Diagnosing the source of lower back pain is notoriously difficult for physicians—current methods have been criticized as ineffective, inaccurate and unreliable—but a combined decision-making approach could help identify the problem with greater certainty and less fuss, researchers wrote in PLOS ONE this month.
Corresponding author Ralf H. J. M. Kurvers, MPIB, and colleagues wrote that while clinicians typically resort to radiography, computed tomography (CT) and MR imaging to diagnose lumbosacral injuries, the medical field is losing faith that those methods are the best tools for the job.
“The use of these techniques has dramatically increased in recent years, despite severe criticism of their validity and effectiveness and practice guidelines advising against the routine use of such techniques,” Kurvers and co-authors said. “Studies evaluating the validity and reliability of different lumbosacral spine image reading methods have reported mixed results, ranging from low to high levels of validity and reliability. All of this suggests that diagnosing low back pain is a highly complex task.”
Collective intelligence—or the idea that combining multiple minds to solve a problem results in increased sensitivity and specificity—is one approach that hasn’t been explored in this case, the authors wrote. The technique has been successful in studies of dermatologists diagnosing skin lesions, radiologists assessing mammograms and clinicians predicting positive bone scans.
Kurvers and his team said it is imperative to find a solution outside of MRI and CT, since one-third of U.S. adults have reported lower back pain in the past three months and it’s the second most common reason for clinic visits in the country.
The researchers gathered groups of chiropractors, chiropractic radiologists and medical radiologists, deeming them “raters," and asked them to evaluate two studies. The first study was completed by 13 raters who independently rated 300 lumbosacral radiographs, while the second consisted of 14 raters independently rating 100 lumbosacral MRIs.
Raters noted abnormalities in both cases, the authors wrote, and study leaders combined the responses at the end for a majority rule decision.
“Our results show that with increasing group size, both sensitivity and specificity increased in both datasets, with groups consistently outperforming single raters,” Kurvers and colleagues said. “These results were found for radiographs and MR image reading alike.”
The researchers said results like this are promising, but physicians will need to weigh the pros and cons of a collective approach before applying it in a clinical setting. While the method seems to boost diagnostic accuracy, it also requires increased viewing time by healthcare providers, and radiologists are often already strapped for time.
“Diagnosing the causes of low back pain is a challenging task, prone to errors,” Kurvers et al. said. “This study showed that pooling independent ratings increases the diagnostic accuracy in lumbosacral spine image interpretation.”
After graduating from Indiana University-Bloomington with a bachelor’s in journalism, Anicka joined TriMed’s Chicago team in 2017 covering cardiology. Close to her heart is long-form journalism, Pilot G-2 pens, dark chocolate and her dog Harper Lee.