The Importance of Image Guidance in Common Spine Interventional Procedures for Pain Management: A Comprehensive Narrative Review
Bibliographic record
Abstract
INTRODUCTION: Image-guided spinal injections are commonly performed by pain physicians and supported by literature. A recent survey showed that half of the Canadian providers still perform landmark-guided injections. This comprehensive review aims to describe the evidence supporting imaging modalities (fluoroscopy, computed tomography (CT) and ultrasound) in improving the accuracy and safety in several commonly performed spine injections. Relevant anatomy and pitfalls of landmark-guided injections are also discussed. METHODS: An extensive literature search was conducted in PubMed, Medline and Embase databases, complemented by a manual search. Search terms included all spine interventions and imaging modalities. RESULTS: Literature shows that incorrect needle placement without imaging guidance can reach 50% in caudal, 30.4% in lumbar interlaminar and 53% in cervical interlaminar epidural steroid injections. Lumbar and cervical transforaminal steroid injections require imaging to identify intravascular or intradiscal needle placement; misplacement rates can be as high as 20% at cervical, 8% at thoracic, 6-15% at lumbar and 16.5-21% at sacral levels. Imaging techniques for sacroiliac joint steroid injections are superior to non-imaging techniques, while medial branch blocks and facet joint injections require image guidance. CONCLUSION: Image guidance is a mandatory requirement when performing spinal procedures for pain management. Fluoroscopy enhances the safety and accuracy of spinal injections, with stored images benefiting patient records. Ultrasound also has an increasingly important role either alone or with fluoroscopy. CT is also effective but with limited accessibility.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".