Featured Research

from universities, journals, and other organizations

Progress reported in quest to create objective method of detecting pain

Date:
December 17, 2012
Source:
Stanford University Medical Center
Summary:
A method of analyzing brain structure using advanced computer algorithms accurately predicted 76 percent of the time whether a patient had lower back pain according to a new study.

A method of analyzing brain structure using advanced computer algorithms accurately predicted 76 percent of the time whether a patient had lower back pain in a new study by researchers from the Stanford University School of Medicine.

The study, published online Dec. 17 in Cerebral Cortex, reported that using these algorithms to read brain scans may be an early step toward providing an objective method for diagnosing chronic pain.

"People have been looking for an objective pain detector -- a 'pain scanner' -- for a long time," said Sean Mackey, MD, PhD, chief of the Division of Pain Medicine and professor of anesthesiology, pain and perioperative medicine, and of neurosciences and neurology. "We're still a long way from that, but this method may someday augment self-reporting as the primary way of determining whether a patient is in chronic pain."

The need for a better way to objectively measure pain instead of relying solely on self-reporting has long been acknowledged. But the highly subjective nature of pain has made this an elusive goal. Advances in neuroimaging techniques have initiated a debate over whether this may be possible. Such a tool would be particularly useful in treating very young or very old patients or others who have difficulty communicating, Mackey said.

In a study published last year in PLoS ONE, Mackey and colleagues used computer algorithms to analyze magnetic resonance imaging scans of the brain to accurately measure thermal pain in research subjects 81 percent of the time. But the question remained whether this could be a successful method for measuring chronic pain.

The goal of the new study was to accurately identify patients with lower back pain vs. healthy individuals on the basis of structural changes to the brain, and also to investigate possible pathological differences across the brain.

Researchers conducted MRI scans of 47 subjects who had lower back pain and 47 healthy subjects. Both groups were screened for medication use and mood disorders. The average age was 37.

The idea was to "train" a linear support vector machine -- a computer algorithm invented in 1995 -- on one set of individuals, and then use that computer model to accurately read the brain scans and classify pain in a completely new set of individuals.

The method successfully predicted the patients with lower back pain 76 percent of the time.

"Lower back pain is the most common chronic condition we deal with," Mackey said. "In many cases, we don't understand the cause. What we have learned is that the problem may not be in the back, but in the amplification coming from the back to the brain and nervous system. In this study, we did identify brain regions we think are playing a role in this phenomena."

An estimated 100 million Americans suffer from chronic pain, and chronic low back pain, in particular, is the most common cause for activity limitation in those younger than 45, according to the study. The prevalence of lower back pain among the U.S. population has also risen significantly, from 3.9 percent in 1992 to 10.2 percent in 2006.

"Previous studies have shown that there are functional changes in the brain of a chronic pain patient, and we show that structural changes may be used to differentiate between those with chronic lower back pain and those without," said former research assistant Hoameng Ung, the first author of the study who is now an MD/PhD student at the University of Pennsylvania School of Medicine. "This observation also suggests a role of the central nervous system in chronic pain, and that some types of chronic low back pain may reflect pathology not within the back, but instead within the brain."

Study results suggested that lower back pain is characterized by a pattern of structural changes in the gray matter, the nervous tissue of the brain, showing indication of disease.

"Our investigation ... suggests that the pathology of lower back pain involves changes in gray matter that are present throughout a distributed system of pain processing and pain-associated areas within the brain," the study stated.

This work was supported by a grant from the National Institutes of Health (DA026092, DA029262, DA023609), an International Association for the Study of Pain collaborative research grant and the Redlich Pain Research Endowment.


Story Source:

The above story is based on materials provided by Stanford University Medical Center. The original article was written by Tracie White. Note: Materials may be edited for content and length.


Journal Reference:

  1. H. Ung, J. E. Brown, K. A. Johnson, J. Younger, J. Hush, S. Mackey. Multivariate Classification of Structural MRI Data Detects Chronic Low Back Pain. Cerebral Cortex, 2012; DOI: 10.1093/cercor/bhs378

Cite This Page:

Stanford University Medical Center. "Progress reported in quest to create objective method of detecting pain." ScienceDaily. ScienceDaily, 17 December 2012. <www.sciencedaily.com/releases/2012/12/121217234959.htm>.
Stanford University Medical Center. (2012, December 17). Progress reported in quest to create objective method of detecting pain. ScienceDaily. Retrieved April 16, 2014 from www.sciencedaily.com/releases/2012/12/121217234959.htm
Stanford University Medical Center. "Progress reported in quest to create objective method of detecting pain." ScienceDaily. www.sciencedaily.com/releases/2012/12/121217234959.htm (accessed April 16, 2014).

Share This



More Health & Medicine News

Wednesday, April 16, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Ebola Outbreak Now Linked To 121 Deaths

Ebola Outbreak Now Linked To 121 Deaths

Newsy (Apr. 15, 2014) The ebola virus outbreak in West Africa is now linked to 121 deaths. Health officials fear the virus will continue to spread in urban areas. Video provided by Newsy
Powered by NewsLook.com
Cognitive Function: Is It All Downhill From Age 24?

Cognitive Function: Is It All Downhill From Age 24?

Newsy (Apr. 15, 2014) A new study out of Canada says cognitive motor performance begins deteriorating around age 24. Video provided by Newsy
Powered by NewsLook.com
How Mt. Everest Helped Scientists Research Diabetes

How Mt. Everest Helped Scientists Research Diabetes

Newsy (Apr. 15, 2014) British researchers were able to use Mount Everest's low altitudes to study insulin resistance. They hope to find ways to treat diabetes. Video provided by Newsy
Powered by NewsLook.com
Carpenter's Injury Leads To Hundreds Of 3-D-Printed Hands

Carpenter's Injury Leads To Hundreds Of 3-D-Printed Hands

Newsy (Apr. 14, 2014) Richard van As lost all fingers on his right hand in a woodworking accident. Now, he's used the incident to create a prosthetic to help hundreds. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins