High-fidelity 3D modelling of the lumbar dorsal rami
Bibliographic record
Abstract
Objective: Lumbar medial branch denervation is commonly used to treat chronic facetogenic low back pain. Controversy exists regarding risk to adjacent neural structures. The objectives of this cadaveric study were to: (1) dissect, digitize, and model in 3D the branches of the first (L1) to fifth (L5) lumbar dorsal rami located near the junction of the transverse process and lateral neck of the superior articular process; and (2) quantify the minimal distance between the lateral/intermediate and medial branches at the anterior quarter and midpoint of the lateral neck of the superior articular process. Design: Eighteen formalin-embalmed specimens were dissected, digitized and modeled in 3D. The high-fidelity 3D models were used to compare branching patterns and quantify the mean minimal distance between the lateral/intermediate and medial branches of the lumbar dorsal ramus at the anterior quarter and midpoint of the lateral neck of the superior articular process. A Two-way ANOVA was performed to determine if difference of mean distances was significant. Results: There was variability in the branching pattern of the lumbar dorsal rami. In 46 cases (51.1%) the lumbar dorsal ramus divided into 2 branches, in 41 cases (45.6%) into 3, and in 3 cases (3.3%) 4. The mean minimal distance between the lateral/intermediate and medial branches was significantly greater at the midpoint (3.2 ± 2.5 mm) than the anterior quarter (1.2 ± 1.8 mm) of the lateral neck of superior articular process. Conclusion: Minimal distance measurements between the branches of the lumbar dorsal rami at the anterior quarter and midpoint of the lateral neck of the superior articular process were computed. When placing the distal end of the needle tip at the anterior quarter of the lateral neck of the superior articular process, the smaller mean minimal distance between the branches suggests there is a greater risk for inadvertent denervation of the lateral/intermediate branches. Further anatomical and clinical investigations are required.
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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) | 0.000 | 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) | 0.003 | 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 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".