Researchers have developed a method to predict how much pain people are feeling based on functional MRI (fMRI) scans, which could pave the way for an objective quantification of pain rather than relying on a patient’s self-reported level of pain, according to research published April 11 in the New England Journal of Medicine.
“If our findings are extended to clinical populations, brain-based signatures could be useful in confirming pain in situations in which patients are unable to communicate pain effectively or when self-reports are otherwise suspect,” wrote Tor Wager, PhD, of the University of Colorado, Boulder, and colleagues.
A total of 114 participants were involved in a series of studies designed to assess thermal pain and distinguish it from social pain. In the first study, Wager and colleagues used a machine-learning analysis to identify a neurologic signature of fMRI activity associated with heat-induced pain. The pattern of activity included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, and the anterior cingulate cortex, among other regions. In three subsequent studies, the authors tested sensitivity and specificity of the signature in a new sample, assessed specificity relative to social pain induced by viewing a photo of an ex-romantic partner, and assessed responsiveness of the measure when a pain reliever was administered.
The authors reported the method demonstrated a sensitivity and specificity of 94 percent or more in discriminating painful heat from nonpainful warmth, pain anticipation and pain recall in the first study group, with similar success in the second sample group. The neurologic signature discriminated between physical and social pain with a sensitivity and specificity of 85 and 73 percent, respectively. The pain relief agent was able to substantially reduce the signature response.
“Such signatures could also help identify functional neuropathologic disorders that may underlie or confer a predisposition to chronic pain, even in the absence of overt structural lesions,” wrote the authors. “More broadly, brain-based signatures could accelerate the identification of neurophysiological subtypes of pain and intermediate markers for treatment discovery.”
In an accompanying editorial, Assia Jaillard, MD, PhD, of Grenoble University in Grenoble, France, and Allan H. Ropper, MD, of Brigham and Women’s Hospital in Boston, acknowledged the promise of the pain research, noting the lack of objective measurements for pain and the limitation of clinical instruments like the visual-analogue scale.
Some measure of hesitation is required, though, as the study had a few limitations, wrote Jaillard and Ropper. Only cutaneous pain, and not pain in the context of disease, was studied, and the photograph of an ex-partner used to elicit social pain is an uncertain stimulus. They called for further studies in more diverse clinical circumstances.
“The studies conducted by Wager and colleagues serve as an example of how functional neuroimaging may help clinicians assess clinical symptoms, such as somatic and emotional pain, that were previously thought to be impenetrable,” wrote Jaillard and Ropper. “Being doctors, though, we may ultimately have to acknowledge that ‘pain is pain’ and can be reported only by the patient.”