A Spine-Specific Phased Array for Transvertebral Ultrasound Therapy: Design and Simulation
Bibliographic record
Abstract
OBJECTIVE: To design and simulate the performance of two spine-specific phased arrays in sonicating targets spanning the thoracic spine, with the objective of efficiently producing controlled foci in the spinal canal. METHODS: Two arrays (256 elements each, 500 kHz) were designed using multi-layered ray acoustics simulation: a four-component array with dedicated components for sonicating via the paravertebral and transvertebral paths, and a two-component array with spine-specific adaptive focusing. Mean array efficiency (canal focus pressure/water focus pressure) was evaluated using forward simulation in neutral and flexed spines to investigate methods that reduce spine-induced insertion loss. Target-specific four-component array reconfiguration and lower frequency sonication (250 kHz) were tested to determine their effects on array efficiency and focal dimensions. RESULTS: When neutral, two- and four-component efficiencies were [Formula: see text]% and [Formula: see text]%, respectively, spine flexion significantly increased four-component efficiency ([Formula: see text]%), but not two-component efficiency ([Formula: see text]%). Target-specific four-component re-configuration significantly improved efficiency ([Formula: see text]%). Both arrays produced controlled foci centered within the canal with similar 50% pressure contour dimensions: 10.8-11.9 mm (axial), 4.2-5.6 mm (lateral), and 5.9-6.2 mm (vertical). Simulation at 250 kHz also improved two- and four-component efficiency ([Formula: see text]% and [Formula: see text]%, respectively), but doubled the lateral focal dimensions. CONCLUSION: Simulation shows that the spine-specific arrays are capable of producing controlled foci in the thoracic spinal canal. SIGNIFICANCE: The complex geometry of the human spine presents geometrical and acoustical challenges for transspine ultrasound focusing, and the design of these spine-specific ultrasound arrays is crucial to the clinical translation of focused ultrasound for the treatment of spinal cord disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".