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Record W3154190085 · doi:10.24908/iqurcp.13354

Validation of a low-cost adjustable, handheld needle guide for spine interventions

2019· article· en· W3154190085 on OpenAlexaffvenue
Julia Wiercigroch

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2019
Typearticle
Languageen
FieldEngineering
TopicMedical Imaging and Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsImaging phantomOrientation (vector space)TrajectoryBiplaneFacet (psychology)Computer scienceMedicinePoint (geometry)Computer visionMobile deviceFluoroscopyArtificial intelligenceNuclear medicineRadiologyMathematicsEngineering

Abstract

fetched live from OpenAlex


 Purpose: MR-guided injections are safer for the patient and the physician than CT-guided interventions but require a significant amount of hand-eye coordination and mental registration by the physician. We propose a low-cost, adjustable, handheld guide to assist the operator in aligning the needle in the correct orientation for the injection.
 Methods: The operator adjusts the guide to the desired insertion angle as determined by an MRI image. Next, the operator aligns the guide in the image plane using the horizontal laser and level gradient. The needle is inserted into the sleeve of the guide and inserted into the patient. To evaluate the method, two operators inserted 5 needles in two facet joints of a lumbar spine phantom. Insertion points, final points and trajectory angles were compared to the projected needle trajectory using an electromagnetic tracking system.
 Results: On their first attempt, operators were able to insert the needle into the facet joint 85% of the time. On average, operators had an insertion point error of 2.92 ± 1.57 mm, a target point error of 3.39 ± 2.28 mm, and a trajectory error of 3.98 ± 2.09 degrees.
 Conclusion: A low-cost, adjustable, handheld guide was developed to assist in correctly positioning a needle in MR-guided needle interventions. The guide is as accurate as other needle placement assistance mechanisms, including the biplane laser guides and image overlay devices when used in lumbar facet joint injections in phantoms.

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)0.002
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.094
GPT teacher head0.382
Teacher spread0.288 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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