Sacro-Iliac Joint Sensory Block and Radiofrequency Ablation: Assessment of Bony Landmarks Relevant for Image-Guided Procedures
Bibliographic record
Abstract
Image-guided sensory block and radiofrequency ablation of the nerves innervating the sacro-iliac joint require readily identifiable bony landmarks for accurate needle/electrode placement. Understanding the relative locations of the transverse sacral tubercles along the lateral sacral crest is important for ultrasound guidance, as they demarcate the position of the posterior sacral network (S1–S3 ± L5/S4) innervating the posterior sacro-iliac joint. No studies were found that investigated the spatial relationships of these bony landmarks. The purpose of this study was to visualize and quantify the interrelationships of the transverse sacral tubercles and posterior sacral foramina to inform image-guided block and radiofrequency ablation of the sacro-iliac joint. The posterior and lateral surfaces of 30 dry sacra (15 M/15 F) were digitized and modeled in 3D and the distances between bony landmarks quantified. The relationships of bony landmarks (S1–S4) were not uniform. The mean intertubercular and interforaminal distances decreased from S1 to S4, whereas the distance from the lateral margin of the posterior sacral foramina to the transverse sacral tubercles increased from S1 to S3. The mean intertubercular distance from S1 to S3 was significantly ( p<0.05 ) larger in males. The interrelationships of the sacral bony landmarks should be taken into consideration when estimating the site and length of an image-guided strip lesion targeting the posterior sacral network.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".