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Record W2544775126 · doi:10.1088/0031-9155/61/22/8025

A numerical study on the oblique focus in MR-guided transcranial focused ultrasound

2016· article· en· W2544775126 on OpenAlexafffund
Alec Hughes, Yuexi Huang, Aki Pulkkinen, Michael L. Schwartz, Andrés M. Lozano, Kullervo Hynynen

Bibliographic record

VenuePhysics in Medicine and Biology · 2016
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of TorontoToronto Western HospitalHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthAcademy of FinlandCanada Research Chairs
KeywordsFocus (optics)Oblique caseTransducerTranscranial DopplerUltrasoundAcousticsPhase (matter)Resistive touchscreenComputer sciencePhysicsRadiologyOpticsMedicineComputer vision

Abstract

fetched live from OpenAlex

Recent clinical data showing thermal lesions from treatments of essential tremor using MR-guided transcranial focused ultrasound shows that in many cases the focus is oblique to the main axis of the phased array. The potential for this obliquity to extend the focus into lateral regions of the brain has led to speculation as to the cause of the oblique focus, and whether it is possible to realign the focus. Numerical simulations were performed on clinical export data to analyze the causes of the oblique focus and determine methods for its correction. It was found that the focal obliquity could be replicated with the numerical simulations to within [Formula: see text] of the clinical cases. It was then found that a major cause of the focal obliquity was the presence of sidelobes, caused by an unequal deposition of power from the different transducer elements in the array at the focus. In addition, it was found that a 65% reduction in focal obliquity was possible using phase and amplitude corrections. Potential drawbacks include the higher levels of skull heating required when modifying the distribution of power among the transducer elements, and the difficulty at present in obtaining ideal phase corrections from CT information alone. These techniques for the reduction of focal obliquity can be applied to other applications of transcranial focused ultrasound involving lower total energy deposition, such as blood-brain barrier opening, where the issue of skull heating is minimal.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.127
GPT teacher head0.336
Teacher spread0.209 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations25
Published2016
Admission routes2
Has abstractyes

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