Garnette Sutherland M.D.

Garnette Sutherland, MD recently published a paper on entitled: Surgeon at a Workstation: Information Age Surgery. I had the chance to talk to Dr. Sutherland about his work and robotics in particular.

Q. How many papers have you published?

A. About 180 peer-reviewed papers, 25-30 book chapters and 10-20 patents.

Q. When did you know you wanted to be a physician?

A. As an undergrad in chemistry and physical chemistry I enjoyed investigating molecular structure and during this time I decided to apply to medical school. Professors suggested I could always come back to chemistry if the doctor thing didn’t work out. During my summer breaks I returned to the lab for work.

I was particularly influenced to become a neurosurgeon by eminent figures such as Dwight Parkinson, MD, Theodore Rasmussan, MD and Bill Feindel, MD. I was drawn to Ontario by Charles Drake, MD – one of the grandmasters of neurosurgery. He performed thousands of challenging cases but he always took great care examining x-rays when things didn’t go well…not just when procedures were a success. When I began my practice, I continued his tradition. This inspired me to bring imaging into the operating room.

Q. Your paper describing the potential and current usage of robots in surgery and involving brain tumors in particular is fascinating. Give us a little background as to how project neuroArm came about.

A. While having intraoperative images obtained during surgery is wonderful, the process of acquiring the images disrupts surgical rhythm. So I thought it would be great to have a machine that could acquire images during surgery without such a disruption. Essentially, I wanted a machine that could operate within the image as it is acquired. NeuroArm is a step towards this goal.

Q. You mention the system has been used on over 30 cases to date. What have been the primary learnings from these instances?

A. One of the early requirements was to create a workstation that recreates the sight, sound and touch of surgery. The learning curve of using such technology is relatively steep, taking 20 cases to become confident using the unfamiliar tools of the workstation. It became clear that the workstation would be an ideal platform to bring the various technologies of the operating room to a single console.

However, the workstation is not yet perfect. While technology is quickly advancing, it cannot yet perfectly replicate complex human senses like touch. There is still some ways to go in order to understand and replicate touch. As this technology improves, so will the workstation’s ability to transmit the sensations of surgery back to the surgeon.

Garnette Sutherland, M.D. operating NeuroArm

Q. If you were telling a patient why a robotic procedure is optimal for their particular circumstance, what would be the typical drivers for that recommendation? How should a patient weigh their decision?

A. We had to go through normal ethics and regulatory approval processes which includes informed patient consent. The primary indicators for the use of the robot were brain tumor, cavernous angioma, and infection. Patients with these conditions were approached about robotic surgery. Patients were informed that the robot would be integrated in a safe and graded manner. If the situation would not be ideal for robot use, we would revert to conventional procedure. Effective treatment always takes precedence over the experimental use of the robot.

Q. What are some of the bigger challenges associated with getting published?

A. Getting a paper into the review process is not simple. Each journal has different style and formatting requirements, and look for different content. Top journals have a rapid initial review which will determine if the paper is appropriate for their publication. My major critique is that once you submit for peer review and it goes through the process of revisions and resubmissions and so forth it is not uncommon to take a year. This can result in publications that are not timely, and do not accurately reflect current advances.

As a case in point, I have a paper in the queue based on the first 35 robot cases, and by the time it’s published, we will have likely performed 80 robot surgeries. The paper may be out of date before it’s even published. Unfortunately, in the academic world there is a lot of emphasis on publication volume, which might interfere with the research process. This creates a conflict between the length of time it takes for publication and the required output of a career academic.