrasound imaging technique. The weight loss (%) vs. degradation time and compressive modulus vs. degradation time were plotted to obtain the correlation between compressive modulus vs. weight loss (%). The pH of the degradation medium in every test tube was measured with a pH meter before and at every week interval of the scaffold degradation.
The dry scaffolds were immersed in medium (high glucose DMEM + 10% fetal bovine serum (FBS) + 1% P/S, Gibco) at 37 °C and shaken by an orbital shaker to reach desired degradation 45% faster and recovered at different periods of time, up to 14 days. After scaffold recovery, the water on the surface was gently removed by filter paper. Then samples for each time point were weighed after water removal and subsequently dried in vacuum until a constant weight was obtained. The weight of the dry scaffold was measured (Wt) and compared with its original weight (W0). The weight lost by degradation was determined as: weight loss = [(W0 Wt)/W0] × 100%. The initial porosity of each scaffold before degradation was measured by using μCT and the dimension of each scaffold was measured by a caliper to keep the original dimension and to avoid any abnormal dimensional changes due to swelling.
For in vitro UEI, three scaffolds were embedded 30 mm apart in a phantom of 1% gelatin (G-2500, Sigma Aldrich Corp., St. Louis, MO) mixed with 0.5% ultrasound scatterer (polystyrene spheres, Amberlite, Sigma Chemical Co., MO). The scaffolds were soaked in deionized water before being embedded in the gel phantom to avoid bubbles being trapped in the pores. A portion of the prepared gelatin solution was first poured into a cubic mould. The scaffold was then embedded halfway as soon as the gelatin starts form. The rest of the gelatin solution was immediately added to fill up the mould. After ultrasound imaging was performed at each stage of the degradation, the samples were recovered and returned to the subsequent degradation process.
A commercial ultrasound (US) scanner (iU22, Philips, Bothell, WA) was used to image and collect consecutive radiofrequency (RF) imaging frames in real-time at 49 Hz over 6 s during continuous deformation of the POC embedded gel phantom by a linear array ultrasound transducer (L8-4, centered at 5 MHz, Philips, Bothell, WA) (see Fig. 2). The ultrasound transducer was fixed to a laboratory designed deformation device to induce a uniform and consistent average strain. The transducer surface measures around 50 mm by 16 mm and directly compresses the gelatin phantom. A phase-sensitive correlation-based 2-D speckle tracking algorithm was applied to determine the in-plane frame-to-frame displacement . To improve the signal-to-noise ratio, frame decimation by factor of 5–10 was applied and incremental frame-to-frame displacements were accumulated referenced to the original geometry (Lagrangian presentation). The axial normal strain was calculated by taking a spatial derivative of the accumulated displacements in the axial direction (ultrasound beam and externally applied deformation direction). Strains for the scaffold at different degradation stages were normalized to the magnitude of the average strain (about 5–10% at total) estimated from the phantom thickness change observed by the ultrasound reflection from the bottom of the phantom, to ensure standardized strain measurements. The speckle in ultrasound image measured about 210 μm (axial) by 380 μm (lateral). The kernel size of the speckle tracking, which will determine the imaging resolution, was set to be 250 μm (axial) by 500 μm (lateral) in this study, which is about 1.2 times the speckle size . The average normalized strain inside the scaffold was estimated to measure the overall alteration of the mechanical property. To examine the spatial variation of the structural degradation inside the scaffold, the coefficient of variation (COV = standard deviation/mean) of the normalized strain was also estimated .
Three scaffolds were implanted subcutaneously in a 5-week-old immunocompromised NIH-III mouse under protocol approved by the University of Michigan Committee on the Use and Care of Animals. The animal was anesthetized with intramuscular injections of ketamine (50 μg g–1) and xylazine (5 μg g–1) in saline. Three dorsal subcutaneous pockets were created by blunt dissection and one scaffold was placed in each pouch. The scaffolds were positioned upright along the long axis of the cylinder. The implantation sites were closed with surgical wound clips. The animal was housed in group with free access to food and water.
Under the approved animal use protocol, the same RF data capturing procedure using the same US scanner as in the in vitro experiment described above was performed. The anesthetized mouse was placed on a custom-built platform in a prone position with its back exposed to the transducer. The imaging transducer also served to compress the scaffolds under the mouse's back surface and underlying tissue. The ultrasound transducer was fixed to a laboratory designed deformation device to induce a uniform and consistent average strain (Fig. 2). The RF frames were captured at a rate of 49 Hz while approximately 5–10% average strain was being generated over 6 s. The signal processing procedures and parameters are mostly same as those used in vitro. Strains for the scaffold at different degradation stages were normalized to the magnitude of the average strain (about 5–10% at total) estimated from the thickness change observed by the ultrasound reflection from the back of the mouse, to ensure standardized strain measurements. Note that 10% deformation corresponds to only 2 mm change out of 20 mm in abdomen thickness of the mouse.
A mechanical measurement system developed in the laboratory capable of measuring the elastic modulus of small tissue samples was used . It tolerates the constraints of biological tissue, such as limited sample size (≤1.5 cm3) and imperfections in sample geometry. The pressing stamp is a cylinder with a diameter of 35 mm. The scaffolds after UEI on each stage of degradation were placed in the sample holder. The elastic modulus was determined by way of strain and simultaneous measurement of resulting force under conditions of continuous deformation.
As described above, six porous POC scaffolds (6.0 mm diameter, 4.0 mm height, 750 μm × 750 μm interconnected cubical pores, porosity 50%) were fabricated and tested. Three of the scaffolds were used for the in vitro study and the other three were implanted in the mouse for in vivo study. In the in vitro study, the scaffolds remained in medium for 14 days until they degraded up to an average 43% by weight loss. The weight measurements of each sample before and after the degradation are listed in Table 1. The accumulated strains referenced to the original geometry were imaged along with the B-scans (Fig. 3). The strain maps overlaid on top of the B-scans (second and third lows in Fig. 3) clearly indicated the degree of scaffold degradation. The average normalized strain generated inside of the scaffold after the degradation (–2.97 ± 0.74) of about 43% by weight was much higher than before the degradation (–0.43 ± 0.03) of the scaffolds. Note that a normalized strain of –1.0 represents that the region of the interest generates the same strain as the average strain estimated by the thickness change of the entire gelatin phantom. The average normalized strains on each sample are listed in Table 1. The increased normalized average strain reflects the weight loss and subsequent elastic property alteration. It was also observed that the strain maps become more inhomogeneous along with scaffold degradation (third row in Fig. 3). The COV after the degradation (25%) was much higher than before the degradation (7%). The increased inhomogeneity of the strain map reflects the possible heterogeneous distribution of structural degradation.
Based on the direct stress–strain measurement curve (Fig. 4), the elastic modulus was determined by taking the slope of the linear least squares fit on the original measurement curve. To assure consistent contact between the pressing stamp and the scaffold samples at the onset of deformations, measurement points were considered invalid if their associated force was less than 10% of the maximal pressing force. Those points with the natural strain greater than 30% were also discarded from elastic modulus estimation due to high deformation of the scaffold samples. The exclusion of the data points beyond this strain range may bias the elastic modulus estimates, but the bias does not alter the separation between before and after the degradation. Within this range of stress–strain relationship, first-order polynomial (linear) fit was applied to estimate the slope. All fits attained a high correlation (r2 > 0.95; see Table 1). The mean elastic modulus among three samples before degradation was 74.1 ± 15.5 kPa. After 43% degradation by weight, the elastic modulus was reduced to 37.7 ± 5.5 kPa.
After 7 days of implantation the weight of the scaffolds was reduced by 23% on average. The weight measurements of each sample before and after the degradation are listed in Table 1. The accumulated strains referenced to the original geometry were imaged along with the B-scans in Fig. 5. The strain maps overlaid on top of the B-scans reflects the degree of the scaffold degradation. Scaffolds after 23% weight degradation showed much higher strains (–1.40 ± 0.24) than those before degradation (–0.21 ± 0.01). The average normalized strains on each sample are listed in Table 1. The increase of inhomogeneity in the strain map was also observed along with the progression of the degradation, reflecting the spatial variation of the structural degradation inside the scaffolds. The COV before the degradation (4.8%) was increased to 17% after the degradation.
Based on the direct stress–strain measurement curve (Fig. 6), the elastic modulus was demonstrated in the same way as the in vitro data. The mean elastic modulus among three samples before degradation was 55.3 ± 1.4 kPa. After 23% degradation by weight, the elastic modulus was reduced to be 37.6 ± 3.9 kPa.
In the in vitro experiments, the scaffolds after degradation exhibited much higher average strain than before degradation. This higher average strain directly reflects the overall alteration of the elasticity of the scaffold samples commensurate with the degradation. The percentage variation of the average normalized strains among the samples was relatively small, as low as 17%. The spatial distribution of the strain map in the scaffolds became inhomogeneous with degradation. The inhomogeneous strain patterns were different from one sample to the other. This could be due either to the random degradation process inside the scaffold structure or a different imaging cross section from one scaffold sample to the other. This inhomogeneity can also be a good signature of the degradation characteristics. This supports the feasibility of monitoring the distribution of the internal tissue ingrowth. The resolution of the strain maps presented in Figs. 3 and and55 is about the kernel size of the speckle tracking centered at 5 MHz, which is 250 μm in axial direction and 500 μm in lateral direction. With higher resolution, using higher frequency transducers up to 100 MHz, the internal structural degradation and tissue growth distribution can be imaged at a resolution down to tens of microns .
The in vivo elasticity imaging illustrates the same pattern of strain increase as found in the in vitro experiments of scaffold degradation. In this feasibility study of UEI for scaffold degradation, it was not intended to monitor tissue regeneration. Thus, the implantation period was limited to 7 days. At the end of the 7 days, a very small amount of granulation tissue was found attached to the surface of the scaffold and it was carefully rinsed off using regular PBS solution and drying off the PBS by filter paper before measuring the weight loss. For the same reasons as discussed for in vitro experiments, different samples show different inhomogeneous strain patterns in the in vivo experiment.
In summary, the strain in the scaffold increased after degradation both in vitro and in vivo. More experiments with a large number of scaffolds with different material and structural characteristics, such as different porosity, will be carried out to further verify results from this initial study. The average strain map clearly differentiates the scaffold before and after degradation both in vitro and in vivo. The increased inhomogeneity in the strain map also reflects the local variability of internal structural decomposition of the scaffold. Preliminary in vitro and in vivo results demonstrate the feasibility of non-invasive ultrasound elasticity imaging to characterize the inter-structural change of the tissue scaffold at high precision and resolution.
From the direct mechanical measurements, stress–strain curves (Figs. 4 and and6)6) also illustrate non-linear elastic behavior of the scaffold. Investigation on non-linearity and elastic modulus reconstruction will add important parameters to fully assess structural, compositional and functional characteristics of the scaffold and engineered tissue.
Depending on the individual pore shape and the distribution of the pores, the internal supporting structure may not be homogeneous inside the scaffold. The degradation process also may vary in space due to the different boundary conditions. To fully characterize the internal structural degradation process, 3-D elasticity imaging is also under investigation . Using either a 2-D transducer array or the same 1-D linear probe used in this 2-D elasticity imaging, scanning the scaffold along the elevation direction (orthogonal to the 2-D imaging plane) using a translational stage at each step of deformation will provide a full 3-D strain map. For a uniform boundary condition, a deformation plate with a large surface area may need to be considered. Based on the 3-D displacement information, a 3-D elastic modulus reconstruction is also under development [46,47].
This technique can also be relatively easily integrated into a commercial ultrasound scanner for various animal studies and possibly translated into human clinical imaging tools.
Although limited by the number of samples and data points, the feasibility of ultrasound elasticity imaging as a non-invasive monitoring tool for the mechanical and degradation property of the tissue scaffolds was demonstrated in vitro and in vivo.
This work was supported in part by NIH grants DE-016129, HL-67647, HL-68658, HL-082640 and EB-003451. The authors thank Philips Ultrasound, Bothell, USA for their system support.