Artificial intelligence (AI) and 3D printing will become technologies that profoundly impact humanity. 3D printing of patient-specific organ models is expected to replace animal carcasses, providing scenarios that simulate the surgical environment for preoperative training and educating patients to propose effective solutions. Due to the complexity of 3D printing manufacturing, it is still used on a small scale in clinical practice, and there are problems such as the low resolution of obtaining MRI/CT images, long consumption time, and insufficient realism. AI has been effectively used in 3D printing as a powerful problem-solving tool. This paper introduces 3D printed organ models, focusing on the idea of AI application in 3D printed manufacturing of organ models. Finally, the potential application of AI to 3D-printed organ models is discussed. Based on the synergy between AI and 3D printing that will benefit organ model manufacturing and facilitate clinical preoperative training in the medical field, the use of AI in 3D-printed organ model making is expected to become a reality.

Advanced bionic organ models with vivid biological structures and wetness and softness are essential for medical-surgical training. Still, there are many challenges in the preparation process, such as matching mechanical properties, good feedback on surgical instruments, reproducibility of specific surgical scenarios, and distinguishability between structural levels. In this paper, we achieved tissuemimicking dual-network (DN) hydrogels with customizable stiffness by adjusting the composition of the hydrogel matrix and the immersion time of the ionic solution to match different biological soft tissues precisely. Combined with advanced threedimensional (3D) printing fabrication techniques, various performance-tunable bionic hydrogel organ models with structural complexity and fidelity, including kidney, liver, pancreas, and vascular tissues, were perfectly fabricated. The simulation and applicability of the model were also simulated for the forced change of the suture needle in the puncture and suture of a single tissue and between different tissues, the cutting of substantive organs by ultrasonic scalpel, the coagulation and hemostasis of blood vessels, the visualization of the internal structure under ultrasound, and the microwave ablation of liver tumors. By constructing advanced biomimetic organ models based on hydrogel with specific and tunable properties, the development of surgical training, medical device testing, and medical education reform will be significantly promoted.

Rapid development of three-dimensional (3D) printing technique has enabled the production of many new materials for medical applications but the dry laboratory surgical training model made of soft and flexible materials is still insufficient. We established a new 3D-printed Nissen fundoplication training model of which materials simulate the real mechanical properties. In this study, 16 participants were divided into two groups: Experimental group and control group. The validity of model was tested using Likert scale by the experts and the experimental group. To evaluate the efficacy, performances of the experimental group were scored at the first, fourth, and eighth training by OSATS system and the duration of procedure was compared through the use of recorded video. Meanwhile, an ex vivo model was used to compare the performance of the experiment group and control group after the training in the same way. Our results showed that the 3D-printed model can support the future surgical applications, help improve surgical skills, and shorten procedure time after training.