3D Printing of Customizable Phantoms to Replace Cadaveric Models in Upper Extremity Surgical Residency Training

Medical phantoms are commonly used for training and skill demonstration of surgical procedures without exposing a patient to unnecessary risk. The discrimination of these tissues is critical to the ability of young orthopedic surgical trainees to identify patient injuries and properly manipulate surrounding tissues into healing-compliant positions. Most commercial phantoms lack anatomical specificity and use materials that inadequately attempt to mimic human tissue characteristics. This paper covers the manufacturing methods used to create novel, higher fidelity surgical training phantoms. We utilize medical scans and 3D printing techniques to create upper extremity phantoms that replicate both osseous and synovial geometries. These phantoms are undergoing validation through OSATS training of surgical residents under the guidance of attendings and chief residents. Twenty upper extremity phantoms with distal radius fracture were placed into traction and reduced by first- and second-year surgical residency students as part of their upper extremity triage training. Trainees reported uniform support for the training, enjoying the active learning exercise and expressing willingness for participation in future trials. Trainees successfully completed the reduction procedure utilizing tactile stimuli and prior lecture knowledge, showing the viability of synthetic phantoms to be used in lieu of traditional cadaveric models.

Applications of Haptic Technology, Virtual Reality, and Artificial Intelligence in Medical Training During the COVID-19 Pandemic

This paper examines how haptic technology, virtual reality, and artificial intelligence help to reduce the physical contact in medical training during the COVID-19 Pandemic. Notably, any mistake made by the trainees during the education process might lead to undesired complications for the patient. Therefore, training of the medical skills to the trainees have always been a challenging issue for the expert surgeons, and this is even more challenging in pandemics. The current method of surgery training needs the novice surgeons to attend some courses, watch some procedure, and conduct their initial operations under the direct supervision of an expert surgeon. Owing to the requirement of physical contact in this method of medical training, the involved people including the novice and expert surgeons confront a potential risk of infection to the virus. This survey paper reviews recent technological breakthroughs along with new areas in which assistive technologies might provide a viable solution to reduce the physical contact in the medical institutes during the COVID-19 pandemic and similar crises.

A review of computer-based simulators for ultrasound training

SUMMARY STATEMENT

Computer-based simulators for ultrasound training are a topic of recent interest. During the last 15 years, many different systems and methods have been proposed. This article provides an overview and classification of systems in this domain and a discussion of their advantages. Systems are classified and discussed according to the image simulation method, user interactions and medical applications. Computer simulation of ultrasound has one key advantage over traditional training. It enables novel training concepts, for example, through advanced visualization, case databases, and automatically generated feedback. Qualitative evaluations have mainly shown positive learning effects. However, few quantitative evaluations have been performed and long-term effects have to be examined.

Visualization and GPU-accelerated simulation of medical ultrasound from CT images

We present a fast GPU-based method for simulation of ultrasound images from volumetric CT scans and their visualization. The method uses a ray-based model of the ultrasound to generate view-dependent ultrasonic effects such as occlusions, large-scale reflections and attenuation combined with speckle patterns derived from pre-processing the CT image using a wave-based model of ultrasound propagation in soft tissue. The main applications of the method are ultrasound training and registration of ultrasound and CT images.