Use and applicability of magnetic resonance elastography of the lumbar spine in adults: a scoping review
Bibliographic record
Abstract
BACKGROUND: Magnetic Resonance Elastography (MRE) is a non-invasive imaging technique that quantifies tissue stiffness by analyzing shear wave propagation. While MRE is widely used in hepatic imaging, its application in the lumbar spine remains an emerging field. Understanding the repeatability and reproducibility of MRE measurements in the lumbar spine is crucial for its clinical implementation. This scoping review aims to summarize current evidence on the use and applicability of MRE for assessing lumbar spine structures, including intervertebral discs and paraspinal muscles. METHODS: A systematic literature search was conducted in MEDLINE (PubMed), CINAHL, Embase, and The Cochrane Library. Studies investigating MRE of the lumbar spine in adult populations were included. Key aspects such as MRE acquisition methods, repeatability and reproducibility of measurements, and study heterogeneity were assessed. Extracted data were categorized based on study design, imaging techniques, and primary outcomes related to lumbar stiffness assessment. RESULTS: This review identified 11 relevant studies. These studies demonstrated the capability of MRE to characterize shear stiffness in the lumbar intervertebral discs and paravertebral muscles, in both resting states, across various muscle conditions, and under different interventions such as physical activity and therapeutic taping. The review documents the heterogeneous methodological approaches of the studies, highlighting the innovative but varied approaches to this field. Due to this, diverse findings were reported, some of which were contradictory. CONCLUSION: The current evidence of MRE of the lumbar spine is promising though limited due to heterogeneous study methodologies. Future research should focus on larger, multicenter studies with standardized protocols. Despite the current limitations in evidence, MRE holds potential for non-invasive lumbar spine assessment and further research validation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, not a consensus.
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".