The Role of a Navigational Radiofrequency Ablation Device and Concurrent Vertebral Augmentation for Treatment of Difficult-to-Reach Spinal Metastases
Bibliographic record
Abstract
AIMS: The purpose of this study was to assess the effectiveness of a navigational radiofrequency ablation device with concurrent vertebral augmentation in the treatment of posterior vertebral body metastatic lesions, which are technically difficult to access. Primary outcomes of the study were evaluation of pain palliation and radiologic assessment of local tumor control. MATERIALS AND METHODS: Thirty-five patients with 41 vertebral spinal metastases involving the posterior vertebral body underwent computed tomography-guided percutaneous targeted radiofrequency ablation, with a navigational radiofrequency ablation device, associated with vertebral augmentation. Twenty-one patients (60%) had 1 or 2 metastatic lesions (Group A) and fourteen (40%) patients had multiple (>2) vertebral lesions (Group B). Changes in pain severity were evaluated by visual analog scale (VAS). Metastatic lesions were evaluated in terms of radiological local control. RESULTS: < 0.001). The mean decrease in VAS score between baseline and one week follow up was 4.8 (95% CI 4.2-5.4). VAS decrease over time between one week and one year following radiofrequency ablation was similar, suggesting that pain relief was immediate and durable. Neither patients with 1-2 vertebral metastases, nor those with multiple lesions, showed radiological signs of local progression or recurrence of the tumor in the index vertebrae during a median follow up of 19 months (4-46 months) and 10 months (4-37 months), respectively. CONCLUSION: Treatment of spinal metastases with a navigational radiofrequency ablation device and vertebral augmentation can be used to obtain local tumor control with immediate and durable pain relief, providing effective treatment in the multimodality management of difficult-to-reach spinal metastases.
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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 | 0.000 | 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) | 0.000 | 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".