This study aims to display the ability and efficacy of 3D printing image-based, implantable biological scaffolds with varying properties. In this study, scaffolds were printed using various ratios of hydroxyapatite (HA) to polycaprolactone (PCL) to display a spectrum of properties suitable for musculoskeletal scaffolds. As an initial application of this method, scaffolds were generated from a series of one hundred DICOM images for a 60-year-old, female proximal femur. Additional structures, including a printed box and a circular lattice were generated. These models were printed at HA to PCL ratios (m/m) of 1:9, 2:8, 3:7, 4:6, 5:5, 6:4, 7:3, 8:2, and 9:1. Postprinting analysis of the ratios was performed with scanning electron microscopy to observe the prints’ microstructure. Post printing analysis also included a compression test to observe biomechanical properties and a cell culture on the prints to observe cellular viability and adhesion. Ratios showed vast microstructural differences. It was also found that the 6:4 sample had the most similar surface level microstructure to that of human trabecular bone. The compression test revealed a positive correlation (R2 = 0.92) between HA concentration (%) and stiffness (N/mm). Cellular viability and adhesion were confirmed for 10 days after initial seeding cells.
Nasal septal perforations (NSPs) are relatively common. They can be problematic for both patients and head and neck reconstructive surgeons who attempt to repair them. Often, this repair is made using an interpositional graft sandwiched between bilateral mucoperichondrial advancement flaps. The ideal graft is nasal septal cartilage. However, many patients with NSP lack sufficient septal cartilage to harvest. Harvesting other sources of autologous cartilage grafts, such as auricular cartilage, adds morbidity to the surgical case and results in a graft that lacks the ideal qualities required to repair the nasal septum. Tissue engineering has allowed for new reconstructive protocols to be developed. Currently, the authors are unaware of any new literature that looks to improve repair of NSP using custom tissue-engineered cartilage grafts. The first step of this process involves developing a protocol to print the graft from a patient's pre-operative CT.
In this study, CT scans were converted into STereoLithography (STL) file format. The subsequent STL files were transformed into 3D printable G-Code using the Slic3r software. This allowed us to customize the parameters of our print and we were able to choose a layer thickness of 0.1mm. A desktop 3D bioprinter (BioBot 1) was then used to construct the scaffold.
This method resulted in the production of a PCL scaffold that precisely matched the patient’s nasal septal defect, in both size and shape. This serves as the first step in our goal to create patient-specific tissue engineered nasal septal cartilage grafts for NSP repair.
Bioprinting of tissue has its applications throughout medicine. Recent advances in medical imaging allows the generation of 3-dimensional models that can then be 3D printed. However, the conventional method of converting medical images to 3D printable G-Code instructions has several limitations, namely significant processing time for large, high resolution images, and the loss of microstructural surface information from surface resolution and subsequent reslicing. We have overcome these issues by creating a JAVA program that skips the intermediate triangularization and reslicing steps and directly converts binary dicom images into G-Code.
In this study, we tested the two methods of G-Code generation on the application of synthetic bone graft scaffold generation. We imaged human cadaveric proximal femurs at an isotropic resolution of 0.03mm using a high resolution peripheral quantitative computed tomography (HR-pQCT) scanner. These images, of the Digital Imaging and Communications in Medicine (DICOM) format, were then processed through two methods. In each method, slices and regions of print were selected, filtered to generate a smoothed image, and thresholded. In the conventional method, these processed images are converted to the STereoLithography (STL) format and then resliced to generate G-Code. In the new, direct method, these processed images are run through our JAVA program and directly converted to G-Code. File size, processing time, and print time were measured for each.
We found that this new method produced a significant reduction in G-Code file size as well as processing time (92.23% reduction). This allows for more rapid 3D printing from medical images.
Current methods of bone graft treatment for critical size bone defects can give way to several clinical complications such as limited available bone for autografts, non-matching bone structure, lack of strength which can compromise a patient’s skeletal system, and sterilization processes that can prevent osteogenesis in the case of allografts. We intend to overcome these disadvantages by generating a patient-specific 3D printed bone graft guided by high-resolution medical imaging. Our synthetic model allows us to customize the graft for the patients’ macro- and microstructure and correct any structural deficiencies in the re-meshing process. These 3D-printed models can presumptively serve as the scaffolding for human mesenchymal stem cell (hMSC) engraftment in order to facilitate bone growth. We performed highresolution CT imaging of a cadaveric human proximal femur at 0.030-mm isotropic voxels. We used these images to generate a 3D computer model that mimics bone geometry from micro to macro scale represented by STereoLithography (STL) format. These models were then reformatted to a format that can be interpreted by the 3D printer. To assess how much of the microstructure was replicated, 3D-printed models were re-imaged using micro-CT at 0.025-mm isotropic voxels and compared to original high-resolution CT images used to generate the 3D model in 32 sub-regions. We found a strong correlation between 3D-printed bone volume and volume of bone in the original images used for 3D printing (R2 = 0.97). We expect to further refine our approach with additional testing to create a viable synthetic bone graft with clinical functionality.