Time-optimized X-ray micro-CT imaging of polymer based scaffolds

Computed tomography technologies to measure key structural features of polymeric biomedical implants from bench to bedside

Implanted polymeric devices, designed to encourage tissue regeneration, require porosity. However, characterizing porosity, which affects many functional device properties, is non-trivial. Computed tomography (CT) is a quick, versatile, and non-destructive way to gain 3D structural information, yet various CT technologies, such as benchtop, preclinical and clinical systems, all have different capabilities. As system capabilities determine the structural information that can be obtained, seamless monitoring of key device features through all stages of clinical translation must be engineered intentionally. Therefore, in this study we tested feasibility of obtaining structural information in pre-clinical systems and high-resolution micro-CT (μCT) under physiological conditions. To overcome the low CT contrast of polymers in hydrated environments, radiopaque nanoparticle contrast agent was incorporated into porous devices. The size of resolved features in porous structures is highly dependent on the resolution (voxel size) of the scan. As the voxel size of the CT scan increased (lower resolution) from 5 to 50 μm, the measured pore size was overestimated, and percentage porosity was underestimated by nearly 50%. With the homogeneous introduction of nanoparticles, changes to device structure could be quantified in the hydrated state, including at high-resolution. Biopolymers had significant structural changes post-hydration, including a mean increase of 130% in pore wall thickness that could potentially impact biological response. By incorporating imaging capabilities into polymeric devices, CT can be a facile way to monitor devices from initial design stages through to clinical translation.

Micro-CT - a digital 3D microstructural voyage into scaffolds: a systematic review of the reported methods and results

BACKGROUND

Cell behavior is the key to tissue regeneration. Given the fact that most of the cells used in tissue engineering are anchorage-dependent, their behavior including adhesion, growth, migration, matrix synthesis, and differentiation is related to the design of the scaffolds. Thus, characterization of the scaffolds is highly required. Micro-computed tomography (micro-CT) provides a powerful platform to analyze, visualize, and explore any portion of interest in the scaffold in a 3D fashion without cutting or destroying it with the benefit of almost no sample preparation need.

MAIN BODY

This review highlights the relationship between the scaffold microstructure and cell behavior, and provides the basics of the micro-CT method. In this work, we also analyzed the original papers that were published in 2016 through a systematic search to address the need for specific improvements in the methods section of the papers including the amount of provided information from the obtained results.

CONCLUSION

Micro-CT offers a unique microstructural analysis of biomaterials, notwithstanding the associated challenges and limitations. Future studies that will include micro-CT characterization of scaffolds should report the important details of the method, and the derived quantitative and qualitative information can be maximized.

Micro-computed tomography characterization of tissue engineering scaffolds: effects of pixel size and rotation step

Quantitative assessment of micro-structure of materials is of key importance in many fields including tissue engineering, biology, and dentistry. Micro-computed tomography (µ-CT) is an intensively used non-destructive technique. However, the acquisition parameters such as pixel size and rotation step may have significant effects on the obtained results. In this study, a set of tissue engineering scaffolds including examples of natural and synthetic polymers, and ceramics were analyzed. We comprehensively compared the quantitative results of µ-CT characterization using 15 acquisition scenarios that differ in the combination of the pixel size and rotation step. The results showed that the acquisition parameters could statistically significantly affect the quantified mean porosity, mean pore size, and mean wall thickness of the scaffolds. The effects are also practically important since the differences can be as high as 24% regarding the mean porosity in average, and 19.5 h and 166 GB regarding the characterization time and data storage per sample with a relatively small volume. This study showed in a quantitative manner the effects of such a wide range of acquisition scenarios on the final data, as well as the characterization time and data storage per sample. Herein, a clear picture of the effects of the pixel size and rotation step on the results is provided which can notably be useful to refine the practice of µ-CT characterization of scaffolds and economize the related resources.