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Record W2006732008 · doi:10.3109/00016489.2011.644805

High-resolution cone-beam computed tomography: a potential tool to improve atraumatic electrode design and position

2012· article· en· W2006732008 on OpenAlexaff
Sharon L. Cushing, Michael J. Daly, Claudiu Treaba, Harley Chan, Jonathan C. Irish, Susan Blasér, Karen A. Gordon, Blake C. Papsin

Bibliographic record

VenueActa Oto-Laryngologica · 2012
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of TorontoOntario Institute for Cancer ResearchSickKids FoundationPrincess Margaret Cancer CentreHospital for Sick Children
FundersCochlear
KeywordsCone beam computed tomographyElectrode arrayBiomedical engineeringCochlear implantMaterials scienceTemporal boneTomographyImage resolutionElectrodeNuclear medicineOpticsMedicineRadiologyComputed tomographyPhysicsSurgery

Abstract

fetched live from OpenAlex

CONCLUSIONS: Flat-panel cone-beam computed tomography (CBCT) is able to assess the trajectory of the implanted cochlear implant (CI) array. This is essential to determine specific effects of electrode design and surgical innovations on outcomes in cochlear implantation. CBCT is a non-invasive approach yielding similar data to histopathological analyses, with encouraging potential for use in surgical, clinical and research settings. OBJECTIVES: To examine the fidelity of CBCT imaging and custom 3D visualization in characterizing CI insertion in comparison to gold standard, histopathological examination. METHODS: Eleven human temporal bones were implanted with the 'Straight Research Array' (SRA). Post-insertion, they were imaged with a prototype mobile C-arm for intraoperative CBCT. Post-acquisition processing of low-dose CBCT images produced high-resolution 3D volumes with sub-millimetre spatial resolution (isotropic 0.2 mm(3) voxels). The bones were resin impregnated and sectioned for light microscopic examination. Dimensional electrode characteristics visible in section images were compared with corresponding CBCT images by independent observers. RESULTS: Overall, CBCT demonstrated adequate resolution to detect: 1) scala implanted; 2) kinking; 3) number of intracochlear contacts; 4) appropriate ascension of the array; and overall confirms ideal insertion. CBCT did not demonstrate adequate resolution to detect reversal of electrode contacts or basilar membrane rupture.

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 score0.656
Threshold uncertainty score0.686

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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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

Citations46
Published2012
Admission routes1
Has abstractyes

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