In a much needed breakthrough, neuroscientists have developed a technique to predict how much physical pain people are feeling by looking at images of their brain scans.
Until this point, the only way for doctors to "measure" pain is by using a pain scale. This typically involves patient self-reporting — like ranking pain on a scale from 1 to 10 — and observing their behavior.
This can be problematic when doctors have to make important clinical decisions. Patients in pain are notorious for both understating and overstating their degree of pain. Also, some patients may be incapacitated in some way and unable to properly articulate their level of discomfort.
What’s more, there is no unified or industry-standard pain scale currently in use; there are over 20 different scales that are utilized in different jurisdictions and contexts. The lack of consensus on this issue points to how difficult it is to measure what is essentially phenomenological quale — the individualized or subjective experience of pain.
Looking to contribute to ongoing efforts to measure pain, neuroscientists from the University of Colorado Boulder, New York University, Johns Hopkins University, and the University of Michigan set about the task of using functional magnetic resonance imaging (fMRI) to identify objective measures of pain. Their findings now appear in the New England Journal of Medicine.
By looking at the brain scans of 114 participants, the researchers developed a technique to measure and predict pain intensity — and remarkably, at the level of the individual person.
For the experiment, each volunteer was subjected to a painful dose of heat. The experience would leave a pattern, or neurologic signature, for the neuroscientists to study (they used machine-learning analyses to identify a pattern of fMRI activity across a wide series of brain regions).
The signatures were distinguished from other sensory experiences, like nonpainful warmth, pain anticipation, and pain recall. They also found that painkillers helped to reduce the severity of the signatures.
The neuroscientists, a team led by CU-Boulder’s Tor Wager, discovered that the signatures in question are transferable across different people, allowing them to predict pain intensity with over 95% accuracy.
Interestingly, the scientists also measured “social pain.” Some volunteers were shown photographs of romantic partners they had recently broken up with. But this kind of emotional pain did not correspond to the signatures left behind by the physical pain.
Looking ahead, it will be some time yet before physicians can quantify physical pain at the clinical setting. But this is a good sign that the day may eventually arrive.
Images: Shutterstock//Chepko Danil Vitalevich; Tor Wager.