Synopsis
Innovative 3D printing technology introduces personalized liver models using self-healing elastomers, mimicking liver softness. These models, created swiftly after CT scans, support repetitive surgical simulations, enhancing preoperative planning and training. Preliminary trials show positive outcomes, preventing unforeseen injuries during surgeries. The breakthrough in liver models could significantly advance hepatic surgery safety.
Article:
In the realm of precision medicine, conventional 3D printed models fall short in mimicking organ elasticity. To bridge this gap, a groundbreaking approach employing self-healing elastomers in 3D printing has emerged. Liver models with organ-like softness are crafted swiftly following CT scans, catering to personalized surgical planning and training.
While current 3D models excel in displaying spatial relationships within the liver, they lack the vital ability to replicate the liver's texture and responsiveness to surgical manipulation. The introduction of self-healing materials aims to rectify this, allowing surgeons to repetitively practice surgical maneuvers before actual operations, fostering enhanced preoperative preparations.
Exploration into self-healing materials reveals the necessity for efficient healing at ambient temperatures within minutes. The research identifies physically crosslinked elastomers with hydrogen bond interactions as promising candidates, offering not only self-healing properties but also the required liver-like softness for accurate simulations.
Employing a top-down DLP (digital light processing) technique, a resin concoction comprising rigid and soft monomers, a photo-initiator, and a light absorber is utilized. This resin allows high-fidelity printing of liver models, showcasing both robustness and self-healing capabilities. The resulting elastomers exhibit excellent mechanical properties conducive to surgical simulations.
The self-healing liver models exhibit a remarkable ability to self-repair at room temperature due to the unique molecular design. Pillars with diameters as small as 500μm are printed, emphasizing the high-resolution potential of these elastomers. This breakthrough technology promises repeated cutting and healing, serving as invaluable tools for surgical training and preoperative planning.
Conclusion:
The integration of self-healing elastomers into 3D printing heralds a new era in precision liver surgery. With these models accurately replicating liver softness and responsiveness, surgeons can engage in trial-and-error simulations, significantly bolstering preoperative preparedness. The innovation shows promising signs in preventing unforeseen injuries during surgeries, highlighting its potential to enhance the safety and precision of hepatic surgeries.
