Design and Fabrication of a Thin-Walled Free-Form Scaffold on the Basis of Medical Image Data and a 3D Printed Template: Its Potential Use in Bile Duct Regeneration.
Suk Hee ParkBo-Kyeong KangJi Eun LeeSeung Woo ChunKiseok JangYoun Hwan KimMi Ae JeongYohan KimKyojin KangNak Kyu LeeDongho ChoiHan Joon KimPublished in: ACS applied materials & interfaces (2017)
Three-dimensional (3D) printing, combined with medical imaging technologies, such as computed tomography and magnetic resonance imaging (MRI), has shown a great potential in patient-specific tissue regeneration. Here, we successfully fabricated an ultrathin tubular free-form structure with a wall thickness of several tens of micrometers that is capable of providing sufficient mechanical flexibility. Such a thin geometry cannot easily be achieved by 3D printing alone; therefore, it was realized through a serial combination of processes, including the 3D printing of a sacrificial template, the dip coating of the biomaterial, and the removal of the inner template. We demonstrated the feasibility of this novel tissue engineering construct by conducting bile duct surgery on rabbits. Moving from a rational design based on MRI data to a successful surgical procedure for reconstruction, we confirmed that the presented method of fabricating scaffolds has the potential for use in customized bile duct regeneration. In addition to the specific application presented here, the developed process and scaffold are expected to have universal applicability in other soft-tissue engineering fields, particularly those involving vascular, airway, and abdominal tubular tissues.
Keyphrases
- tissue engineering
- magnetic resonance imaging
- contrast enhanced
- computed tomography
- stem cells
- minimally invasive
- molecularly imprinted
- electronic health record
- healthcare
- diffusion weighted imaging
- big data
- positron emission tomography
- magnetic resonance
- wound healing
- gene expression
- high resolution
- human health
- deep learning
- high glucose
- coronary artery bypass
- optical coherence tomography
- machine learning
- atrial fibrillation
- risk assessment
- endothelial cells
- data analysis
- coronary artery disease
- dual energy
- artificial intelligence
- solid phase extraction