An incoherent HIFU transducer for treatment of the medial branch nerve: Numerical study and in vivo validation
Bibliographic record
Abstract
BACKGROUND: Chronic back pain due to facet related degenerative changes affects 4-6 million patients a year in the United States. Patients refractory to conservative therapy may warrant targeted injections of steroids into the joint or percutaneous medial branch nerve denervation with radiofrequency ablation. We numerically tested a novel noninvasive high intensity focused ultrasound transducer to optimize nerve ablation near a bone-soft tissue interface. METHODS: A transducer with 4 elements operating in an incoherent mode was modeled numerically and tested pre-clinically under fluoroscopic guidance. After 6 lumbar medial branch nerve ablations were performed in 2 pigs, they were followed clinically for 1 week and then sacrificed for pathological evaluation. RESULTS: Simulations show that the acoustic spot size in water at 6 dB was 14mm axial x 1.6mm lateral and 52mm axial x 1.6mm lateral for coherent and incoherent modes, respectively. We measured the size of N = 6 lesions induced in vivo in a pig model and compared them to the size of the simulated thermal dose. The best match between the simulated and measured lesion size was found with a maximum absorption coefficient in the cortical bone adjusted to 30 dB/cm/MHz. This absorption was used to simulate clinical scenarios in humans to generate lesions with no potential side effects at 1000 and 1500 J. CONCLUSION: The elongated spot obtained with the incoherent mode facilitates the targeting during fluoroscopic-guided medial branch nerve ablation.
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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".