Evaluation of Chronic Pain Using Magnetic Resonance (MR) Neuroimaging Approaches
Bibliographic record
Abstract
OBJECTIVES: Numerous neuroimaging techniques have been recently used to investigate central mechanisms involved in pain perception and to examine morphological and functional brain alterations associated with chronic pain. Compared to self-reporting approaches, objective imaging techniques are expected to potentially lead to better pain assessment and guide management. This comprehensive scoping review aims to identify recent magnetic resonance imaging (MRI) approaches that have been used to characterize the brain of chronic pain subjects, using structural, chemical and functional MRI techniques. METHODS: A systematic search and review of the literature was conducted and the resultant studies were critically examined for relevance. RESULTS: MRI neuroimaging of various chronic pain conditions were summarized. We classified the collected studies into: structural brain alterations, VBM (voxel based morphology) examination of structural changes, DTI, changes in brain chemistry, functional and blood flow brain alterations. DISCUSSION: From our clinical experience, we have noted that most clinicians are not aware of the capabilities of advanced MRI methods in assessing cortical manifestations of chronic pain. In addition, many clinicians are not aware of the cortical alterations present in individuals with chronic pain. This comprehensive scoping review thus sets out to first summarize MRI neuroimaging techniques that are available in the current literature to examine chronic pain. We then identify cortical MR approaches that have been able to reliably predict transition from acute to chronic pain. Finally, we summarize MRI neuroimaging techniques that have been used to track treatment response of individuals with chronic pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.057 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".