A patient-centric approach to surgical excellence: optimizing surgical performance by integrating robotics, machine learning and augmented reality.
Image Credit: VirtaMed
Power Steering for Surgeons
Today, most surgical robots are considered to be at a level similar to the technology that is commonly found in cars, yet we don’t call them robotic cars. Power steering comes as standard in cars, augmenting the driver’s abilities and reducing physical strain while generating consistency when driving.
This is also the main objective of robotics in surgery today, and similar benefits can be observed with robots that can scale motions and assist a surgeon, helping them achieve what is otherwise physically impossible.
An analogy can be made in the field of robotics surgery by drawing from Google Maps and preoperative data. A good route plan offers the driver the best route to reach their destination, and it can update in real-time dependent on the progress and external conditions.
A critical point to note is that the driver has the choice to follow all the information provided by the program or to take an alternative route that suits their view of the situation.
The same should be true for surgeons: that robots and simulators can assist decision making, helping surgeons make well informed choices in the flow of surgery, but the surgeon must have the final say for which actions to take.
Lane Control and Self-Parking
Consider also the rate at which driver technology has advanced over the last decade, including self-parking cars and lane control. Once again technologies such as these facilitate optimal maneuverability of the vehicle via a combination of external data and internal data from sensors embedded throughout the car as well as cameras, LIDAR and planning data from GPS and mapping systems.
This synchronization of all available data is no small feat of engineering, and digital surgery must face up to the same challenges to simultaneously process several data streams and synthesize with preoperative data.
So, to approach this from the perspective of surgical training, the current combination of sensors with sub-millimeter precision with 3D computer models portrays an accurate picture of what a surgeon is doing. Data is utilized to offer intra-operative guidance, such as indicating critical safety issues and to give feedback to the surgeon after the procedure.
Machine learning facilitates the training of models to provide better feedback and identify the best strategies for completing a procedure. If this can be achieved with accuracy and reliability in simulation, then why not in the operating room?
What About Your Co-Drivers?
Decisively, robotic surgery radically alters the mindset and dynamic of the operative team. Communication skills training is vital when it comes to the lead surgeon trusting the first assistant, even when their head is fixed in the surgical console.
Due consideration must be given to the entire surgical team as opposed to focusing on training skills in silos. Each robotic console set up around the patient has a different configuration, with various robotic arms and control consoles that are optimized individually.
No patient wishes to be at the front of the queue when an operating team first uses a new robot. Therefore, the role of mixed reality simulation comes into practice to prepare for the OR setting by accurately replicating relevant scenarios to help reduce the learning curve.
Intuitive Surgical have already trained more than 40,000 surgeons globally on their robotic system, and they have obtained experience regarding how simulation and gamification can create a more motivational training pathway.
The VirtaMed vision incorporates decades of expertise with particularly sensorized simulation environments into the operating room, thus allowing surgeons to take advantage of the data that they generate whenever they utilize a robotic system.
VirtaMed is extremely enthusiastic and committed to exploring new frontiers in robotic healthcare. It is a field that demands collaboration, partnership and transdisciplinary approaches to really push the limits of what is possible.
VirtaMed has already developed excellent partnerships in machine learning with leading universities including the ETH Zurich, and together with innovators and pioneers in robotics, the goal is to make a greater contribution to patient safety.
This information has been sourced, reviewed and adapted from materials provided by VirtaMed.
For more information on this source, please visit VirtaMed.