Engineers from Dartmouth College are pioneering a new way to make back surgery faster, cheaper and safer.
Engineers from the Thayer School of Engineering and the Geisel School of Medicine at Dartmouth have developed a new real-time 3D tracking system designed to guide surgeons as they operate.
While MRIs and CT scans are frequently used to help surgeons quickly identify common spinal issues (like a herniated disk or compressed vertebrae) it can be difficult to find a clear path to operate. Not only do surgeons have to map a path through tissue and bone, they have to respond as each can move during surgery.
The new system aims to work like Google Maps – only for the body.
By rendering images real-time, with a simple handheld tool, we believe we can make surgeries safer and less costly in the future Study author Keith D. Paulsen
The team have developed a new software algorithm which analyses images from two cameras attached to surgical microscopes. The images are then used to create a real-time 3D image on a monitor. Up to now, similar systems using calibrated stereoscopic camera have been used by brain surgeons – but this is a first for spinal operations.
The new intraoperative stereovision system (iSV) avoids the need for physicians to mark key areas of a patient’s spine, or try to match on-going surgery with a pre-op scan. The team believes their system can save up to half-an-hour on each surgery.
For the study, the iSV was tested on pig spines. However, since publishing their technique the Dartmouth team have developed the technology into a handheld ‘wand’ which can be passed over a patient during surgery.
The next step will be fine-tuning the iSV for use on humans and the team have secured another round of funding from the The National Institutes of Health to continue the systems development.
While could be several years before the iSV is widely used in surgery, the new system is an example of how modern engineering is quietly improving lives.
The technique was published in the Operative Neurosurgery asStereovision Co-Registration in Image-Guided Spinal Surgery: Accuracy Assessment Using Explanted Porcine Spines
