CHAI3DCHAI3D

Planning

Traditionally, surgeons prepare for an operation by studying image data, such as CT or MRI, in two-dimensions. Conceptualizing an accurate three-dimensional plan based on two-dimensional imaging is exceedingly difficult.

Using the CHAI3D haptics library, the Stanford BioRobotics Lab, in collaboration with Stanford Otolaryngology, has developed a surgical simulation platform that allows surgeons to both haptically and visually rehearse procedures on their patients’ specific anatomy before the operation. Volume-rendered, three-dimensional models can be viewed from any angle and can be manipulated in a surgically-meaningful way.

Within the simulation, a virtual procedure can be simultaneously followed via conventional tri-planar images for guidance, anatomical reference, and to monitor tissue removal. An endoscope can be used to visualize hard to reach or conceptually difficult anatomy, useful both pre-operatively and for training.

 

 

In conjunction with pre-operative surgical rehearsal, we have developed a virtual library of cases accessible to surgeons and trainees alike. A virtual case can be linked to the patient’s intra-operative surgical video, and can be followed for education and training. Similarly a trainee may attempt a procedure and at anytime overlay the same procedure performed by an expert, visually noting where the trainee has over- or under-dissected.

By way of segmentation, our simulator can represent difficult to comprehend anatomical spatial relationships while remaining specific to a particular patient’s anatomy. Finally, by exporting models and dissections from the simulation to offline rendering systems such as Autodesk Maya, we can use patient-specific data to create realistic, immersive anatomical and surgical training modalities, replacing traditional 2D anatomical textbooks.

In the hands of both novice and expert surgeons, we are currently validating our simulator to objectively measure performance enhancement obtained by pre-operative surgical rehearsal, ultimately leading to safer and more effective patient care.

Reference

CardinalSim project site