In Vivo 3-Dimensional Morphometric Analysis of the Lumbar Foramen in Healthy Subjects
Bibliographic record
Abstract
STUDY DESIGN: In vivo 3-dimensional (3D) morphometric analysis of the lumbar foramen by using 3D computed tomographic models in normal subjects. OBJECTIVE: To describe foraminal geometry in an asymptomatic cohort measured in 3D. SUMMARY OF BACKGROUND DATA: Appropriate assessment of the complex 3D lumbar foraminal geometry is key to correct radiculopathy diagnosis and treatment planning. To the best of our knowledge, there is no other study that quantifies the normal lumbar foramen 3D geometry considering sex, age groups, and spinal levels in vivo. METHODS: Subject-based 3D computed tomographic lumbar models were created in 59 asymptomatic volunteers and foraminal height and width were measured on the basis of the model by custom software. The foraminal height and width were compared by sex, age, and lumbar level. RESULTS: Overall, the foraminal height decreased with age. However, although the foraminal height in males decreased with age at all spinal levels, the foraminal heights in females did not. The foraminal height was significantly larger in the upper lumbar levels in both sexes. The foraminal width in males was significantly smaller than in females for all age groups. The foraminal width in both sexes also decreased similarly with age. The foraminal widths at the lower lumbar levels were significantly smaller than those at the upper levels. Age-related foraminal width decreases were seen in all lumbar levels as well. CONCLUSION: This study described foraminal geometry in vivo in an asymptomatic cohort measured in 3D. Age-related foraminal height decrease was noticeable in males and in the lower lumbar levels. Age-related foraminal width decrease was shown in both sexes and in all lumbar levels. Such information can be used as baseline data for diagnosis of foraminal stenosis and treatment modality planning.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".