Minimally Invasive Resection of a Pediatric Lumbar Osteoblastoma: Case Report
Bibliographic record
Abstract
BACKGROUND: Osteoblastomas are locally aggressive bone tumors typically affecting the posterior elements of the vertebral column. The treatment of choice is total surgical resection, traditionally through an open laminectomy, often with facetectomy and fusion when the lesion is in the foramen. OBJECTIVE: To seek an alternative to open surgery, allowing quick and full functional recovery, to meet the youth and athlete population's specific surgical goals. In this population especially, open surgery can be associated with significant impairment and morbidity. METHODS: We report a pediatric case of posterior L5 osteoblastoma completely removed using a facet-sparing and fusion-avoiding contralateral foraminal minimally invasive approach using a tubular retractor system. A 12-yr-old male competitive tennis player presented with progressive right L5 lumbosciatica. Computed tomography scan and magnetic resonance imaging revealed a lesion of the right L5 pedicle, facet, and vertebral body with significant foraminal soft-tissue extension. Being unfit for percutaneous radiofrequency ablation, the patient underwent a minimally invasive biopsy and resection using an 18-mm-wide METRx nonexpandable tubular retractor (Medtronic) through a contralateral approach, sparing the facet and avoiding fusion surgery. RESULTS: Postoperative imaging showed residual tumor. The patient was reoperated in a similar fashion with complete tumor removal. His symptoms resolved completely postoperatively. He resumed tennis within 4 mo and remains symptom- and tumor-free at 12-mo follow-up. CONCLUSION: Minimally invasive contralateral facet-sparing resection of a pediatric lumbar osteoblastoma is an alternative to standard technique and is associated with significant advantages for young athletes, such as quick and full functional recovery, along with avoidance of fusion when the facet joint is involved.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".