Thoracolumbar Vertebral Endplate Defect Morphology
Bibliographic record
Abstract
STUDY DESIGN: A descriptive, cross-sectional cadaver study. OBJECTIVE: This study aimed to provide a thorough depiction of vertebral endplate defects classified based on their morphologic features and reported with respect to size, location, and prevalence in the human cadaveric spines of older adults. SUMMARY OF BACKGROUND DATA: Back pain has been associated with vertebral endplate defects; however, findings have been inconsistent. This is partially due to miscommunication surrounding the classification of endplate defects observed using clinical imaging, and limited knowledge of the types of defects present on the endplate and their prevalence. A comprehensive study of vertebral endplates is needed to clarify types of structural defects, their character, and prevalence. MATERIALS AND METHODS: Using micro-computed tomography, 3-dimensional reconstructed images were created of 409 endplates from 19 cadaveric spines (9 men and 10 women; aged 62-91; T6-S1). Endplate defects were categorized based on their morphology, size, and location to investigate distribution patterns. RESULTS: Seven types of endplate defects were identified: Schmorl nodes, corner fracture or limbus vertebra, other fractures, erosion, jagged surface, calcification, and depressions. Defects were identified on 63.6% of endplates. Multiple defects were present on 19.1% of endplates. Fracture and erosion were the most common defect types. Defects were more common on the endplate cranial to the intervertebral disc and in male specimens ( P = 0.01). Defects were larger in the lumbar spine and the "total area of endplate defect" was larger on the cranial than the caudal endplate in the thoracic spine ( P < 0.05). CONCLUSION: This is the first study of which we are aware that provides a thorough depiction of the morphology and distribution of endplate defects across the entire lower thoracic and lumbar spine (T6-S1) using micro-computed tomography. Results support the presence of several distinct endplate defect phenotypes with different prevalence rates and provide a reference when considering endplate defects in the elderly.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".