Photo credit: www.sciencedaily.com
Brain Imaging Could Predict Spinal Surgery Outcomes
Recent research from Kobe University indicates that a quick 10-minute brain scan can forecast the success of spinal surgeries aimed at relieving severe, persistent pain. These findings provide a valuable tool for healthcare professionals to discuss spinal cord stimulation options with patients.
For individuals suffering from unmanageable chronic pain, spinal cord stimulation (SCS) is often considered a last resort when other treatments fail. This surgical intervention involves implanting electrodes into the spinal column to deliver electrical impulses that disrupt pain signals sent to the brain. The placement of these electrodes is meticulously adjusted so that the stimulation targets the patient’s specific area of discomfort. Anesthesiologist Ueno Kyohei from Kobe University emphasizes the challenge of determining patient suitability for this procedure, noting that current evaluations rely on brief trials lasting from a few days to two weeks. Although these trials are relatively short, they still present risks and invasiveness, leading clinicians to explore non-invasive methods for predicting patient outcomes.
Functional magnetic resonance imaging (fMRI) has emerged as a pivotal technique for examining brain activity. It can reveal which areas of the brain respond to stimuli and how different regions interact. Ueno notes that previous research indicated a negative correlation between the strength of connections within the brain’s default mode network and the effectiveness of the pain medication ketamine. The default mode network is crucial for self-referential thought and has been linked to chronic pain experiences. Additionally, the connection between the default mode network and the salience network—which manages attention and perception of stimuli—was a point of interest for the researchers. Ueno explains, “Thus, we sought to determine if the interaction of activity within and across these networks could be used to anticipate responsiveness to SCS.”
The findings, published in the British Journal of Anaesthesia, reveal that patients who experienced better outcomes from spinal cord stimulation showed weaker connections between specific regions of the default mode network and the salience network. Ueno remarks that this not only provides a promising biomarker for predicting treatment effectiveness but also reinforces theories about dysfunctional connectivity in these networks contributing to chronic pain development.
While fMRI scans offer valuable insights, they are not the sole method for assessing patient responsiveness. The combination of comprehensive pain assessments and clinical evaluations has also proven to be a reliable predictor for spinal cord stimulation outcomes. The research team argues that despite some debate over MRI scan costs, the study highlights a potential reduction in the burden on patients and healthcare providers if a single 10-minute resting state fMRI scan could predict SCS effectiveness.
The study involved 29 participants with various forms of chronic pain, which may explain the overall lower treatment responsiveness observed compared to other studies. Nonetheless, the researchers believe that enhancing predictive capabilities for diverse patient conditions could prove extremely beneficial. Ueno anticipates that future research—including a broader range of case studies and investigations into how different spinal cord stimulation patterns influence specific brain regions—will lead to improved treatment evaluations. Their ultimate goal is to leverage functional brain imaging to optimize spinal cord stimulation therapies tailored to the individual needs of patients.
The research received funding from the Japan Society for the Promotion of Science (grant 21K08993) and was conducted in collaboration with a researcher from Ritsumeikan University.
Source
www.sciencedaily.com