MétaCan
Menu
Back to cohort
Record W2762891170 · doi:10.1186/s40349-017-0105-z

Current and emerging brain applications of MR-guided focused ultrasound

2017· review· en· W2762891170 on OpenAlexaff
Ying Meng, Suganth Suppiah, Karim Mithani, Benjamin Solomon, Michael L. Schwartz, Nir Lipsman

Bibliographic record

VenueJournal of Therapeutic Ultrasound · 2017
Typereview
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsHealth Sciences CentreSunnybrook HospitalUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineFocused ultrasoundMicrobubblesUltrasoundMedical physicsUltrasound energyRadiologyNeuroscience

Abstract

fetched live from OpenAlex

MRI guided focused ultrasound is an emerging technique that uses acoustic energy to noninvasively treat intracranial disorders. At high frequencies, it can be used to raise tissue temperatures and ablate discrete brain targets with sub-millimeter accuracy. This application is currently under investigation for a broad range of clinical applications, including brain tumors, movement disorders, and psychiatric conditions. At low frequencies MRI guided focused ultrasound can be used to modulate neuronal activity and in conjunction with injected microbubbles, can open the blood-brain barrier to enhance the delivery of therapeutic compounds. The last decade has seen dramatic advances in the science of MRI guided focused ultrasound, helping elucidate both its mechanisms and potential in pre-clinical models, and its translational promise across myriad clinical applications. This review provides an update of current and emerging MRI guided focused ultrasound applications for intracranial disorders and describes future directions and challenges for the field.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.355
Teacher spread0.287 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations60
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Therapeutic UltrasoundSame topicUltrasound and Hyperthermia ApplicationsFrench-language works237,207