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Record W2121114611 · doi:10.1109/ultsym.2007.331

P1B-11 A 2D-Array for Transcranial Ultrasound Focusing Using Shear-Mode Conversion: A Numerical Study

2007· article· en· W2121114611 on OpenAlexafffund
Samuel Pichardo, Kullervo Hynynen

Bibliographic record

VenueProceedings/Proceedings - IEEE Ultrasonics Symposium · 2007
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersCanada Research Chairs
KeywordsShear (geology)Longitudinal waveWavefrontPhysicsAcousticsUltrasoundComputer scienceGeologyWave propagationOptics

Abstract

fetched live from OpenAlex

An incident ultrasonic acoustic wave with a frequency around 1 MHz creates longitudinal and shear waves inside the skull. Both waves propagate independently through the skull and create two longitudinal waves after the skull: a purely longitudinal wave and a longitudinal-shear-longitudinal wave. The process of the last wave is identified here as the shear-mode conversion (Sc). The interest of developing ultrasound techniques based on Scresides in the fact that the transmitted wave due to Sc has less phase-shift. The present study shows the feasibility of focusing ultrasound after the skull using a 2D-array (ScTX) conceived to take advantage of the Sc and with dimensions comparable to near-flat skull regions such as the anterior part of the frontal bone. The ScTX array is composed of two columns of 44 times 7 elements each one separated of 3 cm following its length. The configuration in column is aimed to produce an entering wavefront favorable to the shear-mode conversion. Each element is independently driven at 1 MHz and square-shaped with a length of 1.5 mm. The space between elements is 0.4 mm. The length and width of the device are, respectively, 9.7 and 5.9 cm. The new device was compared to a conventional 2D-array (CnTX) which has the same specifications of the ScTX device, with the exception of the inter-column space. The degree of focus steering of both devices was compared for depths of 1, 2, 4 and 6 cm from the inner face of the skull (dfs). For each depth, and assuming X and Y perpendicular to the sound propagation axis Z, four focal spots were tested at (x,y)=(0, 0), (2 cm, 0), (0, 2 cm) and (2 cm, 2 cm). A prismatic volume of 10.7 times 6.5 times 0.9 cm, located 1 cm from the device, was used to simulate the skull bone. The required phase of elements was calculated using a back-propagation (BP) method. Tests were done with the corrected phase calculated with only shear-mode BP (ScBP), only longitudinal BP (LnBP) and sum of both back-propagated waves (ScBP+LnBP). The resulting acoustic field for each focal point considered the forward-propagation due to the longitudinal and shear-mode transmissions. ScTX with ScBP produced the most focused fields for targets found close to the face of the skull (dfs= 1 cm) and steered following the X direction. For deeper targets (d/s= 2 cm, 4 cm, 6 cm), the correction ScBP+LnBP was more effective to focus ultrasound. For the same targets, the correction ScBP produced focal zones located closer to the device than expected. Calculation of surface area at -3 dB on XZ and YZ planes indicated that the ScTX device created more focused fields for most of tested cases, excepting a few cases involving steering following the Y direction. In conclusion, Focusing using shear mode conversion is feasible using a simple device that is compatible with the geometry of the frontal human bone. Using the proposed device, this focusing is limited to tissues located about 1 cm from the inner face of the skull.

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)0.001
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.018
GPT teacher head0.289
Teacher spread0.271 · 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

Citations0
Published2007
Admission routes2
Has abstractyes

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