In vivo 3D tomography of the lumbar spine using a twin robotic X-ray system: quantitative and qualitative evaluation of the lumbar neural foramina in supine and upright position
Bibliographic record
Abstract
Abstract Objectives Supine lumbar spine examinations underestimate body weight effects on neuroforaminal size. Therefore, our purpose was to evaluate size changes of the lumbar neuroforamina using supine and upright 3D tomography and to initially assess image quality compared with computed tomography (CT). Methods The lumbar spines were prospectively scanned in 48 patients in upright (3D tomographic twin robotic X-ray) and supine (30 with 3D tomography, 18 with CT) position. Cross-sectional area (CSA), cranio-caudal (CC), and ventro-dorsal (VD) diameters of foramina were measured by two readers and additionally graded in relation to the intervertebral disc height. Visibility of bone/soft tissue structures and image quality were assessed independently on a 5-point Likert scale for the 18 patients scanned with both modalities. Descriptive statistics, Wilcoxon’s signed-rank test ( p < 0.05), and interreader reliability were calculated. Results Neuroforaminal size significantly decreased at all levels for both readers from the supine (normal intervertebral disc height; CSA 1.25 ± 0.32 cm 2 ; CC 1.84 ± 0.24 cm 2 ; VD 0.88 ± 0.16 cm 2 ) to upright position (CSA 1.12 ± 0.34 cm 2 ; CC 1.78 ± 0.24 cm 2 ; VD 0.83 ± 0.16 cm 2 ; each p < 0.001). Decrease in intervertebral disc height correlated with decrease in foraminal size (supine: CSA 0.88 ± 0.34 cm 2 ; CC 1.39 ± 0.33 cm 2 ; VD 0.87 ± 0.26 cm 2 ; upright: CSA 0.83 ± 0.37 cm 2 , p = 0.010; CC 1.32 ± 0.33 cm 2 , p = 0.015; VD 0.80 ± 0.21 cm 2 , p = 0.021). Interreader reliability for area was fair to excellent (0.51–0.89) with a wide range for cranio-caudal (0.32–0.74) and ventro-dorsal (0.03–0.70) distances. Image quality was superior for CT compared with that for 3D tomography ( p < 0.001; κ , CT = 0.66–0.92/3D tomography = 0.51–1.00). Conclusions The size of the lumbar foramina is smaller in the upright weight-bearing position compared with that in the supine position. Image quality, especially nerve root delineation, is inferior using 3D tomography compared to CT. Key Points • Weight-bearing examination demonstrates a decrease of the neuroforaminal size. • Patients with higher decrease in intervertebral disc showed a narrower foraminal size. • Image quality is superior with CT compared to 3D tomographic twin robotic X-ray at the lumbar spine.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".