EEG Biomarkers for Chronic Lower Back Pain

Overseen By Omar Altirkawi

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Stanford University

Disqualifiers: Cancer, Severe psychiatric, Litigation, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 4

130 Participants Needed

Trial Summary

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment Picture Viewing EEG, Resting State EEG, Electroencephalogram, EEG, Resting-State EEG, Stop Signal EEG for chronic lower back pain?

Research suggests that changes in brain activity, as measured by EEG, are linked to improvements in chronic low back pain when using psychological treatments like mindfulness and cognitive therapy. These treatments can alter brain oscillations, which may help reduce pain. ^{1 2 3 4 5}

Is EEG safe for use in humans?

EEG (electroencephalogram) is generally considered safe for use in humans as it is a non-invasive method that records brain activity without causing discomfort or harm. ^{6 7 8 9 10}

How is the EEG treatment for chronic lower back pain different from other treatments?

This treatment is unique because it uses EEG (electroencephalogram) to identify brain activity patterns associated with chronic lower back pain, potentially offering a non-invasive way to understand and treat the condition by focusing on brain mechanisms rather than just the spine. ^{1 3 10 11 12}

What is the purpose of this trial?

Chronic low back pain (CLBP) is a pervasive disorder affecting up to one-fifth of adults globally and is the single greatest cause of disability worldwide. Despite the high prevalence and detrimental impact of CLBP, its treatments and mechanisms remain largely unclear. Biomarkers that predict symptom progression in CLBP support precision-based treatments and ultimately aid in reducing suffering. Longitudinal brain-based resting-state neuroimaging of patients with CLBP has revealed neural networks that predict pain chronification and its symptom progression. Although early findings suggest that measurements of brain networks can lead to the development of prognostic biomarkers, the predictive ability of these models is strongest for short-term follow-up. Measurements of different neural systems may provide additional benefits with better predictive power. Emotional and cognitive dysfunction is common in CLBP, occurring at the behavioral and cerebral level, presenting a unique opportunity to detect prognostic brain-based biomarkers. Likewise, improvements in electroencephalogram (EEG) neuroimaging strategies have led to increased spatial resolution, enabling researchers to overcome the limitations of classically used neuroimaging modalities (e.g., magnetic resonance imaging \[MRI\] and functional MRI), such as high cost and limited accessibility. Using longitudinal EEG, this patient-oriented research project will provide a comprehensive neural picture of emotional, cognitive, and resting-state networks in patients with CLBP, which will aid in predicting symptom progression in CLBP. Through this award, the investigators will use modern EEG source analysis strategies to track biomarkers at baseline and 1- and 2-month follow-ups and their covariance with markers for pain and emotional and cognitive dysfunction. A 5-month follow up will also be used to only assess patient reported outcomes. In Aim 1, the investigators will identify and characterize differences in resting-state, emotional, and cognitive networks between patients with CLPB and age/sex-matched controls. In Aim 2, the investigators will identify within-subject changes across time and their relationship with clinical symptoms. In Aim 3, as an exploratory aim, the investigators will apply machine- and deep-learning strategies to detect a comprehensive signature of CLBP using EEG features from resting-state, emotional, and cognitive networks.

Eligibility Criteria

This trial is for adults with chronic low back pain (CLBP) who can speak English. It's not suitable for individuals with cancer, severe psychiatric conditions, those involved in injury litigation or receiving workers' compensation benefits.

Inclusion Criteria

I have been diagnosed with chronic low back pain.

Exclusion Criteria

Severe psychiatric conditions

Pending personal litigation relating to an injury or receiving workers' compensation benefits

Being a non-English speaker.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Baseline Assessment

Baseline EEG and neuropsychological assessments are conducted

1 week

1 visit (in-person)

Follow-up

Participants undergo EEG and neuropsychological assessments at 1-month and 2-month follow-ups

2 months

2 visits (in-person)

Extended Follow-up

Participants are assessed for patient-reported outcomes at a 5-month follow-up

3 months

1 visit (in-person)

Treatment Details

Interventions

• Picture Viewing EEG
• Resting State EEG
• Stop Signal EEG

Trial Overview The study tests if EEG-based biomarkers can predict the progression of CLBP symptoms. Participants will undergo EEGs to track brain activity related to resting state, emotions, and cognition at baseline and then after 3 and 6 months.

Participant Groups

Group I: Single Arm Experimental Treatment 3 Interventions

All participants will complete all interventions

Who Is Running the Clinical Trial?

Stanford University

Lead Sponsor

Trials

2,527

Recruited

17,430,000+

National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

Collaborator

Trials

508

Recruited

1,090,000+

Findings from Research

A study involving 57 adults with chronic low back pain found that psychological treatments like cognitive therapy, mindfulness meditation, and mindfulness-based cognitive therapy significantly reduced theta and alpha brain wave activity, indicating changes in brain function associated with pain management.

All treatments led to a reduction in beta power across multiple brain regions, with a specific link between reduced beta power in the central region and decreased pain intensity observed only in mindfulness-based cognitive therapy, suggesting that these psychological approaches can effectively alter brain activity related to pain perception.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Change in Brain Oscillations as a Mechanism of Mindfulness-Meditation, Cognitive Therapy, and Mindfulness-Based Cognitive Therapy for Chronic Low Back Pain. Day, MA., Matthews, N., Mattingley, JB., et al.[2022]

In a study involving 50 chronic low back pain (cLBP) patients and 44 healthy controls, abnormal functional connectivity (FC) in specific brain regions was identified, particularly in the medial prefrontal cortex and rostral anterior cingulate cortex, which correlated with pain duration and severity.

The study demonstrated that resting-state functional connectivity could accurately distinguish cLBP patients from healthy controls with 91% accuracy in the initial cohort, suggesting that these brain connectivity patterns may play a crucial role in understanding and managing chronic pain.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Abnormal medial prefrontal cortex functional connectivity and its association with clinical symptoms in chronic low back pain. Tu, Y., Jung, M., Gollub, RL., et al.[2022]

Chronic low back pain (LBP) is associated with significant changes in brain structure and connectivity, as shown by differences in cortical thickness and resting-state functional connectivity in a study of 24 LBP patients compared to 27 healthy controls.

Machine learning analysis of cortical thickness data achieved a classification accuracy of 74.51%, suggesting that these brain changes could serve as biomarkers to help guide more effective treatments for LBP.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multi-modal biomarkers of low back pain: A machine learning approach. Lamichhane, B., Jayasekera, D., Jakes, R., et al.[2021]

Patients with chronic low back pain (cLBP) showed altered brain resting state functional connectivity (FC) in the primary somatosensory cortex (S1), with decreased FC during low-intensity pain and increased FC during high-intensity pain, indicating a dynamic response to pain levels.

Additionally, cLBP patients exhibited increased cortical thickness in areas of S1 associated with the lower back compared to healthy controls, suggesting structural plasticity in the brain related to chronic pain.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

S1 is associated with chronic low back pain: a functional and structural MRI study. Kong, J., Spaeth, RB., Wey, HY., et al.[2021]

This systematic review of 12 studies on low back pain (LBP) found evidence of altered brain function, particularly in balance control and decision-making processes, suggesting that chronic LBP may require more cortical attention and affect sensory processing of pain.

Moderate evidence indicated that while some aspects of sensory processing are altered in LBP, the emotional processing of pain stimuli appears unaffected, highlighting the complexity of brain responses in individuals with chronic low back pain.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Are Functional Brain Alterations Present in Low Back Pain? A Systematic Review of EEG Studies. Schouppe, S., Van Oosterwijck, S., Danneels, L., et al.[2021]

This systematic review analyzed 26 studies on musculoskeletal pain, revealing a trend of decreased alpha and beta EEG power in chronic pain conditions, while resting-state EEG showed increased theta and alpha power in chronic musculoskeletal pain.

The evidence for EEG changes in chronic and experimentally induced musculoskeletal pain is considered 'very low,' indicating that more high-quality research is needed to clarify these EEG characteristics and their implications.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Is There a Difference in EEG Characteristics in Acute, Chronic, and Experimentally Induced Musculoskeletal Pain States? a Systematic Review. Mathew, J., Perez, TM., Adhia, DB., et al.[2023]

This study involving 27 subjects with chronic low back pain found that changes in alpha oscillations of the brain, specifically in the central region, are negatively correlated with perceived pain intensity, suggesting a potential biomarker for pain assessment.

The strongest correlation was observed at the Cz electrode, indicating that measuring alpha power differences between eyes-closed and eyes-open conditions could provide a quantitative method for evaluating chronic pain in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Low Back Pain Assessment Based on Alpha Oscillation Changes in Spontaneous Electroencephalogram (EEG). Feng, L., Li, H., Cui, H., et al.[2022]

In a study involving 14 healthy participants, the experience of acutely induced low back pain (LBP) significantly altered their postural coordination and muscle activation during sit-to-stand movements, leading to longer movement times and decreased force exerted under the feet.

The study found that changes in cerebrocortical activity, specifically the contingent negative variation, correlated with the participants' movement modifications during and after experiencing LBP, suggesting a neural mechanism that could be targeted in future research on LBP-related movement patterns.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Effects of experimentally induced low back pain on the sit-to-stand movement and electroencephalographic contingent negative variation. Jacobs, JV., Yaguchi, C., Kaida, C., et al.[2021]

The study involving 14 patients with chronic low back pain showed that ankle acupuncture (AA) significantly reduced pain intensity, as measured by Visual Analog Scale scores, after treatment (P<0.001).

Brain imaging revealed changes in low-frequency brain activity, specifically a decrease in the left insular and increases in the left precuneus and right precentral gyrus, indicating that AA may provide immediate pain relief through specific brain activity modulation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The low-frequency BOLD signal oscillation response in the insular associated to immediate analgesia of ankle acupuncture in patients with chronic low back pain. Xiang, A., Yu, Y., Jia, X., et al.[2022]

In a study of 95 subjects over 6 months, those who developed chronic pain showed decreased alpha power in their EEG readings, indicating a less relaxed brain state, while those who became pain-free exhibited increased alpha power.

These findings suggest that changes in baseline EEG activity are associated with transitions in pain states, which could inform future treatments like neurofeedback for chronic pain management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Does baseline EEG activity differ in the transition to or from a chronic pain state? A longitudinal study. Schuurman, BB., Vossen, CJ., van Amelsvoort, TAMJ., et al.[2023]

This study identified specific brain connectivity patterns as potential noninvasive biomarkers for chronic low back pain (LBP), achieving an impressive classification accuracy of 83.1% in distinguishing LBP patients from healthy controls based on brain imaging data.

The research introduced a novel feature selection method called Enet-subset, which effectively improved the performance of machine learning classifiers by reducing redundant variables, highlighting its potential for enhancing diagnostic tools in chronic pain assessment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Functional Disruptions of the Brain in Low Back Pain: A Potential Imaging Biomarker of Functional Disability. Lamichhane, B., Jayasekera, D., Jakes, R., et al.[2021]

Individuals with chronic pain exhibit increased theta and alpha EEG power at rest, along with decreased amplitude of evoked potentials during sensory stimulation and cognitive tasks, indicating altered brain activity associated with pain.

Quantitative Electroencephalography (qEEG) may serve as a valuable and objective tool for understanding the brain mechanisms of chronic pain and could be useful for measuring outcomes in therapeutic studies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Electroencephalographic Patterns in Chronic Pain: A Systematic Review of the Literature. Pinheiro, ES., de Queirós, FC., Montoya, P., et al.[2022]

References

1. England pubmed.ncbi.nlm.nih.gov

Change in Brain Oscillations as a Mechanism of Mindfulness-Meditation, Cognitive Therapy, and Mindfulness-Based Cognitive Therapy for Chronic Low Back Pain. [2022]

2. United States pubmed.ncbi.nlm.nih.gov

Abnormal medial prefrontal cortex functional connectivity and its association with clinical symptoms in chronic low back pain. [2022]

3. Netherlands pubmed.ncbi.nlm.nih.gov

Multi-modal biomarkers of low back pain: A machine learning approach. [2021]

4. United States pubmed.ncbi.nlm.nih.gov

S1 is associated with chronic low back pain: a functional and structural MRI study. [2021]

5. United States pubmed.ncbi.nlm.nih.gov

Are Functional Brain Alterations Present in Low Back Pain? A Systematic Review of EEG Studies. [2021]

6. United States pubmed.ncbi.nlm.nih.gov

Is There a Difference in EEG Characteristics in Acute, Chronic, and Experimentally Induced Musculoskeletal Pain States? a Systematic Review. [2023]

7. United States pubmed.ncbi.nlm.nih.gov

Low Back Pain Assessment Based on Alpha Oscillation Changes in Spontaneous Electroencephalogram (EEG). [2022]

8. Germany pubmed.ncbi.nlm.nih.gov

Effects of experimentally induced low back pain on the sit-to-stand movement and electroencephalographic contingent negative variation. [2021]

9. New Zealand pubmed.ncbi.nlm.nih.gov

The low-frequency BOLD signal oscillation response in the insular associated to immediate analgesia of ankle acupuncture in patients with chronic low back pain. [2022]

10. United States pubmed.ncbi.nlm.nih.gov

Does baseline EEG activity differ in the transition to or from a chronic pain state? A longitudinal study. [2023]

11. Switzerland pubmed.ncbi.nlm.nih.gov

Functional Disruptions of the Brain in Low Back Pain: A Potential Imaging Biomarker of Functional Disability. [2021]

12. United States pubmed.ncbi.nlm.nih.gov

Electroencephalographic Patterns in Chronic Pain: A Systematic Review of the Literature. [2022]