Researchers Move Closer to Objectively Quantifying Pain

A preliminary study suggests fMRI can be used to determine pain response

1 min read
Researchers Move Closer to Objectively Quantifying Pain

Pain management is one of the most difficult areas of medicine. Clinicians have little to go on beyond patients' self-reports, which can be highly variable. If doctors underestimate a patient's pain, they risk causing unnecessary suffering, but if they employ a better-safe-than-sorry approach, they risk over-medicating with drugs that are increasingly associated with abuse.

There have been various attempts to quantify pain as a physiological phenomenon, but none have proved effective enough to replace self-reporting. Now researchers at Stanford University have published a study of a promising fMRI-based solution.

The researchers used a machine-learning algorithm to recognize specific patterns in the fMRI data. They then found an association between certain patterns and pain in both self-reporting and non-reporting patients, implying a high degree of similarity across subjects. Although specific brain areas, such as the secondary somatosensory cortex, were implicated in the study, the researchers found that a whole-brain approach was more accurate at predicting pain than any individual brain region on its own (86.6 percent, compared to 71.9 percent for the secondary somatosensory cortex and 64.3 percent for a region called the mid-insular cortex).

The next step is to try to make the model robust enough to distinguish between different types of pain--for example, thermal versus mechanical--and to localize where on the body the pain is being experienced. Physicians will probably always have to rely on patient descriptions of pain to some degree, but experiments such as these offer hope that they will soon be able to bolster those qualitative ratings with more objective measurements, which should improve treatment outcomes.

Photo, the National Library of Medicine

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A photo showing machinery in a lab

Foundries such as the Edinburgh Genome Foundry assemble fragments of synthetic DNA and send them to labs for testing in cells.

Edinburgh Genome Foundry, University of Edinburgh

In the next decade, medical science may finally advance cures for some of the most complex diseases that plague humanity. Many diseases are caused by mutations in the human genome, which can either be inherited from our parents (such as in cystic fibrosis), or acquired during life, such as most types of cancer. For some of these conditions, medical researchers have identified the exact mutations that lead to disease; but in many more, they're still seeking answers. And without understanding the cause of a problem, it's pretty tough to find a cure.

We believe that a key enabling technology in this quest is a computer-aided design (CAD) program for genome editing, which our organization is launching this week at the Genome Project-write (GP-write) conference.

With this CAD program, medical researchers will be able to quickly design hundreds of different genomes with any combination of mutations and send the genetic code to a company that manufactures strings of DNA. Those fragments of synthesized DNA can then be sent to a foundry for assembly, and finally to a lab where the designed genomes can be tested in cells. Based on how the cells grow, researchers can use the CAD program to iterate with a new batch of redesigned genomes, sharing data for collaborative efforts. Enabling fast redesign of thousands of variants can only be achieved through automation; at that scale, researchers just might identify the combinations of mutations that are causing genetic diseases. This is the first critical R&D step toward finding cures.

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