Quirks & Quarks

Researchers are reading doctors' brains to see how good they are at surgery

New research suggests neuroimaging might offer a better way to assess surgeon competence

New research suggests neuroimaging might offer a better way to assess surgeon competence

New research suggests neuroimaging might offer a better way to assess surgeon competence. (From research paper)
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Thanks to neuroimaging, there's may be a simpler and more accurate way to assess a new surgeon's skill level.

Using a brain imaging method called "functional near-infrared spectroscopy," researchers were able to see the activity of different regions of the brain while a surgeon performed a simulated surgery, and use patterns of that activity to evaluate their level of expertise.

Dr. Arun Nemani developed this idea in his Ph.D research in biomedical engineering at Rensselaer Polytechnic Institute.

Nemani's technique involves monitoring activity in three areas of the brain —  the primary motor cortex and supplementary motor area which are linked to motor functions; and the prefrontal cortex, which is responsible for motor planning.

He found key differences in the brain activity of skilled groups compared to novice groups. Novice surgeons and unskilled medical students showed increased brain activity in the prefrontal cortex and decreased activity in the two regions responsible for motor function in contrast to expert surgeons and skilled medical students.

Novice surgeons showed increased brain activity in the prefrontal cortex and decreased activities in the primary motor cortex and supplementary motor area when practicing surgery. (From research paper)

This makes sense, explained Nemani, because novices tend to spend more time planning their procedure compared to experienced surgeons and medical students, due to their lack of experience.

He says his method proved superior to the current assessment method, which relies on subjective scores given out by senior surgeons, and demonstrated that neuroimaging offered a more accurate and objective classification of skill levels.

Nemani says the technology could also be adapted to measure performance among other highly skilled professional athletes such as race car drivers or golfers.

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