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Record W2945869175 · doi:10.1109/tbme.2019.2912146

A Spine-Specific Phased Array for Transvertebral Ultrasound Therapy: Design and Simulation

2019· article· en· W2945869175 on OpenAlexafffund
Rui Xu, Meaghan A. O’Reilly

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2019
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and Science
KeywordsPhased arrayUltrasonic imagingUltrasoundComputer scienceEngineeringBiomedical engineeringAcousticsPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.248
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2019
Admission routes2
Has abstractyes

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